[PDF] Multi-indicator comparative evaluation for deep Learning-Based protein sequence design methods[PDF] Multi-indicator comparative evaluation for deep Learning-Based protein sequence design methods

Motivation Proteins found in nature represent only a fraction of the vast space of possible proteins. Protein design presents an opportunity to explore and expand this protein landscape. Within protein design, protein sequence design plays a crucial …

[HTML] Heterologous Booster Immunization Based on Inactivated SARS-CoV-2 Vaccine Enhances Humoral Immunity and Promotes BCR Repertoire Development

Recent studies have indicated that sequentially administering SARS-CoV-2 vaccines can result in increased antibody and cellular immune responses. In this study, we compared homologous and heterologous immunization strategies following two …

[PDF] Recombinant neutralizing secretory IgA antibodies for preventing mucosal acquisition and transmission of SARS-CoV-2

Passive delivery of antibodies to mucosal sites might be a valuable adjunct to COVID- 19 vaccination to prevent infection, treat viral carriage, or block transmission. Neutralising monoclonal IgG antibodies are already approved for systemic delivery …

[HTML] Antibodies from dengue patients with prior exposure to Japanese encephalitis virus are broadly neutralizing against Zika virus

Exposure to multiple mosquito-borne flaviviruses within a lifetime is not uncommon; however, how sequential exposures to different flaviviruses shape the cross-reactive humoral response against an antigen from a different serocomplex has yet to be …

[HTML] Targeted checkpoint control of B cells undergoing positive selection in germinal centers by follicular regulatory T cells

Follicular regulatory T cells (Tfr) can play opposite roles in the regulation of germinal center (GC) responses. Depending on the studies, Tfr suppress or support GC and B cell affinity maturation. However, which factors determine positive vs. negative effects …

[PDF] Whole Exome Sequencing and Analysis of T Cell Receptor β & γ Repertoires in Rheumatoid Arthritis

We investigated the potential genetic variants using whole exome sequencing (WES) and evalu-ated the disease course using T cell receptor (TCR) repertoire analysis in rheumatoid arthritis (RA). Fourteen patients with RA and five healthy controls (HCs) …

[PDF] Hybrid immunity to SARS-CoV-2 arises from serological recall of IgG antibodies distinctly imprinted by infection or vaccination

We used plasma IgG proteomics to study the molecular composition and temporal durability of polyclonal IgG antibodies triggered by ancestral SARS-CoV-2 infection, vaccination, or their combination (" hybrid immunity"). Infection, whether primary or …

DOP20 Changes in systemic antibody epitope repertoires from preclinical to established Inflammatory Bowel Disease

Background Inflammatory bowel diseases (IBD), encompassing Crohn's disease (CD) and ulcerative colitis (UC), exhibit unique immunological changes early in development. Although> 300 IBD-specific antibody responses have been identified1 …

P193 Fatigued patients with Inflammatory Bowel Disease exhibit distinct systemic antibody epitope repertoires

Background Patients with inflammatory bowel diseases (IBD) frequently experience fatigue, affecting up to 80% of those with active disease and approximately 50% with quiescent disease. The exact cause of IBD-associated fatigue is often unknown …

Influence of pre-B cell receptor deficiency on the immunoglobulin repertoires in peripheral blood B cells before and after immunization

During B cell development, pre-B cell receptor (pre-BCR), comprising the immunoglobulin heavy chain (HC) and surrogate light chain (SLC), plays a crucial role. The expression of pre-BCR serves as a certification of HC quality, confirming its …

[PDF] AT cell-based SARS-CoV-2 spike protein vaccine provides protection without antibodies

Manuscript T cell-based SARS2 DNA vaccine_111824 Page 1 1 AT cell-based SARS-CoV-2 spike protein vaccine provides protection without antibodies 1 2 Juan Shi1#, Jian Zheng2,7#, Xiujuan Zhang3#, Wanbo Tai3#, Ryan Compas4#, Jack Deno4 …

Adaptive immune receptor repertoire analysis

B cell and T cell receptor repertoires compose the adaptive immune receptor repertoire (AIRR) of an individual. The AIRR is a unique collection of antigen-specific receptors that drives adaptive immune responses, which in turn is imprinted in each individual AIRR. This supports the concept that the AIRR could determine disease outcomes, for example in autoimmunity, infectious disease and cancer. AIRR analysis could therefore assist the diagnosis, prognosis and treatment of human …

[PDF] Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG1 antibody

Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically≤ 2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly≥ 100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here …

[PDF] FoldExplorer: Fast and Accurate Protein Structure Search with Sequence-Enhanced Graph Embedding

The advent of highly accurate protein structure prediction methods has fueled an exponential expansion of the protein structure database. Consequently, there is a rising demand for rapid and precise structural homolog search. Traditional alignment …

[HTML] Bursts of communication increase opinion diversity in the temporal Deffuant model

Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or consensus and whether polarisation can be avoided, particularly on social media. In this paper, we hypothesise that not only network structure but also the timings of social interactions regulate the emergence of opinion clusters. We …

ACPScanner: Prediction of Anticancer Peptides by Integrated Machine Learning Methodologies

Novel therapeutic alternatives for cancer treatment are increasingly attracting global research attention. Although chemotherapy remains a primary clinical solution, it often results in significant side effects for patients. In recent years, anticancer peptides (ACPs) have emerged as promising candidates for highly specific anticancer drugs, and a number of computational approaches have been developed to identify ACPs. However, existing methods do not recognize specific types of …

[HTML] PSSP-MFFNet: A Multifeature Fusion Network for Protein Secondary Structure Prediction

Protein secondary structure prediction (PSSP) is a fundamental task in modern bioinformatics research and is particularly important for uncovering the functional mechanisms of proteins. To improve the accuracy of PSSP, various general and …

Anti-Cancer Peptides Identification and Activity Type Classification with Protein Sequence Pre-training

Cancer remains a significant global health challenge, responsible for millions of deaths annually. Addressing this issue necessitates the discovery of novel anti-cancer drugs. Anti-cancer peptides (ACPs), with their unique ability to selectively target cancer cells, offer new hope in discovering low side-effect anti-cancer drugs. However, the process of discovering novel ACPs is both time-consuming and costly. Therefore, there is an urgent need for a computational method that can predict …

[PDF] Optimization for machine learning: Memory-efficient and tractible solutions to large-scale non-convex systems

Neural networks generally require large amounts of data to adequately model thedomain space. In situations where the data are limited, the predictions from these models, which are typically obtained from stochastic gradient descent (SGD) minimization algorithms, can be poor. In addition, the data is commonly corrupted due to poor imaging appatus. In these cases, the use of more sophisticated optimization approaches and model architectures becomes crucial to increase the …

Exploiting Structure in Learning: A Path Toward Building Safe and Adaptive Robots

As robots venture into real-world applications, there is an increasing need for them to effectively learn from experience and adapt to unseen situations. This thesis addresses a few critical challenges to practical robot learning, including safety and sample efficiency. The main perspective of this thesis is to leverage various types of structure, ranging from explicit domain knowledge about robotics problem, such as system dynamics, task decomposition, etc., to hidden structure in robotics data. Such …

Identifying Host Factors That Inhibit HIV-1 Infection in Primary CD4+ T Cells

Cellular antiviral factors comprise one of the first lines of defense against viral infection. In the case of HIV-1, it is well established that the early stages of natural infection are inefficient, characterized by infrequent transmission, a severe bottleneck in viral genetic diversity during transmission, and variable viral loads between individuals in the first weeks of infection. Because HIV-1 transmission and acute infection occur prior to the onset of adaptive immune responses, cell-intrinsic factors …

Three-dimensional structure prediction of [GADS]-proteins as tentative primitive proteins

Abstract [GADV]-protein is a random peptide constructed from glycine (G), alanine (A), aspartic acid (D), and valine (V), whereas [GADS]-protein is constructed from G, A, D, and serine (S). Both [GADV]-and [GADS]-proteins are candidates of primitive …

[PDF] Accurate Prediction of Protein-Ligand Interactions by Combining Physical Energy Functions and Graph-Neural Networks

While current computer-aided drug discovery methods offer accuracy or computational efficiency in predicting protein-ligand binding affinities, they face challenges in large-scale virtual screenings. Although promising, machine-learning …

[PDF] BATMAN: Improved T cell receptor cross-reactivity prediction benchmarked on a comprehensive mutational scan database

Predicting T cell receptor (TCR) activation is challenging due to the lack of both unbiased benchmarking datasets and computational methods that are sensitive to small mutations to a peptide. To address these challenges, we curated a …

[PDF] Analysis of the Adaptive Immune Receptor Repertoire Alongside Treatment with Ocrelizumab

Analysis of the Adaptive Immune Receptor Repertoire Alongside Treatment with Ocrelizumab Page 1 Analysis of the Adaptive Immune Receptor Repertoire Alongside Treatment with Ocrelizumab T Schneider-Hohendorf,1 F Rubelt,2 H Mirebrahim,2 H …

[HTML] Human coronavirus OC43-elicited CD4+ T cells protect against SARS-CoV-2 in HLA transgenic mice

Abstract SARS-CoV-2-reactive T cells are detected in some healthy unexposed individuals. Human studies indicate these T cells could be elicited by the common cold coronavirus OC43. To directly test this assumption and define the role of OC43 …

[PDF] Non-classical CD45RBlo memory B-cells are the majority of circulating antigen-specific B-cells following mRNA vaccination and COVID-19 infection.

Resting memory B-cells can be divided into classical and non-classical groups based on differential expression of markers such as CD27 and CD11c, while activated memory B-cells express a combination of markers, making their ontogeny …

[PDF] A novel strategy for an anti-idiotype vaccine: nanobody mimicking neutralization epitope of porcine circovirus type 2

Vaccination is the most effective method to protect humans and animals from diseases. Anti-idiotype vaccines are safer due to their absence of pathogens. However, the commercial production of traditional anti-idiotype vaccines using …

Vaccine-Boosted CCP Decreases Virus Replication and Hastens Resolution of Infection Despite Transiently Enhancing Disease in SARS-CoV-2–Infected Hamsters

Definitive data demonstrating the utility of coronavirus disease 2019 (COVID-19) convalescent plasma (CCP) for treating immunocompromised patients remains elusive. To better understand the mechanism of action of CCP, we studied viral …

CD4+ T cells with latent HIV-1 have reduced proliferative responses to T cell receptor stimulation

The latent reservoir for HIV-1 in resting CD4+ T cells persists despite antiretroviral therapy as a barrier to cure. The antigendriven proliferation of infected cells is a major mechanism of reservoir persistence. However, activation through the T cell …

[HTML] Inactive-enriched machine-learning models exploiting patent data improve structure-based virtual screening for PDL1 dimerizers

Abstract Introduction Small-molecule Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD1/PDL1) inhibition via PDL1 dimerization has the potential to lead to inexpensive drugs with better cancer patient outcomes and …

Predicting protein thermal stability changes upon single and multi-point mutations via restricted attention subgraph neural network

Accurate prediction of protein stability changes due to mutations is instrumental for understanding mechanisms of disease and drug failure, as well as for engineering tailored protein-based materials. In recent years, computational tools using machine …

[HTML] SiFT: uncovering hidden biological processes by probabilistic filtering of single-cell data

Cellular populations simultaneously encode multiple biological attributes, including spatial configuration, temporal trajectories, and cell-cell interactions. Some of these signals may be overshadowed by others and harder to recover, despite the great …

[PDF] MoCHI: neural networks to fit interpretable models and quantify energies, energetic couplings, epistasis and allostery from deep mutational scanning data

The massively parallel nature of deep mutational scanning (DMS) allows the quantification of the phenotypic effects of thousands of perturbations in a single experiment. We have developed MoCHI, a software tool that allows the …

[HTML] Protein design meets biosecurity

The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine …

[PDF] A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification

Although supervised machine learning is popular for information extraction from clinical notes, creating large annotated datasets requires extensive domain expertise and is time-consuming. Meanwhile, large language models (LLMs) have …

[PDF] BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction

As a novel and effective fine-tuning paradigm based on large-scale pre-trained language models (PLMs), prompt-tuning aims to reduce the gap between downstream tasks and pre-training objectives. While prompt-tuning has yielded …

[PDF] Changing fitness effects of mutations through long-term bacterial evolution

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of …

[PDF] BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion Models

Recent text-to-image generation models have demonstrated incredible success in generating images that faithfully follow input prompts. However, the requirement of using words to describe a desired concept provides limited control over the …

Interrogating the Effects of T Cell Receptor Engineering Strategies on TCR Specificity

The hallmark of the adaptive immune system is the ability to discriminate between “self” and “non-self”. A crucial component that allows for this discrimination are T cell with their specialized T cell receptors (TCR) and the peptide major histocompatibility complex (MHC) proteins that they recognize. Through the interrogation of peptides derived from intracellular proteins displayed on MHC complexes, T cells are able to interrogate the health of the cells in the body. The ability of T cells to identify …

[HTML] Designing, cloning and simulation studies of cancer/testis antigens based multi-epitope vaccine candidates against cutaneous melanoma: An immunoinformatics …

Background Melanoma is the most fatal kind of skin cancer. Among its various types, cutaneous melanoma is the most prevalent one. Melanoma cells are thought to be highly immunogenic due to the presence of distinct tumor-associated antigens …

[HTML] Investigation into Cardiac Myhc-α 334–352-Specific TCR Transgenic Mice Reveals a Role for Cytotoxic CD4 T Cells in the Development of Cardiac Autoimmunity

Myocarditis is one of the major causes of heart failure in children and young adults and can lead to dilated cardiomyopathy. Lymphocytic myocarditis could result from autoreactive CD4+ and CD8+ T cells, but defining antigen specificity in disease …

[HTML] MVA-based vaccine candidates encoding the native or prefusion-stabilized SARS-CoV-2 spike reveal differential immunogenicity in humans

In response to the COVID-19 pandemic, multiple vaccines were developed using platforms such as viral vectors and mRNA technology. Here, we report humoral and cellular immunogenicity data from human phase 1 clinical trials investigating two …

[PDF] Functional impairment of" helpless" CD8+ memory T cells is transient and driven by prolonged but finite cognate antigen presentation

Generation of functional CD8+ T cell memory typically requires engagement of CD4+ T cells. However, in certain scenarios, such as acutely-resolving viral infections, effector (TE) and subsequent memory (TM) CD8+ T cell formation appear impervious …

De novo design of obligate ABC heterotrimeric proteins

Disclosed are polypeptides having an amino acid sequence at least 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% identical to the amino acid sequence selected from the group consisting of the amino acid sequences listed in Tables 1, 2, and 3, and heteropolymers formed from such polypeptides.

[HTML] Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution

The utility of genetically encoded biosensors for sensing the activity of signaling proteins has been hampered by a lack of strategies for matching sensor sensitivity to the physiological concentration range of the target. Here we used computational …

Classifying Protein–Protein Binding Affinity with Free-Energy Calculations and Machine Learning Approaches

Understanding the intricate phenomenon of neuronal wiring in the brain is of great interest in neuroscience. In the fruit fly, Drosophila melanogaster, the Dpr-DIP interactome has been identified to play an important role in this process. However …

[HTML] Proteomics, modeling, and fluorescence assays delineate cytochrome b5 residues involved in binding and stimulation of cytochrome P450 17A1 17, 20-lyase

Abstract Cytochrome b 5 (b 5) is known to stimulate some catalytic activities of cytochrome P450 (P450, CYP) enzymes, although mechanisms still need to be defined. The reactions most strongly enhanced by b 5 are the 17, 20-lyase reactions of P450 17A1 involved in steroid biosynthesis. We had previously used a fluorescently labeled human b 5 variant (Alexa 488-T70C-b 5) to characterize human P450 17A1-b 5 interactions, but subsequent proteomic analyses indicated that …

[HTML] Re-Engineering Therapeutic Anti-Aβ Monoclonal Antibody to Target Amyloid Light Chain

Amyloidosis involves the deposition of misfolded proteins. Even though it is caused by different pathogenic mechanisms, in aggregate, it shares similar features. Here, we tested and confirmed a hypothesis that an amyloid antibody can be engineered by a few mutations to target a different species. Amyloid light chain (AL) and β-amyloid peptide (Aβ) are two therapeutic targets that are implicated in amyloid light chain amyloidosis and Alzheimer's disease, respectively. Though crenezumab, an …

Threonine and Polythreonine Accelerate Calcium Carbonate Formation

Acidic macromolecules are considered to be critical to calcium carbonate formation in organisms and have been chosen as a model chemical for modifying biomineralization. Here, this view is challenged, and it is found that low-charge amino acid threonine (Thr) and its polymer poly-Thr can accelerate calcium carbonate formation by increasing nucleation. In contrast to aspartic acid (Asp) and poly-Asp, Thr and poly-Thr did not affect the morphology of product crystals but …

[HTML] Empirical validation of ProteinMPNN's efficiency in enhancing protein fitness

Introduction: Protein engineering, which aims to improve the properties and functions of proteins, holds great research significance and application value. However, current models that predict the effects of amino acid substitutions often perform poorly when evaluated for precision. Recent research has shown that ProteinMPNN, a large-scale pre-training sequence design model based on protein structure, performs exceptionally well. It is capable of designing mutants with structures similar …

[PDF] Topological characterization of the continuum of allosteric response

Allosteric regulation in proteins is often accompanied by conformational changes that facilitate transmission of mechanical signals between distant ligand binding sites. Typically, these deformations are classified in terms of specific archetypes, including various types of hinge mechanisms or allosteric pathways localized to sequences of amino acids. However, many allosteric deformations resist such strict categorization. Here, we introduce a quantitative topological description of allosteric deformation …

[PDF] Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge

Abstract The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS …

Elucidating N-Glycan Microheterogeneity Through Site-Specific Mass Spectrometry Approaches

N-glycans are essential to eukaryotic biology and are important modulators of glycoprotein folding, stability, binding, and other functions. Glycoproteins often host multiple sites of N-glycosylation, each of which is modified by an extensive non-template process as the glycoprotein folds and travels through the secretory pathway. Each site of N-glycosylation on an individual glycoprotein hosts its own distinct distribution of glycoforms which often denote details of their incomplete …

[HTML] Mucosal Immunity against SARS-CoV-2 in the Respiratory Tract

The respiratory tract, the first-line defense, is constantly exposed to inhaled allergens, pollutants, and pathogens such as respiratory viruses. Emerging evidence has demonstrated that the coordination of innate and adaptive immune responses in the respiratory tract plays a crucial role in the protection against invading respiratory pathogens. Therefore, a better understanding of mucosal immunity in the airways is critical for the development of novel therapeutics and next-generation vaccines …

[HTML] Design of consensus toxins and their use for the discovery of broadly neutralizing antibodies

Snakebite envenoming remains a significant global health challenge, impacting millions of people annually, particularly in regions with limited access to medical care. The primary treatment for snakebite envenoming is antivenom, which consists of polyclonal antibodies derived from the immunization of large animals with snake venom. However, this traditional method poses challenges, including the need to extract venom from snakes, the use of big animals in the manufacturing process, the …

[PDF] Maximum Mismatch between Six-Residue Sequences of SARS-CoV-2 Spike Proteins and Human Proteome

A first step toward finding effective antivirals for Covid-19 may be the identification of immunogenic, conserved, short and accessible epitopes on the surface molecules of human coronavirus. An important requirement, however, would be to be sure these epitopes do not align well with human proteins, thereby reducing the possibility of off-target interactions by the antiviral. So far, the focus of the medical and scientific communities has been on finding vaccines that can combat the disease …

[PDF] Sample Efficient Deep Learning Methods for Reinforcement Learning and Bioimaging/submitted by Markus Hofmarcher

Deep learning (DL) has emerged as a pivotal technology, with applications spanning across various domains. Among the sub-fields of deep learning, supervised learning has paved the way for advancements by leveraging labeled data. Another key area, reinforcement learning (RL), learns optimal behaviors through interaction with an environment. Each area presents unique applications, successes, and challenges that demand extensive datasets.

[HTML] Variation in the basal immune state and implications for disease

Analysis of pre-existing immunity and its effects on acute infection often focus on memory responses associated with a prior infectious exposure. However, memory responses occur in the context of the overall immune state and leukocytes must interact with their microenvironment and other immune cells. Thus, it is important to also consider non-antigen-specific factors which shape the composite basal state and functional capacity of the immune system, termed here as I0 ('I naught'). In this …

[PDF] NeoHunter: Flexible software for systematically detecting neoantigens from sequencing data

Complicated molecular alterations in tumors generate various mutant peptides. Some of these mutant peptides can be presented to the cell surface and then elicit immune responses, and such mutant peptides are called neoantigens. Accurate detection of neoantigens could help to design personalized cancer vaccines. Although some computational frameworks for neoantigen detection have been proposed, most of them can only detect SNV‐and indel‐derived neoantigens. In …

[PDF] Integrative single-cell multi-omics of CD19CARpos and CARneg T cells suggest drivers of immunotherapy response in B-cell neoplasias

How phenotypic, clonal, and functional heterogeneity of the CAR-T-cells impact clinical outcomes remain understudied. Here, we integrated clonal kinetics with transcriptomic heterogeneity resolved by single-cell omics to explore cellular …

[HTML] Human tumor-associated macrophages and neutrophils regulate anti-tumor antibody efficacy through lethal and sublethal trogocytosis

The clinical benefits of tumor-targeting antibodies (tAbs) are modest in solid human tumors. The efficacy of many tAbs is dependent on Fc Receptor (FcR)-expressing leukocytes that bind Fc fragments of tAb. Tumor-associated macrophages (TAM) and …

[HTML] LRP11 promotes stem-like T cells via MAPK13-mediated TCF1 phosphorylation, enhancing anti-PD1 immunotherapy

Background Tumor-infiltrating T cells enter an exhausted or dysfunctional state, which limits antitumor immunity. Among exhausted T cells, a subset of cells with features of progenitor or stem-like cells has been identified as TCF1+ CD8+ T cells …

[HTML] Digital twins elucidate critical role of Tscm in clinical persistence of TCR-engineered cell therapy

Despite recent progress in adoptive T cell therapy for cancer, understanding and predicting the kinetics of infused T cells remains a challenge. Multiple factors can impact the distribution, expansion, and decay or persistence of infused T cells in …

[PDF] CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment

SARS-CoV-2 is the causative agent of COVID-19 and continues to pose a significant public health threat throughout the world. Following SARS-CoV-2 infection, virus-specific CD4+ and CD8+ T cells are rapidly generated to form effector and memory …

Bone Mineral Density is Related to CD4+ T Cell Counts and Muscle Mass is Associated with B Cells in Common Variable Immunodeficiency Patients

Background: Common variable immunodeficiency (CVID) is a primary immunodeficiency characterized by chronic/recurrent respiratory infections, bronchiectasis, autoimmunity, inflammatory, gastrointestinal diseases and …

[PDF] Diverse Database and Machine Learning Model to narrow the generalization gap in RNA structure prediction

Understanding macromolecular structures, such as proteins and nucleic acids, is critical for discerning their functions and biological roles. Advanced techniques like crystallography, NMR, and CryoEM have facilitated the determination of over …

[PDF] RNA Secondary Structure Prediction Using a Genetic Algorithm with a Selection Method Based on Free Energy Value and Topological Index

This paper presents a genetic algorithm designed to predict RNA secondary structures, which utilizes selection criteria based on free energy (fitness) and topological similarity. This approach represents structural information using a simple …

[HTML] Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations

Flavin mononucleotide riboswitches are common among many pathogenic bacteria and are therefore considered to be an attractive target for antibiotics development. The riboswitch binds riboflavin (RBF, also known as vitamin B2), and although an …

[HTML] Development and use of machine learning algorithms in vaccine target selection

Computer-aided discovery of vaccine targets has become a cornerstone of rational vaccine design. In this article, I discuss how Machine Learning (ML) can inform and guide key computational steps in rational vaccine design concerned with the identification of B and T cell epitopes and correlates of protection. I provide examples of ML models, as well as types of data and predictions for which they are built. I argue that interpretable ML has the potential to improve the identification of …

Deep learning boosted amyloidosis diagnosis

Amyloid light chain (AL) amyloidosis is a disorder characterized by the deposition of antibody light chains in organs. Early and accurate diagnosis of AL amyloidosis is crucial for timely implementation of appropriate treatment strategies. However, existing computational methods for predicting AL amyloidosis often heavily rely on manually extracted features and their performance is less than satisfactory. In this study, we introduce DeepAL, a deep learning-based approach designed to predict …

[PDF] AFM-RL: Large Protein Complex Docking Using AlphaFold-Multimer and Reinforcement Learning

Various biological processes in living cells are carried out by protein complexes, whose interactions can span across multiple protein structures. To understand the molecular mechanisms of such processes, it is crucial to know the quaternary …

Computational approaches for antibody-based drug design

This chapter focuses on the structure-function-dynamics of antibodies and their importance in the pharmaceutical sector and summarizes how recent computational tools play a vital role in the development and production of antibody and antibody- based therapeutics. We present here general protocols for how to use current computational tools efficiently. In the last part of this chapter, we focus on the great market value of these antibody-based targeted therapies, growing investment of … • Cites: ‪Deciphering the language of antibodies using self-supervised …‬

Computational approaches for antibody-based targeted drug delivery strategies

In this chapter, we will look at the computational tools and techniques that have been employed in the development of antibody-based targeted drug delivery schemes, such as antibody design and optimization, pharmacokinetic modelling, and molecular simulation. We will also explore the obstacles and potential developments in this subject. • Cites: ‪Observed antibody space: a resource for data mining next …‬

Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics

Abstract Machine learning is increasingly used to discover diagnostic and prognostic biomarkers from high-dimensional molecular data. However, a variety of factors related to experimental design may affect the ability to learn generalizable and clinically applicable diagnostics. Here we argue that a causal perspective improves the identification of these challenges and formalizes their relation to the robustness and generalization of machine learning-based diagnostics. To make for a concrete … • Cites: ‪Individualized VDJ recombination predisposes the available Ig …‬

[PDF] Techniques for Theoretical Prediction of Immunogenic Peptides

Small peptides are an important component of the vertebrate immune system. They are important molecules for distinguishing proteins that originate in the host from proteins derived of a pathogenic organism, such as a virus or bacterium …

[HTML] Case report: Insulinomatosis: description of four sporadic cases and review of the literature

The best-known etiologies of hyperinsulinemic hypoglycemia are insulinoma, non- insulinoma pancreatogenous hypoglycemic syndrome, autoimmune processes, and factitious hypoglycemia. In 2009, a disease not associated with classic genetic syndromes and characterized by the presence of multiple pancreatic lesions was described and named insulinomatosis. We present the clinical and pathologic features of four patients with the diagnosis of insulinomatosis, aggregated new … • Cites: ‪New regions with molecular alterations in a rare case of …‬

[PDF] The multilevel extensive diversity across the cynomolgus macaque captured by ultra-deep adaptive immune receptor repertoire sequencing

2024 The extent to which AIRRs differ among and within individuals remains elusive. Via ultra-deep repertoire sequencing of 22 and 25 tissues in three cynomolgus macaques, respectively, we identified 84 and 114 novel IGHV and TRBV alleles, confirming 72 (85.71%) and 100 (87.72%) of them. The heterogeneous V gene usage patterns were influenced, in turn, by genetics, isotype (for BCRs only), tissue group, and tissue. A higher proportion of intragroup shared clones in the intestinal … • Cites: ‪Systems analysis reveals high genetic and antigen-driven …‬

[HTML] mRNA-based precision targeting of neoantigens and tumor-associated antigens in malignant brain tumors

Background Despite advancements in the successful use of immunotherapy in treating a variety of solid tumors, applications in treating brain tumors have lagged considerably. This is due, at least in part, to the lack of well-characterized antigens expressed within brain tumors that can mediate tumor rejection; the low mutational burden of these tumors that limits the abundance of targetable neoantigens; and the immunologically “cold” tumor microenvironment that hampers the generation of … • Cites: ‪MiXCR: software for comprehensive adaptive immunity profiling‬

[PDF] Multiple vaccine comparison in the same adults from the VITAL study reveals vaccine-specific and age-related humoral response patterns.

Vaccine responsiveness is often reduced in older adults. Yet, our lack of understanding of low vaccine responsiveness hampers the development of effective vaccination strategies to reduce the impact of infectious diseases in the ageing population. Young-adult, middle-aged and older-adult participants of the VITAL clinical trials (n= 315, age range: 28-98y), were consecutively vaccinated with a booster quadrivalent influenza (QIV) vaccine, a primary 13-valent pneumococcal … • Cites: ‪The changing landscape of naive T cell receptor repertoire with …‬

[HTML] Innovations in monoclonal antibody-based multipurpose prevention technology (MPT) for the prevention of sexually transmitted infections and unintended pregnancy

Monoclonal antibodies (mAbs) are currently being produced for a number of clinical applications including contraception and the prevention of sexually transmitted infections (STIs). Combinations of contraceptive and anti-STI mAbs, including antibodies against HIV-1 and HSV-2, provide a powerful and flexible approach for highly potent and specific multipurpose prevention technology (MPT) products with desirable efficacy, safety and pharmacokinetic profiles. MAbs can be administered … • Cites: ‪Optimization of therapeutic antibodies by predicting antigen …‬

[PDF] Learning predictive signatures of HLA type from T-cell repertoires

T cells recognize a wide range of pathogens using surface receptors that interact directly with peptides presented on major histocompatibility complexes (MHC) encoded by the HLA loci in humans. Understanding the association between T cell …

[HTML] Characterization of T cell receptor repertoire in penile cancer

Tumor-infiltrating lymphocytes (TILs) play a key role in regulating the host immune response and shaping tumor microenvironment. It has been previously shown that T cell infiltration in penile tumors was associated with clinical outcomes. However, few …

[PDF] Optimizing Accuracy and Efficiency in Analyzing Non-UMI Liquid Biopsy Datasets Using the Sentieon ctDNA Pipeline

Sequencing clinical liquid biopsy, especially circulating tumor DNA (ctDNA), provides a valuable method for identifying low allele frequency tumor variants, opening novel clinical applications, particularly in treatment selection for late-stage cancer patients. Despite advancements, challenges in assay development persist, primarily due to limited sample volumes and insufficiency of reads supporting low allele frequency variants. The allele frequencies of clinically significant variants often …

[PDF] Machine learning and computational analyses of adaptive immune receptors

Every day, our immune system fights off potential threats such as viruses, bacteria or cancer cells. The key molecules used to recognise and memorise these antigens are so-called 'adaptive immune receptors'. Recent technological advancements allow us …

[PDF] Scientific Large Language Models: A Survey on Biological & Chemical Domains

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional linguistic boundaries, encompassing specialized linguistic systems developed within various scientific disciplines. This growing interest has led to the advent of scientific LLMs, a novel subclass specifically engineered for facilitating scientific discovery. As …

[PDF] Integrative analysis of pathogenic variants in glucose-6-phosphatase based on an AlphaFold2 model

Mediating the terminal reaction of gluconeogenesis and glycogenolysis, the integral membrane protein G6PC1 regulates hepatic glucose production by catalyzing hydrolysis of glucose-6-phosphate (G6P) within the lumen of the endoplasmic reticulum. Consistent with its vital contribution to glucose homeostasis, inactivating mutations in G6PC1 cause glycogen storage disease (GSD) type 1a characterized by hepatomegaly and severe hypoglycemia. Despite its physiological importance …

[PDF] Longitudinal Study on Seroprevalence and Immune Response to SARS-CoV-2 in a Population of Food and Retail Workers Through Transformation of ELISA Datasets

Since the onset of the global pandemic caused by the emergence and spread of SARS-CoV-2 in early 2020, numerous studies have been conducted worldwide to understand our immune response to the virus. This study investigates the humoral response elicited by vaccination and by SARS-CoV-2 infection in the poorly studied food and retail workers in the Quebec City area. The 1.5-year study period spans from early 2021, when vaccination became available in this region, to mid-2022 …

[PDF] Emergence of collective phenomena and formation of cell colonies from cell individual characteristics. Applied modeling and simulations.

Biological systems are known for their complexity, as they comprise multiple components that interact with each other, often in sophisticated ways. However, biological systems are inherently physical systems as well, so that their behavior can be predicted in principle using general physical laws. The ever growing available computational power and the development of novel algorithms is providing the necessary framework for such approach. The present thesis focuses on cell …

[HTML] Identification of a highly conserved neutralizing epitope within the RBD region of diverse SARS-CoV-2 variants

The constant emergence of SARS-CoV-2 variants continues to impair the efficacy of existing neutralizing antibodies, especially XBB. 1.5 and EG. 5, which showed exceptional immune evasion properties. Here, we identify a highly conserved …

AI-driven covalent drug design strategies targeting main protease (mpro) against SARS-CoV-2: structural insights and molecular mechanisms

The emergence of new SARS-CoV-2 variants has raised concerns about the effectiveness of COVID-19 vaccines. To address this challenge, small-molecule antivirals have been proposed as a crucial therapeutic option. Among potential …

Immunoinformatics-driven In silico vaccine design for Nipah virus (NPV): Integrating machine learning and computational epitope prediction

The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India. Currently, there are no specific …

[PDF] Repurposing an endogenous degradation domain for antibody-mediated disposal of cell-surface proteins

The exquisite specificity of antibodies can be harnessed to effect targeted degradation of membrane proteins. Here, we demonstrate targeted protein removal utilising a protein degradation domain derived from the endogenous human protein …

Development of a potent recombinant scFv antibody against the SARS-CoV-2 by in-depth bioinformatics study: Paving the way for vaccine/diagnostics development

Abstract Background The SARS-CoV-2 has led to a worldwide disaster. Thus, developing prophylactics/therapeutics is required to overcome this public health issue. Among these, producing the anti-SARS-CoV-2 single-chain variable fragment (scFv) antibodies has attracted a significant attention. Accordingly, this study aims to address this question: Is it possible to bioinformatics-based design of a potent anti-SARS-CoV-2 scFv as an alternative to current production approaches? Method …

Ligand-based virtual screening and biological evaluation of inhibitors of Mycobacterium tuberculosis H37Rv

Novel antimycobacterial compounds are needed to expand the existing toolbox of therapeutic agents, which sometimes fail to be effective. In our study we extracted, filtered, and aggregated the diverse data on antimycobacterial activity of chemical …

[PDF] Single-cell RNA-seq reveals TCR clonal expansion and a high frequency of transcriptionally distinct double-negative T cells in NOD mice

T cells primarily drive the autoimmune destruction of pancreatic beta cells in Type 1 diabetes (T1D). However, the profound yet uncharacterized diversity of the T cell populations in vivo has hindered obtaining a clear picture of the T cell changes that …

[HTML] A large-scale study of peptide features defining immunogenicity of cancer neo-epitopes

Accurate prediction of immunogenicity for neo-epitopes arising from a cancer associated mutation is a crucial step in many bioinformatics pipelines that predict outcome of checkpoint blockade treatments or that aim to design personalised …

Enhancing Antigenic Peptide Discovery: Improved MHC-I Binding Prediction and Methodology

Abstract The Major Histocompatibility Complex (MHC) is a critical element of the vertebrate cellular immune system, responsible for presenting peptides derived from intracellular proteins. MHC-I presentation is pivotal in the immune response and …

[HTML] An analysis pipeline for understanding 6-thioguanine effects on a mouse tumour genome

Mouse tumour models are extensively used as a pre-clinical research tool in the field of oncology, playing an important role in anticancer drugs discovery. Accordingly, in cancer genomics research, the demand for next-generation sequencing (NGS) is …

DRBpred: A sequence-based machine learning method to effectively predict DNA-and RNA-Binding residues

DNA-binding and RNA-binding proteins are essential to an organism's normal life cycle. These proteins have diverse functions in various biological processes. DNA-binding proteins are crucial for DNA replication, transcription, repair, packaging, and …

Large language models improve annotation of prokaryotic viral proteins

Viral genomes are poorly annotated in metagenomic samples, representing an obstacle to understanding viral diversity and function. Current annotation approaches rely on alignment-based sequence homology methods, which are limited by the paucity of characterized viral proteins and divergence among viral sequences. Here we show that protein language models can capture prokaryotic viral protein function, enabling new portions of viral sequence space to be assigned …

[PDF] A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics

In drug discovery, molecular dynamics (MD) simulation for protein-ligand binding provides a powerful tool for predicting binding affinities, estimating transport properties, and exploring pocket sites. There has been a long history of improving …

[PDF] Mitochondrial Transplantation promotes protective effector and memory CD4+ T cell response during Mycobacterium tuberculosis infection and diminishes exhaustion …

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (M. tb), remains a significant health concern worldwide, especially in populations with weakened or compromised immune systems, such as the elderly. Proper adaptive …

[HTML] Personalized neoantigen vaccine enhances the therapeutic efficacy of bevacizumab and anti-PD-1 antibody in advanced non-small cell lung cancer

Clinically, a considerable number of non-small cell lung cancer (NSCLC) patients are unable to receive or resist chemotherapy, and the efficacy of non-chemotherapy treatment strategies based on anti-angiogenic agents combined with immune …

[HTML] Id2 epigenetically controls CD8+ T-cell exhaustion by disrupting the assembly of the Tcf3-LSD1 complex

CD8+ T-cell exhaustion is a state of dysfunction that promotes tumor progression and is marked by the generation of Slamf6+ progenitor exhausted (Texprog) and Tim-3+ terminally exhausted (Texterm) subpopulations. Inhibitor of DNA binding protein 2 …

[PDF] A RANDOMIZED PHASE 1 TRIAL OF NEOANTIGEN DNA VACCINE ALONE VS. NEOANTIGEN VACCINE PLUS DURVALUMAB IN TRIPLE NEGATIVE BREAST …

Study Design: This is a single institution, open-label randomized phase 1 trial of neoantigen DNA vaccine alone vs. neoantigen DNA vaccine plus durvalumab in triple negative breast cancer (TNBC) patients who have residual disease following …

[PDF] Endowing Protein Language Models with Structural Knowledge

Understanding the relationships between protein sequence, structure and function is a long-standing biological challenge with manifold implications from drug design to our understanding of evolution. Recently, protein language models have emerged as the preferred method for this challenge, thanks to their ability to harness large sequence databases. Yet, their reliance on expansive sequence data and parameter sets limits their flexibility and practicality in real-world scenarios. Concurrently, the …

[HTML] The Inhibition Effect of Epigallocatechin-3-Gallate on the Co-Aggregation of Amyloid-β and Human Islet Amyloid Polypeptide Revealed by Replica Exchange …

Alzheimer's disease and Type 2 diabetes are two epidemiologically linked diseases which are closely associated with the misfolding and aggregation of amyloid proteins amyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP), respectively. The co …

[HTML] Flexible structural arrangement and DNA-binding properties of protein p6 from Bacillus subtillis phage φ29

The genome-organizing protein p6 of Bacillus subtilis bacteriophage φ29 plays an essential role in viral development by activating the initiation of DNA replication and participating in the early-to-late transcriptional switch. These activities require the …

Atomic force microscope kymograph analysis: A case study of two membrane proteins

Kymograph analysis is employed across the biological atomic force microscopy (AFM) community to boost temporal resolution. The method is well suited for revealing protein dynamics at the single molecule level in near-native conditions …

[PDF] FBM: Freestanding bilayer microscope for single-molecule imaging of membrane proteins

Integral membrane proteins (IMPs) constitute a large fraction of organismal proteomes, playing fundamental roles in physiology and disease. Despite their importance, the mechanisms underlying dynamic features of IMPs, such as …

[PDF] LocaPep: Localization of Epitopes on Protein Surfaces Using Peptides from Phage Display Libraries

The use of peptides from a phage display library selected by binding to a given antibody is a widespread technique to probe epitopes of antigenic proteins. However, the identification of interaction sites mimicked by these peptides on the …

[HTML] Generation and optimization of off-the-shelf immunotherapeutics targeting TCR-Vβ2+ T cell malignancy

Current treatments for T cell malignancies encounter issues of disease relapse and off-target toxicity. Using T cell receptor (TCR) Vβ2 as a model, here we demonstrate the rapid generation of an off-the-shelf allogeneic chimeric antigen receptor (CAR)-T …

[HTML] Multistep tumor genetic evolution and changes in immunogenicity trigger immune-mediated disease eradication in stage IV melanoma: lessons from a single case

Durable remissions are observed in 10%–20% of treated patients with advanced metastatic melanoma but the factors associated with long-term complete clinical responses are largely unknown. Here, we report the molecular characteristics of …

[HTML] DisoFLAG: accurate prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model

Intrinsically disordered proteins and regions (IDPs/IDRs) are functionally important proteins and regions that exist as highly dynamic conformations under natural physiological conditions. IDPs/IDRs exhibit a broad range of molecular functions …

[PDF] Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Large language models are trained on massive scrapes of the web, which are often unstructured, noisy, and poorly phrased. Current scaling laws show that learning from such data requires an abundance of both compute and data, which grows with …

[HTML] A human antibody derived from original SARS-CoV-2 infection effectively neutralizes omicron

Abstract SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) Variants of Concern (VOCs), such as the Omicron sub-variants, present significant challenges in pandemic control due to their capacity to escape antibodies and breach vaccine …

[PDF] Hypermutation of Immunoglobulin Genes in Memory B Cells of DNA Repair–deficient Mice

To investigate the possible involvement of DNA repair in the process of somatic hypermutation of rearranged immunoglobulin variable (V) region genes, we have analyzed the occurrence, frequency, distribution, and pattern of mutations in …

Mucosal-associated invariant T (MAIT) cells exhibit restricted T cell receptor β constant region usage, obfuscating assessment of T cell clonality

Background: αβ T cells express either T cell receptor (TCR) β constant region 1 (TRBC1) or TRBC2. Flow cytometric quantification of TRBC1 expression enables rapid detection of T cell clonality in haematological malignancy and is being widely …

[PDF] Towards Unified AI Drug Discovery with Multimodal Knowledge

Background: In real-world drug discovery, human experts typically grasp molecular knowl-12 edge of drugs and proteins from multimodal sources including molecular structures, structured 13 knowledge from knowledge bases, and unstructured knowledge from biomedical literature. Ex-14 isting multimodal approaches in AI drug discovery integrate either structured or unstructured 15 knowledge independently, which compromises the holistic understanding of biomolecules. Be-16 sides, they fail …

[PDF] Quantifying the hardness of bioactivity prediction tasks for transfer learning

Today, machine learning methods are widely employed in drug discovery. However, the chronic lack of data continues to hamper their further development, validation, and application. Several modern strategies aim to mitigate the challenges associated with data scarcity by learning from data on related tasks. These knowledge-sharing approaches encompass transfer learning, multi-task learning, and meta-learning. A key question remaining to be answered for these approaches is about the extent to …

[PDF] IgM N-glycosylation correlates with COVID-19 severity and rate of complement deposition

The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been …

[PDF] A Biophysical Model for ATAC-seq Data Analysis

The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) can be used to identify open chromatin regions, providing complementary information to RNA-seq which measures gene expression by sequencing. Single-cell" multiome" methods offer the possibility of measuring both modalities simultaneously in cells, raising the question of how to analyze them jointly, and also the extent to which the information they provide is better than unregistered data …

[PDF] Transformer Encoder with Protein Language Model for Protein Secondary Structure Prediction

In bioinformatics, protein secondary structure prediction plays a significant role in understanding protein function and interactions. This study presents the TE_SS approach, which uses a transformer encoder-based model and the Ankh protein …

[PDF] ProteinMPNN Recovers Complex Sequence Properties of Transmembrane β-Barrels

Recent deep-learning (DL) protein design methods have been successfully applied to a range of protein design problems including the de novo design of novel folds, protein binders, and enzymes. However, DL methods have yet to meet the challenge …

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Abstract jats: titleAbstract</jats: title> jats: pDimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label …

[PDF] NeoMUST: an accurate and efficient multi-task learning model for neoantigen presentation

Accurate identification of neoantigens is important for advancing cancer immunotherapies. This study introduces Neoantigen MUlti-taSk Tower (NeoMUST), a model employing multi-task learning to effectively capture task-specific information …

[HTML] Beneficial effect of temporary methotrexate interruption on B and T cell responses upon SARS-CoV-2 vaccination in patients with rheumatoid arthritis or psoriatic …

B and T cell responses were evaluated in patients with rheumatoid arthritis (RA) or psoriatic arthritis (PsA) after 1 or 2 weeks of methotrexate (MTX) withdrawal following each COVID-19 vaccine dose and compared with those who maintained MTX. Adult …

A rigorous benchmarking of alignment-based HLA typing algorithms for RNA-seq data

Accurate identification of human leukocyte antigen (HLA) alleles is essential for various clinical and research applications, such as transplant matching and drug sensitivities. Recent advances in RNA-seq technology have made it possible to …

[PDF] Lower Humoral and Cellular Immunity following Asymptomatic SARS-CoV-2 Infection in Education (The ACE Cohort)

Purpose Asymptomatic SARS-CoV-2 infections were widely reported during the COVID-19 pandemic, acting as a hidden source of infection. Many existing studies investigating asymptomatic immunity failed to recruit true asymptomatic individuals …

[PDF] DCs targeted therapy expands CD8 T cell responses to bona-fide neoantigens in lung tumors

Cross-presentation by type 1 cDCs (cDC1) is critical to induce and sustain antitumoral CD8 T cell responses to model antigens, in various tumor settings. However, the impact of cross-presenting cDC1 and the potential of DC-based …

[PDF] Deep learning for protein structure prediction and design—progress and applications

Proteins are the key molecular machines that orchestrate all biological processes of the cell. Most proteins fold into three-dimensional shapes that are critical for their function. Studying the 3D shape of proteins can inform us of the mechanisms that underlie biological processes in living cells and can have practical applications in the study of disease mutations or the discovery of novel drug treatments. Here, we review the progress made in sequence-based prediction of protein structures with a …

[PDF] Generative β-Hairpin Design Using a Residue-Based Physicochemical Property Landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on …

[PDF] Predicting protein functions using positive-unlabeled ranking with ontology-based priors

Automated protein function prediction is a crucial and widely studied problem in bioinformatics. Computationally, protein function is a multilabel classification problem where only positive samples are defined and there is a large number of unlabeled …

[PDF] Language models enable zero-shot prediction of RNA secondary structures including pseudoknots

Current deep learning-based models for predicting RNA secondary structures face challenges in achieving high generalization ability. At the same time, a vast repository of unlabeled non-coding RNA (ncRNA) sequences remains untapped for …

[PDF] Making Use of Averaging Methods in MODELLER for Protein Structure Prediction

Recent advances in protein structure prediction, driven by AlphaFold 2 and machine learning, demonstrate proficiency in static structures but encounter challenges in capturing essential dynamic features crucial for understanding biological function. In …

Deciphering the crystal structure of a novel nanobody against the NEIL1 DNA glycosylase

Nanobodies (VHHs) are single-domain antibodies with three antigenic CDR regions and are used in diverse scientific applications. Here, an∼ 14 kDa nanobody (A5) specific for the endonuclease VIII (Nei)-like 1 or NEIL1 DNA glycosylase involved in …

[PDF] For antibody sequence generative modeling, mixture models may be all you need

Antibody therapeutic candidates must exhibit not only tight binding to their target but also good developability properties, especially low risk of immunogenicity. In this work, we fit a simple generative model, SAM, to sixty million human heavy and …

[HTML] A Mechanistic Understanding of the Modes of Ca2+ Ion Binding to the SARS-CoV-1 Fusion Peptide and Their Role in the Dynamics of Host Membrane Penetration

The SARS-CoV-1 spike glycoprotein contains a fusion peptide (FP) segment that mediates the fusion of the viral and host cell membranes. Calcium ions are thought to position the FP optimally for membrane insertion by interacting with negatively …

[HTML] Interaction of human dendritic cell receptor DEC205/CD205 with keratins

Abstract DEC205 (CD205) is one of the major endocytic receptors on dendritic cells and has been widely used as a receptor target in immune therapies. It has been shown that DEC205 can recognize dead cells through keratins in a pH-dependent …

[PDF] A general platform for targeting MHC-II antigens via a single loop

Class-II major histocompatibility complexes (MHC-IIs) are central to the communications between CD4+ T cells and antigen presenting cells (APCs), but intrinsic structural features associated with MHC-II make it difficult to develop a …

[PDF] TIMED-Design: Flexible and Accessible Protein Sequence Design with Convolutional Neural Networks

Motivation Sequence design is a crucial step in the process of designing or engineering proteins. Traditionally, physics-based methods have been used to solve for optimal sequences, with the main disadvantages being that they are …

[PDF] MHC class I chain-related genes B shedding modulates pancreatic tumor immunity via the activation of NKG2DLow T cells

Natural killer group 2 member D ligands (NKG2DLs) are expressed as stress response proteins in cancer cells. NKG2DLs induce immune cell activation or tumor escape responses, depending on their expression. Human pancreatic cancer cells …

[PDF] Integrating Sequence and Graph Information for Enhanced Drug-Target Affinity Prediction

To address the limitations of both sequence-based and graph-based methods, we propose a method that leverages the strengths of both approaches while mitigating their shortcomings. Specifically, we utilize the sequence-based DTA prediction …

[PDF] In-silico Drug Repurposing pipeline for Epilepsy: Integrating Deep Learning and Structure-based Approaches

Epilepsy is a severe neurological disorder characterized by its chronic predisposition to recurrent epileptic seizures. Due to its considerable global prevalence and healthcare burden, the pursuit of effective new medication for epilepsy treatment …

[HTML] Structure-aware deep model for MHC-II peptide binding affinity prediction

The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an important branch in immune bioinformatics, especially helpful in accelerating the design of disease vaccines and immunity therapy. Although deep learning-based …

[PDF] ScRNA-Seq Reveals T Cell Immunity in COVID-19 Patients and Implications for Immunotherapy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused widespread transmission and been threatening health and lives due to high infectivity, acute progression and lacking of effective treatment. Both innate immunity and adaptive immunity are essential to defend against viral infection, while T cells function as a bridge of both arms and induce effective immune responses. Although traditional approaches demonstrate general features of T cells in COVID-19 patients …

[PDF] GeNLP: a web tool for NLP-based exploration and prediction of microbial gene function

GeNLP is a web application that enables exploring microbial gene “semantics” and predictions of uncharacterized gene families based on their genomic context. It utilizes a pre-trained language model to uncover gene relationships and allows …

[PDF] TransMEP: Transfer learning on large protein language models to predict mutation effects of proteins from a small known dataset

Machine learning-guided optimization has become a driving force for recent improvements in protein engineering. In addition, new protein language models are learning the grammar of evolutionarily occurring sequences at large scales. This …

[PDF] Late-stage reshaping of phage-displayed libraries to macrocyclic and bicyclic landscapes using multipurpose linchpin

Genetically-encoded libraries (GEL) are increasingly used for discovery of ligands for 'undruggable'targets that cannot be addressed with small molecules. However, there is currently no consensus whether 'zero knowledge'naïve libraries or libraries with …

[PDF] Cell-intrinsic PD-L1 ablation sustains effector CD8+ T cell responses and promotes antitumor T cell therapy

Adoptive cell therapies are emerging forms of immunotherapy that reprogram T cells for enhanced antitumor responses. Although surface programmed cell death-ligand 1 (PD-L1)/programmed cell death protein 1 (PD-1) engagement inhibits antitumor …

[HTML] CD57-positive CD8+ T cells define the response to anti-programmed cell death protein-1 immunotherapy in patients with advanced non-small cell lung cancer

Immune checkpoint inhibitors have transformed the treatment landscape of non-small cell lung cancer (NSCLC). However, accurately identifying patients who will benefit from immunotherapy remains a challenge. This study aimed to discover …

[HTML] Multiomics profiling reveals the benefits of gamma-delta (γδ) T lymphocytes for improving the tumor microenvironment, immunotherapy efficacy and prognosis in …

Background As an unconventional subpopulation of T lymphocytes, γδ T cells can recognize antigens independently of major histocompatibility complex restrictions. Recent studies have indicated that γδ T cells play contrasting roles in tumor …

[PDF] T antigen-specific CD8+ T cells associate with PD-1 blockade response in virus-positive Merkel cell carcinoma

Merkel cell carcinoma (MCC) is a highly immunogenic skin cancer primarily induced by Merkel Cell Polyomavirus, driven by the expression of the oncogenic T antigens (T-Ags). Blockade of the programmed cell death protein-1 (PD-1) pathway has …

Single-cell profiling reveals kidney CD163+ dendritic cell participation in human lupus nephritis

Objectives The current work aimed to provide a comprehensive single-cell landscape of lupus nephritis (LN) kidneys, including immune and non-immune cells, identify disease-associated cell populations and unravel their participation within the …

[PDF] Influence of ATLG Serum Levels on CD3/CD19-depleted Hematopoietic Grafts and on Immune Recovery in Pediatric Haplo-HSCT

Anti-T lymphocyte globulin (ATLG) significantly reduces the risk of engraftment failure in allogeneic hematopoietic stem cell transplantation (HSCT), but hampers post-transplant immune reconstitution. We hypothesized that in patients receiving …

DeepGum: Deep feature transfer for gut microbiome analysis using bottleneck models

The intricate relationship between gut microbiome composition and gastrointestinal diseases has been a focal point of numerous scientific investigations. In terms of sample points, the gut metagenome data has typically been produced in the orders of tens, hundreds or mostly in thousands per cohort. As there are practical and technical limitations resulting in this process, the small sample size-large dimension problem brings along hypothesis testing difficulties. To overcome these issues, by …

Machine Learning in RNA Structure Prediction: Advances and Challenges

RNA molecules play a crucial role in various biological processes, with their functionality closely tied to their structures. The remarkable advancements in machine learning techniques for protein structure prediction have shown promise in the field of RNA structure prediction. In this perspective, we discuss the advances and challenges encountered in constructing machine learning-based models for RNA structure prediction. We explore topics including model building strategies …

[PDF] Using large scale transfer learning to highlight the role of chromatin state in intron retention

Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self …

[PDF] NEAR: Neural Embeddings for Amino acid Relationships

We present NEAR, a method based on representation learning that is designed to rapidly identify good sequence alignment candidates from a large protein database. NEAR's neural embedding model computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of k-NN search, filtration, and neighbor aggregation. NEAR's ResNet embedding model is trained using an N-pairs loss function guided by sequence …

Toolkit for mapping the clonal landscape of tumor-infiltrating B cells

Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor-in distinct cancers, subcohorts and individual patients-is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor …

[PDF] Harnessing AlphaFold to reveal state secrets: Prediction of hERG closed and inactivated states

To design safe, selective, and effective new therapies, there must be a deep understanding of the structure and function of the drug target. One of the most difficult problems to solve has been resolution of discrete conformational states of transmembrane ion channel proteins. An example is KV11. 1 (hERG), comprising the primary cardiac repolarizing current, IKr. hERG is a notorious drug anti-target against which all promising drugs are screened to determine potential for arrhythmia. Drug …

Nudix hydrolase 23 post-translationally regulates carotenoid biosynthesis in plants

Carotenoids are essential for photosynthesis and photoprotection. Plants have evolved multifaceted regulatory mechanisms to control carotenoid biosynthesis. However, the regulatory mechanisms and the regulators conserved among plant species remain elusive. Phytoene synthase (PSY) catalyzes the highly regulated step of carotenogenesis and geranylgeranyl diphosphate synthase (GGPPS) acts as a hub to interact with GGPP-utilizing enzymes for the synthesis of specific …

[PDF] Virtual Screening of Synthetic Proteins Based on ESM2 Model

The virtual screening of synthetic proteins is to develop an effective method to predict and screen out synthetic proteins that are similar to the target sequences in terms of their structural and physicochemical properties by combining advanced computational tools and models, such as AlphaFold2 and ESM2. Through virtual screening, the experimental cost and time period can be reduced, and some guidelines for customized design of new proteins can be provided. All similar …

Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures

With the increasing resistance of bacterial pathogens to conventional antibiotics, antivirulence strategies targeting virulence factors (VFs) have become an effective new therapy for the treatment of pathogenic bacterial infections. Therefore, the identification and prediction of VFs can provide ideal candidate targets for the implementation of antivirulence strategies in treating infections caused by pathogenic bacteria. Currently, the existing computational models predominantly rely …

[PDF] Rapid proteome-wide prediction of lipid-interacting proteins through ligand-guided structural genomics

Lipids are primary metabolites that play essential roles in multiple cellular pathways. Alterations in lipid metabolism and transport are associated with infectious diseases and cancers. As such, proteins involved in lipid synthesis, trafficking, and modification, are targets for therapeutic intervention. The ability to rapidly detect these proteins can accelerate their biochemical and structural characterization. However, it remains challenging to identify lipid binding motifs in proteins due to a …

[PDF] Predicting TCR sequences for unseen antigen epitopes using structural and sequence features

T-cell receptor (TCR) recognition of antigens is fundamental to the adaptive immune response. With the expansion of experimental techniques, a substantial database of matched TCR-antigen pairs has emerged, presenting opportunities for computational prediction models. However, the accurate forecasting of binding affinities for unseen antigen-TCR pairs remains a major challenge. Here, we present Convolutional-Self-Attention TCR (CATCR), a novel framework tailored to enhance the prediction of …

[HTML] Regulatory T cells in spondyloarthropathies: genetic evidence, functional role, and therapeutic possibilities

Regulatory T cells (Tregs) are a very specialized subset of T lymphocytes: their main function is controlling immune responses during inflammation. T-regs involvement in autoimmune and immune-mediated rheumatic diseases is well-described. Here, we critically review the up-to-date literature findings on the role of Tregs in spondyloarthropathies, particularly in ankylosing spondylitis (AS), a polygenic inflammatory rheumatic disease that preferentially affects the spine and the sacroiliac …

Bayesian multiple instance classification based on hierarchical probit regression

MICProB_Supp. pdf: tables, figures, and Bayesian full conditionals mentioned in the paper. In the first section of this Supplementary Material, we provide additional figures for simulation results. In the second section of this Supplementary Material, we provide the full posterior conditionals for the Gibbs sampler with marginally noninformative priors for covariance matrices and corresponding results on the TCGA data. The remaining section of this Supplementary Material provides …

[HTML] Profiling of T cell repertoire in peripheral blood of patients from type 2 diabetes with complication

More than 90% of patients with diabetes worldwide are type 2 diabetes (T2D), which is caused by insulin resistance or impaired producing insulin by pancreatic β cells. T2D and its complications, mainly large cardiovascular (LCV) and kidney (Ne) …

[PDF] Beyond FOXP3: a 20-year journey unravelling human regulatory T-cell heterogeneity

FOXP3+ regulatory T-cells (Tregs) represent 4-7% of the CD4+ T-cell population and are essential for regulating peripheral tolerance and immune homeostasis. Early phase clinical trials have demonstrated proof-of-principle for the use of isolated and expanded polyclonal Tregs in the treatment of inflammatory disorders, transplant rejection and autoimmune diseases. Treg research traces its origins back more than 40 years. The first evidence for thymus-derived cells with suppressive function came …

Methods for compression of molecular tagged nucleic acid sequence data

A method for compressing molecular tagged sequence data includes: grouping sequence reads associated with a molecular tag sequence to form a family of sequence reads, corresponding vectors of flow space signal measurements and corresponding sequence alignments, calculating an arithmetic mean of the corresponding vectors of flow space signal measurements to form a vector of consensus flow space signal measurements, calculating a standard deviation of the …

[PDF] N-glycosylation as a Modulator of Protein Conformation and Assembly in Disease

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact …

Protein language models learn evolutionary statistics of interacting sequence motifs

Protein language models (pLMs) have emerged as potent tools for predicting and designing protein structure and function, and the degree to which these models fundamentally understand the inherent biophysics of protein structure stands as an …

SARS-CoV-2 spike-reactive naïve B cells and preexisting memory B cells cocontribute to antibody responses in unexposed individuals after vaccination

Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine …

[PDF] DeepGOMeta: Predicting functions for microbes

Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples …

[PDF] Optimizing sequence design strategies for perturbation MPRAs: a computational evaluation framework

The advent of perturbation-based massively parallel reporter assays (MPRAs) technique has facilitated the delineation of the roles of non-coding regulatory elements in orchestrating gene expression. However, computational efforts remain …

[HTML] Identification of a spike-specific CD8+ T cell epitope following vaccination against the Middle East respiratory syndrome coronavirus in humans

Licensed vaccines against the Middle East respiratory syndrome coronavirus (MERS-CoV), an emerging pathogen of concern, are lacking. The Modified Vaccinia virus Ankara vector-based vaccine MVA-MERS-S, expressing the MERS-CoV-spike …

An In silico Study on B-cell Epitope Mapping of Acinetobacter baumannii Outer Membrane Protein K

Background Acinetobacter baumannii is one of the main causes of nosocomial infections. No vaccine has yet been licensed for use in humans, and efforts are still ongoing. Objective In the present study, we have predicted the B-cell epitopes of A …

Internal Fragments Enhance Middle-Down Mass Spectrometry Structural Characterization of Monoclonal Antibodies and Antibody-Drug Conjugates

Monoclonal antibodies (mAbs) and antibody-drug conjugates (ADCs) are important large biotherapeutics (∼ 150 kDa) and high structural complexity that require extensive sequence and structure characterization. Middle-down mass spectrometry …

The self-reactive FVIII T cell repertoire in healthy individuals relies on a short set of epitopes and public clonotypes

Non-mutated FVIII-specific CD4 T cell epitopes have been recently found to contribute to the development of inhibitors in patients with hemophilia A (HA), while auto-reactive CD4 T cells specific to FVIII circulate in the blood of healthy individuals …

[HTML] Antibody discovery identifies regulatory mechanisms of protein arginine deiminase 4

Unlocking the potential of protein arginine deiminase 4 (PAD4) as a drug target for rheumatoid arthritis requires a deeper understanding of its regulation. In this study, we use unbiased antibody selections to identify functional antibodies capable of …

Response to tumor-infiltrating lymphocyte adoptive therapy is associated with preexisting CD8+ T-myeloid cell networks in melanoma

Adoptive cell therapy (ACT) using ex vivo–expanded tumor-infiltrating lymphocytes (TILs) can eliminate or shrink metastatic melanoma, but its long-term efficacy remains limited to a fraction of patients. Using longitudinal samples from 13 patients with …

[PDF] Towards Equitable MHC Binding Predictions: Computational Strategies to Assess and Reduce Data Bias

Deep learning tools that predict peptide binding by major histocompatibility complex (MHC) proteins play an essential role in developing personalized cancer immunotherapies and vaccines. In order to ensure equitable health outcomes from …

Self-Assembling Protein Nanostructures

Self-Assembling Protein Nanostructures - UNIVERSITY OF WASHINGTON THROUGH ITS CENTER FOR COMMERCIALIZATION Login Sign up US Patents/Apps Other SEARCH TOOLS & RESOURCES Title: Self-Assembling Protein Nanostructures …

[HTML] Identification of Campylobacter jejuni and Campylobacter coli genes contributing to oxidative stress response using TraDIS analysis

Abstract Background Campylobacter jejuni and Campylobacter coli are the major causative agents of bacterial gastroenteritis worldwide and are known obligate microaerophiles. Despite being sensitive to oxygen and its reduction products, both …

Isolation of antigen-specific B cells in ANCA-associated vasculitis; successes and challenges

Background: A limitation of traditional fluorescence microscopy is the number of antigens that may be studied simultaneously–typically no more than three per section. The 'Hyperion'imaging mass cytometry (IMC) system overcomes this …

[HTML] People who use drugs show no increase in pre-existing T-cell cross-reactivity toward SARS-CoV-2 but develop a normal polyfunctional T-cell response after standard …

People who use drugs (PWUD) are at a high risk of contracting and developing severe coronavirus disease 2019 (COVID-19) and other infectious diseases due to their lifestyle, comorbidities, and the detrimental effects of opioids on cellular immunity. However, there is limited research on vaccine responses in PWUD, particularly regarding the role that T cells play in the immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we show that before …

Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances

Synthetic antibodies (Abs) represent a category of engineered proteins meticulously crafted to replicate the functions of their natural counterparts. Such Abs are generated in vitro, enabling advanced molecular alterations associated with antigen recognition, paratope site engineering, and biochemical refinements. In a parallel realm, deep sequencing has brought about a paradigm shift in molecular biology. It facilitates the prompt and cost-effective high-throughput sequencing of DNA and …

Lupus-associated innate receptors drive extrafollicular evolution of autoreactive B cells

In systemic lupus erythematosus, recent findings highlight the extrafollicular (EF) pathway as prominent origin of autoantibody-secreting cells (ASCs). CD21 lo CD11c+ B cells, associated with aging, infection, and autoimmunity, are contributors to autoreactive EF ASCs but have an obscure developmental trajectory. To study EF kinetics of autoreactive B cell in tissue, we adoptively transferred WT and gene knockout B cell populations into the 564Igi mice-an autoreactive host enriched with …

[HTML] 深度突变扫描技术在蛋白研究中的应用

作为细胞结构与功能的中心参与者, 蛋白质一直是生命科学研究的中心主题. 分析蛋白质序列变异对其结构, 功能的影响, 是研究蛋白的重要手段之一. 近年一种称为深度突变扫描(deep mutational scanning, DMS) 的技术被广泛应用于蛋白研究领域, 其通过高丰度DNA 文库在蛋白特定区域平行引入成千上万种突变, 经筛选后, 利用高通量测序为每一种突变打分, 从而揭示序列与功能之间的相关性. 深度突变扫描以其高通量, 快速简易, 节省人工等特点, 已经成为蛋白质功能研究以及 …

[HTML] AnnoPRO: a strategy for protein function annotation based on multi-scale protein representation and a hybrid deep learning of dual-path encoding

Protein function annotation has been one of the longstanding issues in biological sciences, and various computational methods have been developed. However, the existing methods suffer from a serious long-tail problem, with a large number of GO families containing few annotated proteins. Herein, an innovative strategy named AnnoPRO was therefore constructed by enabling sequence-based multi-scale protein representation, dual-path protein encoding using pre-training, and function …

[PDF] Discovery and Characterization of Terpene Synthases Powered by Machine Learning

Terpene synthases (TPSs) generate the scaffolds of the largest class of natural products, including several first-line medicines. The amount of available protein sequences is increasing exponentially, but computational characterization of their …

[PDF] 基于多视图矩阵补全的蛋白受体功能预测

蛋白受体是细胞信号转导的重要组成部分, 也是人类最重要的药物靶点, 其中G 蛋白偶联受体(G Protein Coupled Receptors, GPCRs) 占绝大部分, 目前市场上大约34% 的药物都以GPCRs 作为靶点. 准确地注释GPCR 蛋白的生物学功能对于理解它们涉及的生理过程及靶向药物发现至关重要, 其中基因本体学(Gene Ontology, GO) 是描述蛋白质功能最常用的方式, GPCR 蛋白和GO 都包含多个视图信息, 有效利用这些信息可有效提升蛋白质功能的预测性能 …

Cytotoxic lymphocyte-monocyte complex reflects the dynamics of COVID-19 systemic immune response

SARS-CoV-2 infection causes a variety of clinical manifestations, many of which originate from altered immune responses, either locally or systemically. Immune cell crosstalk occurs mainly in lymphoid organs. However, systemic cell interaction specific to COVID-19 has not been well characterized. Here, by employing single cell RNA sequencing and imaging flow cytometry analysis, we unraveled, in peripheral blood, a heterogeneous group of cell complexes formed by the adherence of CD14+ …

[PDF] H3K27M neoepitope vaccination in diffuse midline glioma induces B and T cell responses across diverse HLA loci of a recovered patient

H3K27M, a driver mutation with T and B cell neoepitope characteristics, defines an aggressive subtype of diffuse glioma with poor survival. We functionally dissect the immune response of one patient treated with an H3K27M peptide vaccine who …

Granzyme K+ CD8 T cells in autoimmunity

CD8 T cells expressing granzyme K are enriched in synovial tissue from patients with rheumatoid arthritis and in tissues affected by several other autoimmune diseases. The roles these cells play in autoimmune disease is under active investigation, and several recent studies have begun to shed light on this question. Putting this cell type into functional perspective is especially important given their enrichment at the sites of disease. This review summarizes available evidence for the presence of CD8 T …

[HTML] T-Cell Receptor Sequences Identify Combined Coxsackievirus–Streptococci Infections as Triggers for Autoimmune Myocarditis and Coxsackievirus–Clostridia …

Recent research suggests that T-cell receptor (TCR) sequences expanded during human immunodeficiency virus and SARS-CoV-2 infections unexpectedly mimic these viruses. The hypothesis tested here is that TCR sequences expanded in …

SARS‐CoV‐2‐associated T‐cell infiltration in the central nervous system

Objectives Infection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes coronavirus disease 2019 (COVID‐19). Although an acute SARS‐CoV‐2 infection mainly presents with respiratory illness, neurologic symptoms and sequelae are increasingly recognised in the long‐term treatment of COVID‐19 patients. The pathophysiology and the neuropathogenesis behind neurologic complications of COVID‐19 remain poorly understood, but mounting evidence points …

[PDF] Analysis of tumor-related features of non-small cell lung cancer based on TCR repertoire workflow

Objective· To explore the immune-related characteristics of non-small cell lung cancer (NSCLC), discover potential tumor markers in VJ genes, and lay the foundation for establishing a TCR-antigen recognition prediction model. Methods· A total of 704 NSCLC samples were collected to establish a comprehensive T-cell receptor (TCR) repertoire analysis workflow. The upstream analysis included steps such as raw data processing, quality control, filtering, TCR sequence identification …

[PDF] 基于 TCR 组库分析流程的非小细胞肺癌特征分析

目的· 探究非小细胞肺癌(non-small cell lung cancer, NSCLC) 免疫相关特征, 发掘VJ 基因中的肿瘤潜在标志物, 为建立T 细胞受体(T-cell receptor, TCR)-抗原识别预测模型提供基础. 方法· 收集704 例NSCLC 样本, 用于构建一套系统的TCR 组库分析流程, 涵盖从原始数据到质控, 过滤, TCR 序列的识别和提取等上游分析部分, 以及组库克隆分布, 克隆分型, VJ 基因共享性, 互补决定区3 (CDR3) 分布特征以及克隆追踪等下游分析流程. 使用Shannon-Weiner 指数, Chao1 等指数分析样本克隆分布 …

[PDF] Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review …

Background: Artificial Intelligence (AI) is an area of computer science/engineering that is aiming to spread technological systems. The COVID-19 pandemic caused economic and public health turbulence around the world. Among the many possibilities for using AI in the medical field is FreeStyle Libre®(FSL), which uses a disposable sensor inserted into the user's arm, and a touchscreen device/reader is used to scan and retrieve other continuous monitoring of glucose (CMG) readings …

Research on Performance Evaluation of Production-Marketing Integrated Supply Chain Based on Neural Network

Neural networks have demonstrated strong forecasting and pattern recognition capabilities in many fields, and supply chain performance evaluation has always been a key issue in enterprise management, especially in the modern complex business environment, the effective management of production-marketing integrated supply chain has become particularly important. The purpose of this study is to explore how to use neural network methods to evaluate the performance of …

[PDF] Lived Experiences of Students and Teachers in Virtual Mentorship in Undergraduate Research: A Transcendental Phenomenological Study

This transcendental phenomenological study aimed to uncover the students' and teachers' lived experiences in virtual mentorship in undergraduate research. Ten participants were interviewed: Five (5) students and five (5) teachers. Using Colaizzi's strategy, in terms of lived experiences, the positive lived experiences of the students involved efficient feedback system, the use of varied materials, enhancement of self-efficacy among mentees, and enhanced class participation …

[PDF] Review on therapeutic potential of peptides: Advancements in synthesis methods, linear and cyclic peptides, and strategies for overcoming challenges

In the realm of therapeutic peptides, tremendous progress has been achieved in the last two decades. The building block of peptides that is,'Amino Acid'has been modified by various chemical modifications such as side‐chain alteration in linear peptides, cyclization, back‐bone modification, pro‐drug moiety, conjugation with heterocycles, and natural products to make peptides a foremost candidate as a therapeutic drug. Since the advent of insulin in 1922, peptides have immensely …

[HTML] Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein–protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the …

[PDF] Conformational plasticity of a BiP-GRP94 chaperone complex

Hsp70/Hsp90-chaperones and their regulatory co-chaperones are critical for maintaining protein homeostasis. GRP94, the sole Hsp90-chaperone in the secretory pathway of mammalian cells, is essential for the maturation of important secretory and transmembrane proteins. Without the requirement of co-chaperones, the Hsp70-protein BiP controls regulatory conformational changes of GRP94–the structural basis of which has remained elusive. Here, we biochemically and structurally …

[PDF] HDX-MS, Molecular Dynamics, and Modeling: An Integrative Approach to Model Solution Structural Ensembles

Probing the structural equilibrium that proteins and protein complexes can adopt in solution is critical in understanding a multitude their biophysical properties. Two common ways to probe these dynamic structures are hydrogen deuterium exchange coupled mass spectrometry (HDX-MS) and molecular dynamics simulations (MD). HDX-MS is a solution-based technique that reports on a system's secondary and tertiary structure and dynamics at peptide level resolution. Although informative, the …

[HTML] Multi-epitope vaccine design against leishmaniasis using IFN-γ inducing epitopes from immunodominant gp46 and g63 proteins

There is no currently approved human vaccine against leishmaniasis. Utilization of immunogenic antigens and their epitopes capable of enhancing immune responses against leishmaniasis is a crucial step for rational in silico vaccine design. The …

[HTML] Polytopic fractional delivery of an HIV vaccine alters cellular responses and results in increased epitope breadth in a phase 1 randomized trial

Background Elicitation of broad immune responses is understood to be required for an efficacious preventative HIV vaccine. This Phase 1 randomized controlled trial evaluated whether administration of vaccine antigens separated at multiple injection …

[HTML] Virus-like particle vaccine displaying an external, membrane adjacent MUC16 epitope elicits ovarian cancer-reactive antibodies

Background MUC16 is a heavily glycosylated cell surface mucin cleaved in the tumor microenvironment to shed CA125. CA125 is a serum biomarker expressed by> 95% of non-mucinous advanced stage epithelial ovarian cancers. MUC16/CA125 …

[HTML] Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time …

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) …

[HTML] Structure-based prediction of protein-protein interaction network in rice

Comprehensive protein-protein interaction (PPI) maps are critical for understanding the functional organization of the proteome, but challenging to produce experimentally. Here, we developed a computational method for predicting PPIs …

[PDF] Crocin attenuates the lipopolysaccharide-induced neuroinflammation via expression of AIM2 and NLRP1 inflammasome in an experimental model of Parkinson's …

The underlying mechanisms of inflammasome activation and the following dopaminergic neuron loss caused by chronic neuroinflammation remain entirely unclear. Therefore, this study aimed to investigate the impact of crocin on the …

[PDF] Adoptive transfer of T lymphocytes retrovirally transduced to express personalized neoantigen reactive T cell receptors can mediate tumor regression in patients with …

Adoptive cell transfer (ACT) using neoantigen reactive T lymphocytes can mediate cancer regression. Here, we developed methods to isolate unique, personalized, neoantigen reactive T cell receptors (TCRs) from tumor infiltrating lymphocytes (TIL) …

MucLiPred: Multi-Level Contrastive Learning for Predicting Nucleic Acid Binding Residues of Proteins

Protein–molecule interactions play a crucial role in various biological functions, with their accurate prediction being pivotal for drug discovery and design processes. Traditional methods for predicting protein–molecule interactions are limited. Some …

Empowering Protein Engineering Through Recombination of Beneficial Substitutions

Directed evolution stands as a seminal technology for generating novel protein functionalities, a cornerstone in biocatalysis, metabolic engineering, and synthetic biology. Today, with the development of various mutagenesis methods and advanced analytical machines, the challenge of diversity generation and high‐throughput screening platforms is largely solved, and one of the remaining challenges is: how to empower the potential of single beneficial substitutions with …

[PDF] Protein language models learn evolutionary statistics of interacting sequence motifs

Protein language models (pLMs) have emerged as potent tools for predicting and designing protein structure and function, and the degree to which these models fundamentally understand the inherent biophysics of protein structure stands as an …

[PDF] Aggregating Residue-Level Protein Language Model Embeddings with Optimal Transport

Protein language models (PLMs) have emerged as powerful approaches for mapping protein sequences into informative embeddings suitable for a range of applications. PLMs, as well as many other protein representation schemes, generate …

[HTML] GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference

The recent advances of single-cell RNA sequencing (scRNA-seq) have enabled reliable profiling of gene expression at the single-cell level, providing opportunities for accurate inference of gene regulatory networks (GRNs) on scRNA-seq data. Most …

[HTML] Foldy: An open-source web application for interactive protein structure analysis

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities …

[PDF] Sequence, Structure and Functional space of Drosophila de novo proteins

During de novo emergence, new protein coding genes emerge from previously non-genic sequences. The de novo proteins they encode are dissimilar in composition and predicted biochemical properties to conserved proteins. However, many …

Hit-and-run vaccine system that overcomes limited neoantigen epitopes for efficient broad antitumor response

Neoantigen cancer vaccines have been envisioned as one of the most promising means for cancer therapies. However, identifying neoantigens for tumor types with low tumor mutation burdens continues to limit the effectiveness of neoantigen …

[HTML] Targeted demethylation and activation of NLRC5 augment cancer immunogenicity through MHC class I

Impaired expression of MHC (major histocompatibility complex) class I in cancers constitutes a major mechanism of immune evasion. It has been well documented that the low level of MHC class I is associated with poor prognosis and resistance to …

[HTML] Manufacture of CD22 CAR T cells following positive versus negative selection results in distinct cytokine secretion profiles and γδ T cell output

Chimeric antigen receptor T cells (CART) have demonstrated curative potential for hematological malignancies, but the optimal manufacturing has not yet been determined and may differ across products. The first step, T cell selection, removes …

[PDF] A unique human cord blood CD8+ CD45RA+ CD27+ CD161+ T cell subset identified by flow cytometric data analysis using Seurat

Advances in single-cell level analytical techniques, especially cytometric approaches, have led to profound innovation in biomedical research, particularly in the field of clinical immunology. This has resulted in an expansion of high …

Large scale transcriptional analysis of MHC class I haplotype diversity in sheep.

Domestic sheep (Ovis aries) have been an important component of livestock agricultural production for thousands of years. Preserving genetic diversity within livestock populations maintains a capacity to respond to changing environments and …

[HTML] Structure prediction of linear and cyclic peptides using CABS-flex

The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The …

[HTML] A Detailed Protocol for Constructing a Human Single-Chain Variable Fragment (scFv) Library and Downstream Screening via Phage Display

The development of monoclonal antibodies (mAbs) represents a significant milestone in both basic research and clinical applications due to their target specificity and versatility in therapeutic and diagnostic applications. The innovative …

Characterization of galactosyltransferase and sialyltransferase genes mediating the elongation of the extracellular O-GlcNAc glycans

O-GlcNAc is a unique post-translational modification found in cytoplasmic, nuclear, and mitochondrial proteins. In a limited number of extracellular proteins, O-GlcNAc modifications occur through the action of EOGT, which specifically modifies subsets …

RNA3DB: a dataset for training and benchmarking deep learning models for RNA structure prediction

With advances in protein structure prediction thanks to deep learning models like AlphaFold, RNA structure prediction has recently received increased attention from deep learning researchers. RNAs introduce substantial challenges due to the …

[PDF] Binding Affinity Prediction with 3D Machine Learning: Training Data and Challenging External Testing

Protein-ligand binding affinity prediction is one of the major challenges in computational assisted drug discovery. An active area of research uses machine learning (ML) models trained on 3D structures of protein ligand complexes to predict …

[PDF] Unsupervised Learnings of Protein Large Language Models for Make Benefit Glorious Sector of Biotech

Protein language models were nurtured by unlikely parents---corporations. Now that they have come of age, they have been forced to strike out on their own. A common pitfall that biotechnology platforms make is to attempt to solve as many problems, all …

[PDF] De novo protein design—From new structures to programmable functions

Methods from artificial intelligence (AI) trained on large datasets of sequences and structures can now" write" proteins with new shapes and molecular functions de novo, without starting from proteins found in nature. In this Perspective, I will discuss …

Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Recently, ChatGPT, a representative large language model (LLM), has gained considerable attention. Due to their powerful emergent abilities, recent LLMs are considered as a possible alternative to structured knowledge bases like knowledge …

Protein language models meet reduced amino acid alphabets

Abstract Motivation Protein Language Models (PLMs), which borrowed ideas for modelling and inference from Natural Language Processing, have demonstrated the ability to extract meaningful representations in an unsupervised way. This led to …

[HTML] Leveraging Biases in Large Language Models:" bias-kNN''for Effective Few-Shot Learning

Large Language Models (LLMs) have shown significant promise in various applications, including zero-shot and few-shot learning. However, their performance can be hampered by inherent biases. Instead of traditionally sought methods that aim …

[HTML] Human Nasal Epithelium Organoids for Assessing Neutralizing Antibodies to a Protective SARS-CoV-2 Virus-like Particle Vaccine

Existing mRNA COVID-19 vaccines have shown efficacy in reducing severe cases and fatalities. However, their effectiveness against infection caused by emerging SARS-CoV-2 variants has waned considerably, necessitating the development of …

[PDF] Targeting PD-L1 in solid cancer with myeloid cells expressing a CAR-like immune receptor

Myeloid cells are prevalent in solid cancers, but they frequently exhibit a pro-tumor phenotype, hindering cancer immunotherapy. Their abundance makes engineered myeloid cell therapy an intriguing approach to tackle challenges posed by solid …

Additional Reassuring Data for SARS-CoV-2 Vaccination in Immune-Mediated Inflammatory Diseases, but With a Catch

Vaccination remains the most important intervention to attenuate the risk and severity of infectious diseases in those immunosuppressed for the treatment of rheumatic conditions and is indeed true for coronavirus disease 2019 (COVID-19). Substantial …

[PDF] Recapitulating memory B cell responses in a Lymphoid Organ-Chip to evaluate mRNA vaccine boosting strategies

Predicting the immunogenicity of candidate vaccines in humans remains a challenge. To address this issue, we developed a Lymphoid Organ-Chip (LO chip) model based on a microfluidic chip seeded with human PBMC at high density within …

[HTML] A Novel Single-Tube Next Generation Sequencing Assay for B-Cell Receptor Clonality Testing

B-cell neoplasms possess clonal B-cell receptor rearrangements (BCR clonotype lineages) that can be identified by sequencing the B-cell repertoire for use in diagnostics, risk stratification, and high-sensitivity monitoring. BCR somatic …

Structural basis and analysis of hamster ACE2 binding to different SARS-CoV-2 spike RBDs

Pet golden hamsters were first identified being infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant of concern (VOC) and transmitted the virus back to humans in Hong Kong in January 2022. Here, we …

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction …

[PDF] The T-cell niche tunes immune function through modulation of the cytoskeleton and TCR-antigen forces

Obesity is a major public health crisis given its rampant growth and association with an increased risk for cancer. Interestingly, patients with obesity tend to have an increased tumor burden and decreased T-cell function. It remains unclear how …

Petabase-Scale Homology Search for Structure Prediction

The recent CASP15 competition highlighted the critical role of multiple sequence alignments (MSAs) in protein structure prediction, as demonstrated by the success of the top AlphaFold2-based prediction methods. To push the boundaries of MSA …

Relationship between B-Cell Populations, Development and Function of B-Cell Subsets

The intricate interplay among B-cell populations maintains human health. The study of B cells at the granular level has confirmed the definition of different B-cell populations with distinct functions, based on phenotype, gene expression, variable heavy chain (VH) usage and antigen specificity. All the other populations of B cells detected in the peripheral blood are generated by immunological experience. The B-cell compartment is fluid and in continuous evolution. Transitional and mature-naive …

Evolution of genome and immunogenome in esophageal squamous cell carcinomas driven by neoadjuvant chemoradiotherapy

Background Neoadjuvant chemoradiotherapy (NCRT) followed by surgery is a standard treatment for locally advanced esophageal squamous cell carcinomas (ESCCs). However, evolution of genome and immunogenome in ESCCs driven by NCRT remain incompletely elucidated. Methods We performed whole-exome sequencing of 51 ESCC tumors collected before and after NCRT, 36 of which were subjected to transcriptome sequencing. Results Clonal analysis identified clonal …

[PDF] Voronota-LT: efficient, flexible and solvent-aware tessellation-based analysis of atomic interactions

Motivation: In the fields of structural biology and bioinformatics, understanding molecular interactions is paramount. However, existing advanced geometric methods for describing interatomic contacts considering full structural context have typically demanded substantial computational resources, hindering their practical application. Given the ever-growing volume of structural data, there is an urgent need for more efficient tools for interaction analysis. Results: We present Voronota …

[PDF] Fine-tuning of Conditional Transformers Improves the Generation of Functionally Characterized Proteins

Conditional transformers improve the generative capabilities of large language models (LLMs) by processing specific control tags able to drive the generation of texts characterized by specific features. Recently, a similar approach has been applied to the generation of functionally characterized proteins by adding specific tags to the protein sequence to qualify their functions (eg, Gene Ontology terms) or other characteristics (eg, their family or the species which they belong to). In this …

[HTML] Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency─ or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application …

The Structure of the Hfq Protein from Chromobacterium haemolyticum Revealed a New Variant of Regulation of RNA Binding with the Protein

The structure of the Hfq protein from the bacterium Chromobacterium haemolyticum, which forms crystals in two different spatial groups, has been determined. In both cases, the protein has a specific quaternary hexamer-ring structure. The obtained structure showed a previously undescribed interaction between the C-terminal unstructured part of Hfq and the amino acid residues of the proximal RNA-binding site of the protein. This contact may contribute to the regulation of the binding of RNA …

[PDF] Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning

Accurately modeling the protein fitness landscapes holds great importance for protein engineering. Recently, due to their capacity and representation ability, pre-trained protein language models have achieved state-of-the-art performance in …

Design of human ACE2 mimic miniprotein binders that interact with RBD of SARS-CoV-2 variants of concerns

The world of medicine demands from the research community solutions to the emerging problem of SARS-CoV-2 variants and other such potential global pandemics. With advantages of specificity over small molecule drugs and designability over antibodies, miniprotein therapeutics offers a unique solution to the threats of rapidly emerging SARS-CoV-2 variants. Unfortunately, most of the promising miniprotein binders are de novo designed and it is not viable to generate …

[HTML] Somatic Mutations within Myocilin due to Aging May Be a Potential Risk Factor for Glaucoma

Glaucoma is a chronic optic neuropathy that leads to irreversible vision loss. Aging and family history are the two most important risk factors of glaucoma. One of the most studied genes involved in the onset of open-angle glaucoma is myocilin (MYOC). About 105 germline mutations within MYOC are known to be associated with glaucoma and result in endoplasmic reticulum (ER) stress, which leads to trabecular meshwork (TM) cell death and subsequent intraocular pressure (IOP) …

[PDF] Activation loop phosphorylation and cGMP saturation of PKG regulate egress of malaria parasites.

The cGMP-dependent protein kinase (PKG) is the sole cGMP sensor in malaria parasites, acting as an essential signalling hub to govern key developmental processes throughout the parasite life cycle. Despite the importance of PKG in the …

[HTML] Beyond Lengthscales: No-regret Bayesian Optimisation With Unknown Hyperparameters Of Any Type

Bayesian optimisation requires fitting a Gaussian process model, which in turn requires specifying hyperparameters-most of the theoretical literature assumes those hyperparameters are known. The commonly used maximum likelihood estimator for hyperparameters of the Gaussian process is consistent only if the data fills the space uniformly, which does not have to be the case in Bayesian optimisation. Since no guarantees exist regarding the correctness of hyperparameter estimation, and those …

Mucosal Immunity to Bacteria and Immunoglobulin A Synthesis

Mucosal immunity requires a fine balance to maintain a mutualistic relationship between the host and its complex commensal communities and to respond and clear infection at mucosal sites. Antibodies of the immunoglobulin A (IgA) isotype are pivotal to maintain gut homoeostasis. IgA production in mammals exceeds those of all other isotypes and is secreted across mucosal epithelium where it interacts with our microbiota or pathogens. Here we discuss the mechanisms underlying selective …

Memory B Cells and Plasma Cells

Immunological memory provided by memory B cells, memory T cells and long-lived (memory) plasma cells yields long-lasting, effective cellular and humoral immune protection to previously encountered pathogens and vaccines. Memory B cells provide a fast and potent anamnestic antibody response following a reencounter with antigen, thereby providing an extra arm of immunity to pathogens that are not cleared by pre-existing antibodies. In addition, they qualify as potent antigen-presenting and …

[PDF] Protein language models meet reduced amino acid alphabets

Abstract Motivation Protein Language Models (PLMs), which borrowed ideas for modelling and inference from Natural Language Processing, have demonstrated the ability to extract meaningful representations in an unsupervised way. This led to …

[PDF] PackDock: a Diffusion Based Side Chain Packing Model for Flexible Protein-Ligand Docking

Structure-based drug design (SBDD) relies on accurate knowledge of protein structure and ligand-binding conformations. However, most of the static conformations obtained by advanced methods such as structural biology and de …

[HTML] Antibody complementarity-determining region design using AlphaFold2 and DDG predictor

The constraints imposed by natural antibody affinity maturation often culminate in antibodies with suboptimal binding affinities, thereby limiting their therapeutic efficacy. As such, the augmentation of antibody binding affinity is pivotal for the …

[PDF] The Main Protease of Middle East Respiratory Syndrome Coronavirus Induces Cleavage of Mitochondrial Antiviral Signaling Protein to Antagonize the Innate Immune …

Mitochondrial antiviral signaling protein (MAVS) is a crucial signaling adaptor in the sensing of positive-sense RNA viruses and the subsequent induction of the innate immune response. Coronaviruses have evolved multiple mechanisms to evade this …

[HTML] A monoclonal antibody targeting a large surface of the receptor binding motif shows pan-neutralizing SARS-CoV-2 activity

Here we report the characterization of 17T2, a SARS-CoV-2 pan-neutralizing human monoclonal antibody isolated from a COVID-19 convalescent individual infected during the first pandemic wave. 17T2 is a class 1 VH1-58/κ3-20 antibody, derived …

PeptiVAX: A new adaptable peptides-delivery platform for development of CTL-based, SARS-CoV-2 vaccines

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a threat to public health and the global economy, necessitating the development of various vaccination strategies. Mutations in the SPIKE protein gene …

[HTML] Novel neutralizing SARS-CoV-2-specific mAbs offer detection of RBD linear epitopes

To stop the spread of the COVID-19 disease, it is crucial to create molecular tools to investigate and diagnose COVID-19. Current efforts focus on developing specific neutralizing monoclonal antibodies (NmAbs) elicited against the receptor-binding …

[PDF] SARS‐CoV‐2‐associated T‐cell infiltration in the central nervous system

Objectives Infection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes coronavirus disease 2019 (COVID‐19). Although an acute SARS‐CoV‐2 infection mainly presents with respiratory illness, neurologic symptoms and …

[HTML] Incongruity between T cell receptor recognition of breast cancer hotspot mutations ESR1 Y537S and D538G following exogenous peptide loading versus endogenous …

ABSTRACT T cell receptor engineered T cell (TCR T) therapies have shown recent efficacy against certain types of solid metastatic cancers. However, to extend TCR T therapies to treat more patients across additional cancer types, new TCRs …

[PDF] Determination of the clinical relevance of donor epitope‐specific HLA‐antibodies in kidney transplantation

In kidney transplantation, survival rates are still partly impaired due to the deleterious effects of donor specific HLA antibodies (DSA). However, not all luminex‐defined DSA appear to be clinically relevant. Further analysis of DSA recognizing …

[PDF] Large scale transcriptional analysis of MHC class I haplotype diversity in sheep

Domestic sheep (Ovis aries) have been an important component of livestock agricultural production for thousands of years. Preserving genetic diversity within livestock populations maintains a capacity to respond to changing environments and …

[PDF] Molecular sensitization and epitope prediction of cat allergens

Methods B epitopes were determined in silico using BepiPred-2.0 software and a combination of different methods N-align, SMM-align, CombLib N-align. SMM-align was used for predicting T epitopes in four allergens. Specific IgE levels to four …

[HTML] Immunoinformatics, molecular docking and dynamics simulation approaches unveil a multi epitope-based potent peptide vaccine candidate against avian leukosis …

Lymphoid leukosis is a poultry neoplastic disease caused by avian leukosis virus (ALV) and is characterized by high morbidity and variable mortality rates in chicks. Currently, no effective treatment and vaccination is the only means to control it. This …

[HTML] Increasing HbA1c is associated with reduced CD8+ T cell functionality in response to influenza virus in a TCR-dependent manner in individuals with diabetes mellitus

Diabetes mellitus is on the rise globally and is a known susceptibility factor for severe influenza virus infections. However, the mechanisms by which diabetes increases the severity of an influenza virus infection are yet to be fully defined. Diabetes …

Epitope-specific IgE, IgG4, and IgG1 antibodies for clinical phenotyping of IgE-mediated wheat allergy

Methods Children and adolescents (n= 109) enrolled in Bangkok and New York underwent Oral Food Challenges to diagnose wheat allergy. Seventy-nine peptides were synthesized from 5 proteins, including ω-5-g, alpha/beta-gliadin (a/bg), gamma …

[PDF] Dynamics of The Γδtcr Repertoires During The Dedifferentiation Process and Pilot Implications for Immunotherapy of Thyroid Cancer

Abstract γδ T cells are evolutionarily conserved T lymphocytes that manifest unique antitumor efficacy independent of tumor mutation burden (TMB) and conventional human leukocyte antigen (HLA) recognition. However, the dynamic changes in their …

[PDF] Relevance of Human IgE Monoclonal Antibodies within the IgE Repertoire to Dust Mite Allergen Der p 2

Methods hIgE mAb 2F10, 4C8, and 2G1 were isolated from hybridomas produced with B cells from allergic subjects. Antigen binding fragments (Fab) from 2F10 or 4C8 were mixed with recombinant Der-p-2.0103 for crystallography. The capacity of Der-p …

[PDF] Germinal center BCR maturation in appendicitis reveals a role for antigen-specific adaptive immune responses during disease

Appendicitis is one of the most common abdominal emergencies globally, yet little is understood about the inflammatory mechanisms or potential drivers of disease. Neutrophil inflammation and increased cytokine expression such as IL-6 and IL-8 are …

[PDF] In vivo affinity maturation of the HIV-1 Env-binding domain of CD4

Many human proteins have been repurposed as biologics for clinical use. These proteins have been engineered with in vitro techniques that improve affinity for their ligands. However, these approaches do not select against properties that impair …

[PDF] Prompting Large Language Models for Zero-Shot Clinical Prediction with Structured Longitudinal Electronic Health Record Data

The inherent complexity of structured longitudinal Electronic Health Records (EHR) data poses a significant challenge when integrated with Large Language Models (LLMs), which are traditionally tailored for natural language processing. Motivated by …

[PDF] Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes

Large language models (LLMs) have shown remarkable advances in language generation and understanding but are also prone to exhibiting harmful social biases. While recognition of these behaviors has generated an abundance of bias mitigation …

[PDF] Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities

Augmenting large language models (LLMs) to understand audio--including non-speech sounds and non-verbal speech--is critically important for diverse real-world applications of LLMs. In this paper, we propose Audio Flamingo, a novel audio …

[PDF] SPIRED-Fitness: an end-to-end framework for the prediction of protein structure and fitness from single sequence

Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and …

[PDF] A hypo-immunoreactive derivative lacking the dominant linear Scylla paramamosain allergen epitope

Background: Scylla paramamosain frequently elicits IgE-mediated type-I hypersensitivity reactions. Molecular candidates for crab allergen-specific immunotherapy (AIT) have not been studied previously. This study aimed to …

[HTML] Osteoclasts and Probiotics Mediate Significant Expansion, Functional Activation and Supercharging in NK, γδ T, and CD3+ T Cells: Use in Cancer Immunotherapy

Our previous studies have introduced osteoclasts (OCs) as major activators of NK cells. It was found that OCs exhibit the capabilities of inducing cell expansion as well as increasing the cytotoxic activity of NK cells by granule release and increasing the …

Immunometabolic adaptation of CD19-targeted CAR T cells in the central nervous system microenvironment of patients promotes memory development

Metabolic reprogramming is a hallmark of T cell activation, and metabolic fitness is fundamental for T cell-mediated anti-tumor immunity. Insights into the metabolic plasticity of chimeric antigen receptor (CAR) T cells in patients could help identify …

Landscape of T cell epitopes displays hot mutations of SARS-CoV-2 variant spikes evading cellular immunity

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been accompanied by the emergence of viral mutations that pose a great challenge to existing vaccine strategies. It is not fully understood with regard to the …

[HTML] A phase 1/2 clinical trial of invariant natural killer T cell therapy in moderate-severe acute respiratory distress syndrome

Invariant natural killer T (iNKT) cells, a unique T cell population, lend themselves for use as adoptive therapy due to diverse roles in orchestrating immune responses. Originally developed for use in cancer, agenT-797 is a donor-unrestricted allogeneic …

[HTML] Per-cell histone acetylation is associated with terminal differentiation in human T cells

Epigenetic remodeling at effector gene loci has been reported to be critical in regulating T cell differentiation and function. However, efforts to investigate underlying epigenetic mechanisms that control T cell behaviors have been largely …

[PDF] Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

Background Identification of Human leukocyte antigen (HLA) types from DNA-sequenced human samples is important in organ transplantation and cancer immunotherapy and remains a challenging task considering sequence homology …

[PDF] PhenoLinker: Phenotype-Gene Link Prediction and Explanation using Heterogeneous Graph Neural Networks

The association of a given human phenotype to a genetic variant remains a critical challenge for biology. We present a novel system called PhenoLinker capable of associating a score to a phenotype-gene relationship by using heterogeneous …

[HTML] A computational model of circRNA-associated diseases based on a graph neural network: prediction and case studies for follow-up experimental validation

Abstract Background Circular RNAs (circRNAs) have been confirmed to play a vital role in the occurrence and development of diseases. Exploring the relationship between circRNAs and diseases is of far-reaching significance for studying …

[PDF] Multi-level protein pre-training with Vabs-Net

In recent years, there has been a surge in the development of 3D structure-based pre-trained protein models, representing a significant advancement over pre-trained protein language models in various downstream tasks. However, most existing structure-based pre-trained models primarily focus on the residue level, ie, alpha carbon atoms, while ignoring other atoms like side chain atoms. We argue that modeling proteins at both residue and atom levels is important since the side chain …

[PDF] Graph Neural Machine: A New Model for Learning with Tabular Data

In recent years, there has been a growing interest in mapping data from different domains to graph structures. Among others, neural network models such as the multi-layer perceptron (MLP) can be modeled as graphs. In fact, MLPs can be represented as directed acyclic graphs. Graph neural networks (GNNs) have recently become the standard tool for performing machine learning tasks on graphs. In this work, we show that an MLP is equivalent to an asynchronous message passing GNN model which …

[PDF] Interplay between tie strength and neighbourhood topology in complex networks: Granovetter's theory and beyond

Granovetter's weak ties theory is a very important sociological theory according to which a correlation between edge weight and the network's topology should exist. More specifically, the neighbourhood overlap of two nodes connected by an edge should be positively correlated with edge weight (tie strength). However, some real social networks exhibit a negative correlation-the most prominent example is the scientific collaboration network, for which overlap decreases with edge weight. It has …

[HTML] Single-Cell RNA Sequencing Reveals HIF1A as a Severity-Sensitive Immunological Scar in Circulating Monocytes of Convalescent Comorbidity-Free COVID-19 …

COVID-19, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is characterized by a wide range of clinical symptoms and a poorly predictable disease course. Although in-depth transcriptomic investigations of peripheral blood samples from COVID-19 patients have been performed, the detailed molecular mechanisms underlying an asymptomatic, mild or severe disease course, particularly in patients without relevant comorbidities, remain poorly understood. While previous …

[HTML] LFA-1 nanoclusters integrate TCR stimulation strength to tune T-cell cytotoxic activity

T-cell cytotoxic function relies on the cooperation between the highly specific but poorly adhesive T-cell receptor (TCR) and the integrin LFA-1. How LFA-1-mediated adhesion may scale with TCR stimulation strength is ill-defined. Here, we show that …

[HTML] SARS-CoV-2 vaccination may mitigate dysregulation of IL-1/IL-18 and gastrointestinal symptoms of the post-COVID-19 condition

The rapid development of safe and effective vaccines helped to prevent severe disease courses after SARS-CoV-2 infection and to mitigate the progression of the COVID-19 pandemic. While there is evidence that vaccination may reduce the risk of …

[PDF] Defining the mechanisms and properties of post-transcriptional regulatory disordered regions by high-throughput functional profiling

Disordered regions within RNA binding proteins are required to control mRNA decay and protein synthesis. To understand how these disordered regions modulate gene expression, we surveyed regulatory activity across the entire disordered proteome using a high-throughput functional assay. We identified hundreds of regulatory sequences within intrinsically disordered regions and demonstrate how these elements cooperate with core mRNA decay machinery to promote transcript turnover …

[HTML] CompeteSMoE--Effective Training of Sparse Mixture of Experts via Competition

Sparse mixture of experts (SMoE) offers an appealing solution to scale up the model complexity beyond the mean of increasing the network's depth or width. However, effective training of SMoE has proven to be challenging due to the representation collapse issue, which causes parameter redundancy and limited representation potentials. In this work, we propose a competition mechanism to address this fundamental challenge of representation collapse. By routing inputs only to experts …

[PDF] Automated Cognate Detection as a Supervised Link Prediction Task with Cognate Transformer

Identification of cognates across related languages is one of the primary problems in historical linguistics. Automated cognate identification is helpful for several downstream tasks including identifying sound correspondences, proto-language reconstruction, phylogenetic classification, etc. Previous state-of-the-art methods for cognate identification are mostly based on distributions of phonemes computed across multilingual wordlists and make little use of the cognacy labels that define …

Unlocking protein-based biomarker potential for graft-versus-host disease following allogenic hematopoietic stem cell transplants

Despite the numerous advantages of allogeneic hematopoietic stem cell transplants (allo-HSCT), there exists a notable association with risks, particularly during the preconditioning period and predominantly post-intervention, exemplified by the …

Preclinical Evaluation of an Anti-CD41 CAR T Cell in Acute Megakaryoblastic Leukemia on in Vitro and In Vivo Models

Acute Megakaryoblastic Leukemia (AMkL) is a rare disease that represents 5% of all reported AML cases and is diagnosed with high frequency in children with Down Syndrome and elderly people. M7-AMkL is characterized by a low overall survival …

Frontiers Corrigendum Template for Authors

Frontiers | Frontiers Corrigendum Template for Authors Skip to main content Top bar navigation Frontiers in Immunology About us About us Who we are Mission Values History Leadership Awards Impact and progress Frontiers' impact Progress Report …

[PDF] Deep mutational scanning reveals functional constraints and antigenic variability of Lassa virus glycoprotein complex

Lassa virus is estimated to cause thousands of human deaths per year, primarily due to spillovers from its natural host, Mastomys rodents. Efforts to create vaccines and antibody therapeutics must account for the evolutionary variability of Lassa virus's …

[HTML] Ultrahigh frequencies of peripherally matured LGI1-and CASPR2-reactive B cells characterize the cerebrospinal fluid in autoimmune encephalitis

Intrathecal synthesis of central nervous system (CNS)-reactive autoantibodies is observed across patients with autoimmune encephalitis (AE), who show multiple residual neurobehavioral deficits and relapses despite immunotherapies. We …

CD23+ IgG1+ memory B cells are poised to switch to pathogenic IgE production in food allergy

Food allergy is caused by allergen-specific immunoglobulin E (IgE) antibodies, but little is known about the B cell memory of persistent IgE responses. Here, we describe, in human pediatric peanut allergy, a population of CD23+ IgG1+ memory B …

Σύντομη ιστορία του κόσμου

Σε αυτή την πανοραμική θεώρηση του κόσμου, ο David Baker καταγράφει τις ιστορικές μεταβολές στο Σύμπαν, αποκαλύπτοντας την τεράστια αύξηση της πολυπλοκότητας που συνοδεύει κάθε εξελικτική φάση του παρελθόντος, του …

[PDF] Preservation of memory B cell homeostasis in an individual producing broadly neutralising antibodies against HIV-1

Immunological determinants favouring emergence of broadly neutralising antibodies are crucial to the development of HIV-1 vaccination strategies. Here, we combined RNAseq and B cell cloning approaches to isolate a broadly neutralising antibody …

Type 2–polarized memory B cells hold allergen-specific IgE memory

Allergen-specific immunoglobulin E (IgE) antibodies mediate pathology in diseases such as allergic rhinitis and food allergy. Memory B cells (MBCs) contribute to circulating IgE by regenerating IgE-producing plasma cells upon allergen encounter …

TCR signaling induces STAT3 phosphorylation to promote TH17 cell differentiation

TH17 differentiation is critically controlled by “signal 3” of cytokines (IL-6/IL-23) through STAT3. However, cytokines alone induced only a moderate level of STAT3 phosphorylation. Surprisingly, TCR stimulation alone induced STAT3 …

[PDF] Anti-Vα24Jα18 TCR antibody tunes iNKT cell responses to target and kill CD1d-negative tumors in an FcγRII (CD32)-dependent manner

Invariant natural killer T (iNKT) cells play an essential role in antitumor immunity by exerting cytotoxicity and producing massive amounts of cytokines. iNKT cells express invariant T cell receptors (TCRs) to recognize their cognate glycolipid antigens such …

[PDF] TCR beta Chain Repertoire Characteristic between Healthy Human CD4+ and CD8+ T Cells

T cell is vital in the adaptive immune system, which relays on TCR to recognize and defend against infection and tumors. T cells are mainly divided into well-known CD4+ and CD8+ T cells, which can recognize short peptide antigens presented by …

[HTML] T Cell Responses in Pregnant Women Who Received mRNA-Based Vaccination to Prevent COVID-19 Revealed Unknown Exposure to the Natural Infection and …

We studied T-cell responses to SARS-CoV-2 in 19 pregnant subjects at different gestational weeks who received three doses of mRNA-based vaccination to prevent COVID-19. SARS-CoV-2 peptide pools were used for T-cell recognition studies …

[PDF] Identification and Structural Characterization of a mutant KRAS-G12V specific TCR restricted by HLA-A3

Mutations in KRAS are some of the most common across multiple cancer types and are thus attractive targets for therapy. Recent studies demonstrated that mutant KRAS generates immunogenic neoantigens that can be targeted in adoptive T cell …

Multi-epitope mRNA vaccine candidate to combat HMPV virus: Comment

We would like to discuss on the publication “Development of a novel multi-epitope mRNA vaccine candidate to combat HMPV virus. 1” The research largely relies on in-silico predictions and simulations. While these methods are beneficial for preliminary …

A Tool to Teach Evolution of Protein Sequences and Structures: Prediction of Protein Structure by Building Homology Models

Computer modeling and protein structure visualization tools are effective and engaging ways of presenting various molecular biology concepts to high school and college students. Here, we describe a series of activities and exercises that use …

Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire

Historically, antibody reactivity to pathogens and vaccine antigens has been evaluated using serological measurements of antigen-specific antibodies. However, it is difficult to evaluate all antibodies that contribute to various functions in a single assay, such as the measurement of the neutralizing antibody titer. Bulk antibody repertoire analysis using next-generation sequencing is a comprehensive method for analyzing the overall antibody response; however, it is unreliable for estimating …

[PDF] Learning immune receptor representations with protein language models

Protein language models (PLMs) learn contextual representations from protein sequences and are profoundly impacting various scientific disciplines spanning protein design, drug discovery, and structural predictions. One particular research …

[HTML] The MOG antibody non-P42 epitope is predictive of a relapsing course in MOG antibody-associated disease

Background Myelin oligodendrocyte glycoprotein (MOG) IgG seropositivity is a prerequisite for MOG antibody-associated disease (MOGAD) diagnosis. While a significant proportion of patients experience a relapsing disease, there is currently no …

[PDF] SARS-CoV-2 spike-FLIPr fusion protein plus lipidated FLIPr protects against various SARS-CoV-2 variants in hamsters

Vaccine-induced mucosal immunity and broad protective capacity against various severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants remain inadequate. Formyl peptide receptor-like 1 inhibitory protein (FLIPr), produced by …

Cbl-b mitigates the responsiveness of naive CD8+ T cells that experience extensive tonic T cell receptor signaling

Naive T cells experience tonic T cell receptor (TCR) signaling in response to self-antigens presented by major histocompatibility complex (MHC) in secondary lymphoid organs. We investigated how relatively weak or strong tonic TCR signals …

[PDF] Frequency of Dengue Virus-Specific T Cells is related to Infection Outcome in Endemic Settings

Dengue is widespread in tropical and subtropical regions globally and leads to a considerable burden of disease. Annually, dengue virus (DENV) causes up to 400 million infections, of which~ 25% present with clinical symptoms ranging from mild to …

[PDF] Cerebra: a computationally efficient framework for accurate protein structure prediction

Remarkable progress has been made in the field of protein structure prediction in the past years. State-of-the-art methods like AlphaFold2 and RoseTTAFold2 achieve prediction accuracy close to experimental structural determination, but at the cost of …

[PDF] ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning

Designing de novo proteins beyond those found in nature holds significant promise for advancements in both scientific and engineering applications. Current methodologies for protein design often rely on AI-based models, such as surrogate …

Revolutionizing protein–protein interaction prediction with deep learning

Protein–protein interactions (PPIs) are pivotal for driving diverse biological processes, and any disturbance in these interactions can lead to disease. Thus, the study of PPIs has been a central focus in biology. Recent developments in deep learning methods, coupled with the vast genomic sequence data, have significantly boosted the accuracy of predicting protein structures and modeling protein complexes, approaching levels comparable to experimental techniques. Herein, we …

[PDF] Progress and Opportunities of Foundation Models in Bioinformatics

Bioinformatics has witnessed a paradigm shift with the increasing integration of artificial intelligence (AI), particularly through the adoption of foundation models (FMs). These AI techniques have rapidly advanced, addressing historical challenges in bioinformatics such as the scarcity of annotated data and the presence of data noise. FMs are particularly adept at handling large-scale, unlabeled data, a common scenario in biological contexts due to the time-consuming and costly nature of …

[PDF] Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

Combining discrete and continuous data is an important capability for generative models. We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that provides the missing link in enabling flow-based generative …

[HTML] Computer-aided engineering of stabilized fibroblast growth factor 21

FGF21 is an endocrine signaling protein belonging to the family of fibroblast growth factors (FGFs). It has emerged as a molecule of interest for treating various metabolic diseases due to its role in regulating glucogenesis and ketogenesis in the liver. However, FGF21 is prone to heat, proteolytic, and acid-mediated degradation, and its low molecular weight makes it susceptible to kidney clearance, significantly reducing its therapeutic potential. Protein engineering studies addressing these challenges …

[HTML] B cell-reactive triad of B cells, follicular helper and regulatory T cells at homeostasis

Autoreactive B cells are silenced through receptor editing, clonal deletion and anergy induction. Additional autoreactive B cells are ignorant because of physical segregation from their cognate autoantigen. Unexpectedly, we find that follicular B cell-derived autoantigen, including cell surface molecules such as FcγRIIB, is a class of homeostatic autoantigen that can induce spontaneous germinal centers (GCs) and B cell-reactive autoantibodies in non-autoimmune animals with intact T and B cell …

Canine T zone lymphoma is a tumor of mature, previously activated αβ T cells

ABSTRACT T cell lymphomas are a diverse group of tumors found in both dogs and humans, originating from various normal T cell types. Identifying the origin of neoplastic lymphocytes can offer valuable insights into the pathogenesis and clinical behavior of these tumors. T zone lymphoma (TZL) in dogs is characterized by the absence of CD45 expression, a strong breed predilection, and its association with adult-onset demodicosis—a condition believed to be linked to immunosuppression …

[PDF] Liver transplant-facilitated recovery of MAIT cell from dysregulation in HBV-related liver failure demonstrates clinical benefits

Mucosal-associated invariant T (MAIT) cells exert multifaceted effects such as anti-microbial activity, tissue repair, and pro-fibrotic effects across various disease settings. Nonetheless, their role in liver injury and hemostasis is a current topic of debate. Here, we presented a MAIT cell-centered profiling in chronic HBV-infected patients with varying degree of liver injury and those who underwent liver transplantation. Liver transplantation facilitated a gradual recovery of recipient …

[PDF] PRESCOTT: a population aware, epistatic and structural model accurately predicts missense effect

Predicting the functional impact of point mutations is a complex yet vital task in genomics. PRESCOTT stands at the forefront of this challenge and reconstructs complete mutational landscapes of proteins, enables the identification of protein …

[HTML] Unraveling Molecular Recognition of Glycan Ligands by Siglec-9 via NMR Spectroscopy and Molecular Dynamics Modeling

Human sialic-acid-binding immunoglobulin-like lectin-9 (Siglec-9) is a glycoimmune checkpoint receptor expressed on several immune cells. Binding of Siglec-9 to sialic acid containing glycans (sialoglycans) is well documented to modulate its functions …

Community Benchmarking Exercises for Docking and Scoring

Drug discovery is an extensive and challenging pathway that needs a humungous amount of funding as well as concerted efforts from interdisciplinary experts. High throughput screening is a traditional approach for identifying hit compounds by …

Addressing the antibody germline bias and its effect on language models for improved antibody design

The versatile binding properties of antibodies have made them an extremely important class of biotherapeutics. However, therapeutic antibody development is a complex, expensive and time-consuming task, with the final antibody needing to not …

[PDF] Professional Agents--Evolving Large Language Models into Autonomous Experts with Human-Level Competencies

The advent of large language models (LLMs) such as ChatGPT, PaLM, and GPT-4 has catalyzed remarkable advances in natural language processing, demonstrating human-like language fluency and reasoning capacities. This position paper introduces the concept of Professional Agents (PAgents), an application framework harnessing LLM capabilities to create autonomous agents with controllable, specialized, interactive, and professional-level competencies. We posit that PAgents …

[PDF] GenerRNA: A generative pre-trained language model for de novo RNA design

The design of RNA plays a crucial role in developing RNA vaccines, nucleic acid therapeutics, and innovative biotechnological tools. Nevertheless, existing techniques lack versatility across various tasks and frequently suffer from a deficiency of automated generation. Inspired by the remarkable success of Large Language Models (LLMs) in the realm of protein and molecule design, we present GenerRNA, the first large-scale pre-trained model for RNA generation, aiming to …

Predicting Protein Functions Based on Heterogeneous Graph Attention Technique

In bioinformatics, protein function prediction stands as a fundamental area of research and plays a crucial role in addressing various biological challenges, such as the identification of potential targets for drug discovery and the elucidation of disease mechanisms. However, known functional annotation databases usually provide positive experimental annotations that proteins carry out a given function, and rarely record negative experimental annotations that proteins do not carry out a …

Porosity prediction through well logging data: A combined approach of convolutional neural network and transformer model (CNN-transformer)

Porosity, as a key parameter to describe the properties of rock reservoirs, is essential for evaluating the permeability and fluid migration performance of underground rocks. In order to overcome the limitations of traditional logging porosity interpretation methods in the face of geological complexity and nonlinear relationships, this study introduces a CNN (convolutional neural network)-transformer model, which aims to improve the accuracy and generalization ability of logging porosity prediction. CNNs …

[HTML] Chemical and biological language models in molecular design: opportunities, risks and scientific reasoning

In the physical and life sciences, including drug discovery, the use of deep learning (DL) models, such as language models (LMs) or graph neural networks (GNNs), is on the rise for various applications. LMs are generally designed to translate sequences of characters and are particularly versatile and adaptable to many different machine translation tasks, giving rise to their popularity in many areas. Transformer networks, with their multi-head self-attention mechanism, and encoder …

[HTML] Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data Reveals Memory-like NK Cell Subset Associated with Mycobacterium tuberculosis Latency

Natural killer (NK) cells are innate-like lymphocytes that belong to the family of type-1 innate lymphoid cells and rapidly respond to virus-infected and tumor cells. In this study, we have combined scRNA-seq data and bulk RNA-seq data to define the …

Application of Chimeric Antigen Receptor Therapy beyond Oncology: A Bibliometric and Visualized Analysis

Purpose: Chimeric antigen receptor therapy beyond oncology has gained increasing attention. While a substantial number of publications have emerged in recent years, there has been a paucity of conducted bibliometric studies. Our objective is to …

Chromatin Accessibility Landscapes of CD4+ T cells in Monozygotic Discordant Twin pairs for Asthma.

Methods ATAC-seq was utilized to assess chromatin accessibility in CD4+ T cell subsets (Naïve, Th2, and Th1 cells), obtained from asthmatic and non-asthmatic participants, including discordant twin pairs and non-twin individuals. The inclusion …

[PDF] Scientific Language Modeling: A Quantitative Review of Large Language Models in Molecular Science

Efficient molecular modeling and design are crucial for the discovery and exploration of novel molecules, and the incorporation of deep learning methods has revolutionized this field. In particular, large language models (LLMs) offer a fresh …

[PDF] Integration of cognitive tasks into artificial general intelligence test for large models

During the evolution of large models, performance evaluation is necessarily performed on the intermediate models to assess their capabilities, and on the well-trained model to ensure safety before practical application. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united framework for assessing the multidimensional intelligence of large models. In this perspective, we advocate for a comprehensive framework of artificial general intelligence (AGI) test …

Therapeutic vaccine-induced plasma cell differentiation is defective in the presence of persistently high HBsAg levels

Abstract Background & Aims The impaired response of antigen-specific B cells to therapeutic vaccination in chronic hepatitis B virus (HBV) infection remains unclear. The development of vaccines or strategies to overcome this obstacle is vital for advancing chronic hepatitis B (CHB) management. Methods A mouse model, denominated as E6F6-B, was engineered featuring a knock-in of a B cell receptor (BCR) that specifically recognizes the HBV surface antigen (HBsAg). This model …

[PDF] On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis

We investigate the computational limits of the memory retrieval dynamics of modern Hopfield models from the fine-grained complexity analysis. Our key contribution is the characterization of a phase transition behavior in the efficiency of all possible modern Hopfield models based on the norm of patterns. Specifically, we establish an upper bound criterion for the norm of input query patterns and memory patterns. Only below this criterion, sub-quadratic (efficient) variants of the modern Hopfield model …

[PDF] A model for enhancer selection in dense regulatory networks captures the dynamics of cell type specification

Multicellular organisms are made of many cell types that share a common genetic code. Cell type specification occurs through feedback interactions between transcription factors (TFs) and enhancers, which are regulatory elements with dynamic chromatin that can initiate transcription in distal genes. Understanding the structure and dynamics of these regulatory networks is a key challenge for cell biology. Here, we address this by considering a generic model for a dense feedback …

[PDF] Voronoi Candidates for Bayesian Optimization

Bayesian optimization (BO) offers an elegant approach for efficiently optimizing black-box functions. However, acquisition criteria demand their own challenging inner-optimization, which can induce significant overhead. Many practical BO methods …

Mining Channel-Regulated Peptides from Animal Venom by Integrating Sequence Semantics and Structural Information

Channel-regulated peptides (CRPs) derived from animal venom hold great promise as potential drug candidates for numerous diseases associated with channel proteins. However, discovering and identifying CRPs using traditional bio-experimental methods is a time-consuming and laborious process. While there were a few computational studies on CRPs, they were limited to specific channel proteins, relied heavily on complex feature engineering, and lacked the incorporation of multi …

[PDF] Effective Protein-Protein Interaction Exploration with PPIretrieval

Protein-protein interactions (PPIs) are crucial in regulating numerous cellular functions, including signal transduction, transportation, and immune defense. As the accuracy of multi-chain protein complex structure prediction improves, the challenge has shifted towards effectively navigating the vast complex universe to identify potential PPIs. Herein, we propose PPIretrieval, the first deep learning-based model for protein-protein interaction exploration, which leverages existing PPI data to …

[HTML] 机器学习在蛋白质功能预测领域的研究进展

蛋白质是有机生命体内不可或缺的化合物, 在生命活动中发挥着多种重要作用, 了解蛋白质的功能有助于医学和药物研发等领域的研究. 此外, 酶在绿色合成中的应用一直备受人们关注, 但是由于酶的种类和功能多种多样, 获取特定功能酶的成本高昂, 限制了其进一步的应用. 目前, 蛋白质的具体功能主要通过实验表征确定, 该方法实验工作繁琐且耗时耗力, 同时, 随着生物信息学和测序技术的高速发展, 已测序得到的蛋白质序列数量远大于功能获得注释的序列数量, 高效预测蛋白质功能变 …

[PDF] ICoN: Integration using Co-attention across Biological Networks

Motivation. Molecular interaction networks are powerful tools for studying cellular functions. Integrating diverse types of networks enhances performance in downstream tasks such as gene module detection and protein function prediction. The challenge lies in extracting meaningful protein feature representations due to varying levels of sparsity and noise across these heterogeneous networks. Results. We propose ICoN, a novel co-attention-based, denoising, unsupervised graph …

[PDF] International Journal of Data Science and Big Data Analytics

This paper explores the transformative integration of Natural Language Processing (NLP) with data visualization in the realm of healthcare informatics. The study encompasses a comprehensive analysis of health data derived from medical documentation, social media, and biological literature. Through advanced computational modeling and machine learning, the research enriches our understanding of linguistic conceptual relationships within complex healthcare …

[HTML] Visualization of Early RNA Replication Kinetics of SARS-CoV-2 by Using Single Molecule RNA-Fish Combined with Immunofluorescence

SARS-CoV-2 infection remains a global burden. Despite intensive research, the mechanism and dynamics of early viral replication are not completely understood, such as the kinetics of the formation of genomic RNA (gRNA), sub-genomic RNA …

[HTML] Hybrid immunity to SARS‐CoV‐2 in patients with chronic lymphocytic leukemia

Objective Preventing severe COVID‐19 remains a priority globally, particularly in the immunocompromised population. As shown in healthy individuals, immunity against SARS‐CoV‐2 can be yielded by previous infection, vaccination, or both (hybrid …

[PDF] Mechanical forces amplify TCR mechanotransduction in T cell activation and function

Adoptive T cell immunotherapies, including engineered T cell receptor (eTCR) and chimeric antigen receptor (CAR) T cell immunotherapies, have shown efficacy in treating a subset of hematologic malignancies, exhibit promise in solid tumors, and …

[HTML] Identification of a novel linear B-cell epitope on the p30 protein of African swine fever virus using monoclonal antibodies

Abstract The outbreak of African Swine Fever (ASF) has caused huge economic losses to the pig industry. There are no safe and effective vaccines or diagnostics available. The p30 protein serves as a key target for the detection of ASFV antibodies …

Computational design of binders targeting the VSDIV from NaV1. 7 sodium channel

Chronic pain affects about 20% of the US population, but safe treatments are limited. There is an urgent need for effective and non-addictive therapies for chronic pan conditions. Voltage-gated sodium (NaV) channel, NaV1. 7, is a key player in pain …

[PDF] Identification of B cell subsets based on antigen receptor sequences using deep learning

B cell receptors (BCRs) denote antigen specificity, while corresponding cell subsets indicate B cell functionality. Since each B cell uniquely encodes this combination, physical isolation and subsequent processing of individual B cells become …

[PDF] Addressing the antibody germline bias and its effect on language models for improved antibody design

The versatile binding properties of antibodies have made them an extremely important class of biotherapeutics. However, therapeutic antibody development is a complex, expensive and time-consuming task, with the final antibody needing to not …

[PDF] Electrostatic properties of human germlines and biodistribution of small biologics

Off-target biodistribution of biologics bears important toxicological consequences. Antibody fragments intended for use as vectors of cytotoxic payloads (eg antibody-drug conjugates, radiotherapy) can accumulate at clearance organs like kidneys and liver, where they can cause dose-limiting toxicities. Renal and hepatic uptakes are known to be affected by protein electrostatics, which promote protein internalization through pinocytosis. Using minibodies as a model of an antibody fragment lacking …

Accurate top protein variant discovery via low-N pick-and-validate machine learning

A strategy to obtain the greatest number of best-performing variants with least amount of experimental effort over the vast combinatorial mutational landscape would have enormous utility in boosting resource producibility for protein …

[PDF] Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction

The 3D structure of RNA critically influences its functionality, and understanding this structure is vital for deciphering RNA biology. Experimental methods for determining RNA structures are labour-intensive, expensive, and time-consuming. Computational …

Leveraging data-efficient RNA contact prediction toward reliable RNA structure prediction

On the molecular level, life is orchestrated through an interplay of many biomolecules. To gain any detailed understanding of biomolecular function, one needs to know their structure. For proteins, the richness of labeled training data …

Contact maps in RNA structure prediction: Much more than pure simulation accelerators

Predicting the spatial structure of non-coding RNA (ncRNA) is an important task for understanding fundamental processes in living nature. Physical force fields are used to infer the structure from a sequence using simulations on high-performance …

COSMIC2: A global resource for structure prediction and structural analysis

334a Tuesday, February 13, 2024 on National Science Foundation-funded supercomputers housed at the San Diego Supercomputer Center. As such, computing time is free and provided by the COSMIC2 project team to users …

Understanding HIV bnAb interactions through structure prediction and MD simulations

One approach for an HIV vaccine is through broadly neutralizing antibody (bnAb) elicitation. However, a major challenge with this approach is that bnAb precursors are still largely unknown. Here, we propose combining bioinformatics, deep learning …

Structure prediction of cyclic peptides via molecular dynamics and machine learning

A major obstacle to cyclic peptide development is that little structural information is available for these molecules, making it difficult to perform structure-based design or understand why different cyclic peptide sequences display different binding affinity …

[PDF] Building and analyzing metacells in single-cell genomics data

The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of …

[PDF] Fast and accurate modeling and design of antibody-antigen complex using tFold

Accurate prediction of antibody-antigen complex structures holds significant potential for advancing biomedical research and the design of therapeutic antibodies. Currently, structure prediction for protein monomers has achieved considerable success, and promising progress has been made in extending this achievement to the prediction of protein complexes. However, despite these advancements, fast and accurate prediction of antibody-antigen complex structures remains a challenging …

Structure-based neural network predictions of protein-carbohydrate interactions

Carbohydrates dynamically and transiently interact with proteins for cell-cell recognition, cellular differentiation, immune response, and other cellular processes. Despite the molecular importance of these interactions, there are currently few …

[HTML] Systematic evaluation of B-cell clonal family inference approaches

The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life …

[HTML] An Engineered Mouse Model That Generates a Diverse Repertoire of Endogenous, High-Affinity Common Light Chain Antibodies

Bispecific antibodies have gained increasing popularity as therapeutics as they enable novel activities that cannot be achieved with monospecific antibodies. Some of the most popular bispecific formats are molecules in which two Fab arms with …

[PDF] Pycofitness—evaluating the fitness landscape of RNA and protein sequences

Motivation The accurate prediction of how mutations change biophysical properties of proteins or RNA is a major goal in computational biology with tremendous impacts on protein design and genetic variant interpretation. Evolutionary approaches such …

[PDF] Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning

In this paper, we propose R $^ 3$: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the benefits of process supervision for large language …

[PDF] Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models

Large pretrained protein language models (PLMs) have improved protein property and structure prediction from sequences via transfer learning, in which weights and representations from PLMs are repurposed for downstream tasks. Although PLMs …

[PDF] Pretrained Generative Language Models as General Learning Frameworks for Sequence-Based Tasks

We propose that small pretrained foundational generative language models with millions of parameters can be utilized as a general learning framework for sequence-based tasks. Our proposal overcomes the computational resource, skill set, and …

[PDF] Noise Contrastive Alignment of Language Models with Explicit Rewards

User intentions are typically formalized as evaluation rewards to be maximized when fine-tuning language models (LMs). Existing alignment methods, such as Direct Preference Optimization (DPO), are mainly tailored for pairwise preference data …

[PDF] Transferable deep generative modeling of intrinsically disordered protein conformations

Intrinsically disordered proteins have dynamic structures through which they play key biological roles. The elucidation of their conformational ensembles is a challenging problem requiring an integrated use of computational and experimental methods …

[PDF] Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

Detecting text generated by modern large language models is thought to be hard, as both LLMs and humans can exhibit a wide range of complex behaviors. However, we find that a score based on contrasting two closely related language models is highly …

[HTML] Assessment of human leukocyte antigen-based neoantigen presentation to determine pan-cancer response to immunotherapy

Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with …

[HTML] Mucosal vaccine-induced cross-reactive CD8+ T cells protect against SARS-CoV-2 XBB. 1.5 respiratory tract infection

A nasally delivered chimpanzee adenoviral-vectored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine (ChAd-SARS-CoV-2-S) is currently used in India (iNCOVACC). Here, we update this vaccine by creating ChAd-SARS …

[HTML] Increased cAMP-PKA signaling pathway activation is involved in up-regulation of CTLA-4 expression in CD4+ T cells in acute SIVmac239-infected Chinese rhesus …

Abstract Human immunodeficiency virus-1 (HIV-1) infection can cause chronic activation, exhaustion, and anergy of the immune system. Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) is an immune checkpoint molecule, which plays an …

[PDF] PREX1 improves homeostatic proliferation to maintain a naïve CD4 T cell compartment in older age

The human adult immune system maintains normal T-cell counts and compensates for T-cell loss over lifetime 23 mainly through peripheral homeostatic proliferation after the ability of the thymus to generate new T cells has 24 rapidly declined at …

Zeb2 drives the formation of CD11c+ atypical B cells to sustain germinal centers that control persistent infection

CD11c+ atypical B cells (ABCs) are an alternative memory B cell lineage associated with immunization, infection, and autoimmunity. However, the factors that drive the transcriptional program of ABCs have not been identified, and the function of this …

T cell receptor sequences are the dominant factor contributing to the phenotype of CD8+ T cells with specificities against immunogenic viral antigens

BRD4354 Is a Potent Covalent Inhibitor against the SARS-CoV-2 Main Protease

Numerous organic molecules are known to inhibit the main protease (MPro) of SARS-CoV-2, the pathogen of Coronavirus Disease 2019 (COVID-19). Guided by previous research on zinc-ligand inhibitors of MPro and zinc-dependent histone deacetylases …

[PDF] TCRosetta: an integrated analysis and annotation platform for T-cell receptor sequences

T cells and T-cell receptors (TCRs) are essential components of the adaptive immune system. Characterization of the TCR repertoire offers a promising and highly informative source for understanding the functions of T cells in the immune response …

[HTML] Drug repurposing screen identifies lonafarnib as respiratory syncytial virus fusion protein inhibitor

Respiratory syncytial virus (RSV) is a common cause of acute lower respiratory tract infection in infants, older adults and the immunocompromised. Effective directly acting antivirals are not yet available for clinical use. To address this, we screen the …

[HTML] Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches

Leishmania donovani is the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to …

A two‐step mechanism for the binding of the HIV‐1 MPER epitope by the 10 E 8 antibody onto biosensor‐supported lipid bilayers

HIV‐1 antibodies targeting the carboxy‐terminal area of the membrane‐proximal external region (ctMPER) are close to exerting viral pan‐neutralization. Here, we reconstituted the ctMPER epitope as the N‐terminal extremity of the Env glycoprotein …

A tool for analyzing complex epitope binning data of monoclonal antibodies

Monoclonal antibodies (mAbs) of different antigen binding footprints can be categorized using binding competition profile differences measured using epitope binning assays, for example, on surface plasmon resonance (SPR) platform. In SPR …

Machine learning for prediction of protein function and elucidation of enzyme function and control

Our machine learning methodology, partial order optimum likelihood (POOL) is used to predict biochemically active amino acids in the three-dimensional structures of proteins. Computed electrostatic and chemical properties of individual amino acids …

Accurately predicting protein pKa values non-equilibrium alchemy

The stability, solubility, and function of a protein depend both on its net charge and the protonation states of its individual residues. pK a is a measure of the tendency for a given residue to (de) protonate at a specific pH. Although pK a values can be …

TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion

Studying the effect of single amino acid variations (SAVs) on protein structure and function is integral to advancing our understanding of molecular processes, evolutionary biology, and disease mechanisms. Screening for deleterious variants is …

De novo protein design targeting voltage-gated sodium channel 1.7 using RFdiffusion and AlphaFold2

Voltage-gated sodium (Na V) channels—pore-forming transmembrane proteins regulating sodium flux across cell membranes—have been genetically and pre-clinically identified as a nociceptive drug target with limited addiction potential. In …

[PDF] The signature of a T-cell response to KSHV persists across space and time in individuals with epidemic and endemic KS from Uganda

Inadequate T-cell control of Kaposi sarcoma-associated herpesvirus (KSHV) infection predisposes to development of Kaposi sarcoma (KS), but little is known about the T-cell response to KSHV. Postulating that KS tumors contain abundant KSHV-specific T-cells, we performed transcriptional profiling and T-cell receptor (TCR) repertoire analysis of tumor biopsies from 144 Ugandan adults with KS. We show that CD8+ T-cells and M2-polarized macrophages dominate the tumor micro …

Tolerance-inducing therapies in coeliac disease—mechanisms, progress and future directions

Coeliac disease is an autoinflammatory condition caused by immune reactions to cereal gluten proteins. Currently, the only available treatment for the condition is a lifelong avoidance of gluten proteins in the diet. There is an unmet need for alternative therapies. Coeliac disease has a strong association with certain HLA− DQ allotypes (DQ2. 5, DQ2. 2 and DQ8), and these disease-associated HLA-DQ molecules present deamidated gluten peptides to gluten-specific CD4+ T cells. The …

[PDF] ClassONN: Classification with Oscillatory Neural Networks using the Kuramoto Model

Over the recent years, networks of coupled oscillators or oscillatory neural networks (ONNs) emerged as an alternative computing paradigm with information encoded in phase. Such networks are intrinsically attractive for associative memory applications such as pattern retrieval. Thus far, there are few works focusing on image classification using ONNs, as there is no straightforward way to do it. This paper investigates the performance of a neuromorphic phase-based classification model …

UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow

We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique …

[PDF] Dirichlet Flow Matching with Applications to DNA Sequence Design

Discrete diffusion or flow models could enable faster and more controllable sequence generation than autoregressive models. We show that na\" ive linear flow matching on the simplex is insufficient toward this goal since it suffers from discontinuities in the training target and further pathologies. To overcome this, we develop Dirichlet flow matching on the simplex based on mixtures of Dirichlet distributions as probability paths. In this framework, we derive a connection between …

[PDF] Transcription factors across the Escherichia coli pangenome: a 3D perspective

Motivation: Identification of complete sets of transcription factors (TFs) is a foundational step in the inference of genetic regulatory networks. With the availability of high-quality predictions of protein three-dimensional structures (3D), it has become possible to use structural comparisons for the inference of homology beyond what is possible from sequence analyses alone. This work explores the potential to use predicted 3D structures for the identification of TFs in the Escherichia coli …

[PDF] Structure-Informed Protein Language Model

Protein language models are a powerful tool for learning protein representations through pre-training on vast protein sequence datasets. However, traditional protein language models lack explicit structural supervision, despite its relevance to protein …

[HTML] Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective …

[PDF] Using explainable machine learning to uncover the kinase-substrate interaction landscape

Motivation Phosphorylation, a post-translational modification regulated by protein kinase enzymes, plays an essential role in almost all cellular processes. Understanding how each of the nearly 500 human protein kinases selectively …

[PDF] Discovering and overcoming the bias in neoantigen identification by unified machine learning models

Neoantigens, formed by genetic mutations in tumor cells, are abnormal peptides that can trigger immune responses. Precisely identifying neoantigens from vast mutations is the key to tumor immunotherapy design. There are three main steps in the …

Exploring the immunogenicity of Rv2201-519: A T-cell epitope-based antigen derived from Mycobacterium tuberculosis AsnB with implications for tuberculosis …

Research dedicated to diagnostic reagents and vaccine development for tuberculosis (TB) is challenging due to the paucity of immunodominant antigens that can predict disease risk and exhibit protective potential. Therefore, it is crucial to …

[PDF] Predicting COVID-19 booster immunogenicity against future SARS-CoV-2 variants and the benefits of vaccine updates

The ongoing evolution of the SARS-CoV-2 virus has led to a move to update vaccine antigens in 2022 and 2023. These updated antigens were chosen and approved based on in vitro neutralisation titres against recent SARS-CoV-2 variants. However …

Utilizing murine dendritic cell line DC2. 4 to evaluate the immunogenicity of subunit vaccines in vitro

Subunit vaccines hold substantial promise in controlling infectious diseases, due to their superior safety profile, specific immunogenicity, simplified manufacturing processes, and well-defined chemical compositions. One of the most important end …

[PDF] Protein property prediction based on local environment by 3D equivariant convolutional neural networks

Predicting the properties of proteins is an important procedure in protein engineering. It determines the subspace of mutations for protein modifications, which is critical to the success of the project, but heavily relies on the knowledge and experience of scientists. In this study, we propose a novel deep 3D-CNN model, Eq3DCNN, specifically designed for local environment-related tasks in protein engineering. Eq3DCNN uses basic atom descriptors and their coordinates as inputs …

[PDF] Data science opportunities of large language models for neuroscience and biomedicine

Large language models (LLMs) are a new asset class in the machine-learning landscape. Here we offer a primer on defining properties of these modeling techniques. We then reflect on new modes of investigation in which LLMs can be used to reframe classic neuroscience questions to deliver fresh answers. We reason that LLMs have the potential to (1) enrich neuroscience datasets by adding valuable meta-information, such as advanced text sentiment,(2) summarize vast information …

[PDF] Functional genomics in inborn errors of immunity

Inborn errors of immunity (IEI) comprise a diverse spectrum of 485 disorders as recognized by the International Union of Immunological Societies Committee on Inborn Error of Immunity in 2022. While IEI are monogenic by definition, they illuminate various pathways involved in the pathogenesis of polygenic immune dysregulation as in autoimmune or autoinflammatory syndromes, or in more common infectious diseases that may not have a significant genetic basis. Rapid improvement …

[HTML] Computational Enzyme Redesign Enhances Tolerance to Denaturants for Peptide C-Terminal Amidation

The escalating demand for biocatalysts in pharmaceutical and biochemical applications underscores the critical imperative to enhance enzyme activity and durability under high denaturant concentrations. Nevertheless, the development of a practical computational redesign protocol for improving enzyme tolerance to denaturants is challenging due to the limitations of relying solely on model-driven approaches to adequately capture denaturant–enzyme interactions. In this study, we …

[PDF] A learnable transition from low temperature to high temperature proteins with neural machine translation

This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 million protein homologous pairs from organisms adapted to different temperatures, demonstrates promising capability in targeting thermal stability. A designed variant of the Drosophila melanogaster Engrailed Homeodomain shows …

A Comprehensive Study on Data Augmentation using Machine Learning with Variational Autoencoders

Data augmentation plays a pivotal role in enhancing the performance of machine learning models, particularly in tasks where labeled data is limited. This paper introduces an innovative approach to data augmentation utilizing Variational Autoencoders (VAEs). VAEs are generative models that learn the underlying structure of the input data, allowing for the generation of new, similar data points. In this paper, we explore the theoretical foundations of VAEs, their application in data …

[PDF] Merkel cell polyomavirus-specific and CD39+ CLA+ CD8 T cells as blood-based predictive biomarkers for PD-1 blockade in Merkel cell carcinoma

Merkel cell carcinoma is a skin cancer often driven by Merkel cell polyomavirus (MCPyV) with high rates of response to anti-PD-1 therapy despite low mutational burden. MCPyV-specific CD8 T cells are implicated in anti-PD-1-associated immune responses and provide a means to directly study tumor-specific T cell responses to treatment. Using mass cytometry and combinatorial tetramer staining, we find that baseline frequencies of blood MCPyV-specific cells correlated with response and …

[PDF] Koo-Winkelaar

Idiopathic acquired aplastic anemia (AA) is characterized by bone marrow (BM) hypocellularity due to a profound decrease in hematopoiesis resulting in pancytopenia (1). Symptoms of AA relate to the severity of pancytopenia and severe cases of AA are potentially fatal, mainly due to bleeding and infectious complications. Two effective treatments can result in recovery of hematopoiesis: allogeneic hematopoietic stem cell transplantation (allo-HSCT) and immunosuppressive …

Age-associated CD4+ T cells with B cell-promoting functions are regulated by ZEB2 in autoimmunity

Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4+ T cell subsets from 354 autoimmune disease patients and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3midCD4+ effector memory T cell subset that expands with age, which we designated “age-associated helper T (ThA) cells”. ThA cells exhibited both a …

[PDF] GLUT1-mediated glucose import in B cells is critical for anaplerotic balance and humoral immunity

Glucose uptake increases during B cell activation and antibody-secreting cell (ASC) differentiation, but conflicting findings prevent a clear metabolic profile at different stages of B cell activation. Deletion of the glucose transporter type 1 (GLUT1) gene in mature B cells (GLUT1-cKO) results in normal B cell development, but it reduces germinal center B cells and ASCs. GLUT1-cKO mice show decreased antigen-specific antibody titers after vaccination. In vitro, GLUT1-deficient B cells show …

[HTML] Single cell analysis revealed that two distinct, unique CD4+ T cell subsets were increased in the small intestinal intraepithelial lymphocytes of aged mice

Recent advances in research suggest that aging has a controllable chronic inflammatory disease aspect. Aging systemic T cells, which secrete pro-inflammatory factors, affect surrounding somatic cells, and accelerate the aging process through chronic inflammation, have attracted attention as potential therapeutic targets in aging. On the other hand, there are few reports on the aging of the intestinal immune system, which differs from the systemic immune system in many ways. In the current …

Regulation of Membrane Localization and Protein Stability by the PTEN Translational Isoform, PTEN-L

The importance of PTEN as a tumor suppressor is clearly illustrated by its frequent alterations in multiple cancer types (breast, glioblastoma, prostate, endometrial) through mutation, homozygous deletion, loss of heterozygosity, and repression at the transcriptional, post-transcriptional, and post-translational levels. Cancer patients with tumoral PTEN loss or repression are often treated with small molecule inhibitors targeting aberrant signaling pathways, but restoration of PTEN protein expression …

[PDF] Cryo-EM Structure of a Human LECT2 Amyloid Fibril Reveals a Network of Polar Ladders

Amyloid diseases are linked to the formation and persistence of large, multimeric structures in various tissues. Amyloid fibrils are characterized by a cross-beta scaffold in which identical protein molecules mate tightly as beta-strands to form a long, unbranched fibril1, 2. Before amyloid-forming proteins assemble into fibrils, they can display a globular fold, requiring partial or total unfolding to convert into an amyloid state3, 4. Debilitating neurodegenerative diseases such as Alzheimer's and …

[PDF] HDAC1/2 and HDAC3 play distinct roles in controlling adult Meibomian gland homeostasis

Purpose To investigate the roles of HDAC1/2 and HDAC3 in adult Meibomian gland (MG) homeostasis. Methods HDAC1/2 or HDAC3 were inducibly deleted in MG epithelial cells of adult mice. The morphology of MG was examined. Proliferation, apoptosis, and expression of MG acinus and duct marker genes, meibocyte differentiation genes, and HDAC target genes, were analyzed via immunofluorescence, TUNEL assay, and RNA in situ hybridization. Results Co …

[PDF] SARS-CoV-2 infection induces robust mucosal antibody responses in the upper respiratory tract.

Despite multiple research efforts to characterize COVID-19 in humans, there is no clear data on the specific role of mucosal immunity on COVID-19 disease. Here, we longitudinally profile the antibody response against SARS-CoV-2 and seasonal …

Benchmarking antibody clustering methods using sequence, structural, and machine learning similarity measures for antibody discovery applications

Antibodies are proteins of our immune system that have been harnessed as biotherapeutics. The discovery of antibody-based therapeutics relies on analyzing large volumes of diverse sequences coming from phage display or animal …

Discovering inhibitors against human norovirus protein target 3CLpro using ligand-protein docking

Human norovirus (HuNoV) is the causative agent for viral gastrointestinal infections and is the leading cause of acute gastroenteritis globally, affecting all population groups. Norovirus is a highly contagious virus exhibiting gastrointestinal symptoms …

Alchemical free-energy simulations support the formation of the sarco-endoplasmic reticulum calcium pump (SERCA) inhibitory complex from the phospholamban …

116a Sunday, February 11, 2024 in PLN (Ile18 to Leu52) for the SERCA-PLN complex, as well as the PLN monomer and pentamer in a lipid bilayer. We compared the simulation data to the functional analyses of the PLN alanine substitutions and …

[PDF] AlphaCRV: A Pipeline for Identifying Accurate Binder Topologies in Mass-Modeling with AlphaFold

The speed and accuracy of deep learning-based structure prediction algorithms makes it now possible to perform in silico pull-downs to identify protein-protein interactions at a proteome-wide scale. However, existing scoring algorithms struggle …

[PDF] Association of Baseline Tumor-Specific Neoantigens and CD8+ T-Cell Infiltration With Immune-Related Adverse Events Secondary to Immune Checkpoint Inhibitors

PURPOSE Recent evidence has shown that higher tumor mutational burden strongly correlates with an increased risk of immune-related adverse events (irAEs). By using an integrated multiomics approach, we further studied the association between …

[PDF] Exhausted tumor-infiltrating CD39+ CD103+ CD8+ T cells unveil potential for increased survival in human pancreatic cancer

In pancreatic ductal adenocarcinoma, the infiltration of CD8+ T cells within the tumor microenvironment correlate with a favorable prognosis. However, a significant proportion of tumor-infiltrating T cells become trapped within the desmoplastic stroma …

[PDF] ExpoSeq: Simplified analysis of high-throughput sequencing data from antibody discovery campaigns

High-throughput sequencing (HTS) offers a modern, fast, and explorative solution to unveil the full potential of display techniques, like antibody phage display, in molecular biology. However, a significant challenge lies in the processing and analysis of such data. Furthermore, there is a notable absence of open-access user-friendly software tools that can be utilised by scientists lacking programming expertise. Here, we present ExpoSeq as an easy-to-use tool to explore, process, and …

State-specific protein–ligand complex structure prediction with a multiscale deep generative model

The binding complexes formed by proteins and small molecule ligands are ubiquitous and critical to life. Despite recent advancements in protein structure prediction, existing algorithms are so far unable to systematically predict the binding …

[PDF] Integrating Machine Learning-Enhanced Immunopeptidomics and SARS-CoV-2 Population-Scale Analyses Unveils Novel Antigenic Features for Next-Generation …

Next-generation T-cell-directed vaccines for COVID-19 aim to induce durable T-cell immunity against circulating and future hypermutated SARS-CoV-2 variants. Mass Spectrometry (MS)-based immunopeptidomics holds promise for guiding vaccine …

Aberrant B cell receptor signaling in circulating naïve and IgA+ memory B cells from newly-diagnosed autoantibody-positive rheumatoid arthritis patients

Objective Altered B cell receptor (BCR) signaling has been implicated in the pathogenesis of rheumatoid arthritis (RA). Here we aimed to identify signaling aberrations in autoantibody-positive and autoantibody-negative RA patients by …

[HTML] Applying valency-based immuno-selection to generate broadly cross-reactive antibodies against influenza hemagglutinins

Conserved epitopes shared between virus subtypes are often subdominant, making it difficult to induce broadly reactive antibodies by immunization. Here, we generate a plasmid DNA mix vaccine that encodes protein heterodimers with sixteen different …

[PDF] Early generation of a precursor CD8 T cell that can adapt to acute or chronic viral infection

Abstract Virus specific PD-1+ TCF-1+ TOX+ stem-like CD8+ T cells are essential for maintaining T cell responses during chronic infection and are also critical for PD-1 directed immunotherapy. In this study we have used the mouse model of chronic …

[HTML] Characterization of T-Cell receptor repertoire in immunoglobulin a nephropathy

Immunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by abnormal IgA deposition in glomerulus. Current diagnosis of IgAN still depends on renal biopsy, an invasive method that might increase the risk of clinical outcomes …

[PDF] Deciphering Membrane‐Protein Interactions and High‐Throughput Antigen Identification with Cell Doublets

Deciphering cellular interactions is essential to both understand the mechanisms underlying a broad range of human diseases, but also to manipulate therapies targeting these diseases. Here, the formation of cell doublets resulting from specific …

[HTML] Low dose post-transplant cyclophosphamide and sirolimus induce mixed chimerism with CTLA4-Ig or lymphocyte depletion in an MHC-mismatched murine …

Allogeneic hematopoietic cell transplantation (allo-HCT) offers a curative option for patients with certain non-malignant hematological diseases. High-dose post-transplant cyclophosphamide (PT-Cy)(200 mg/kg) and sirolimus (3 mg/kg),(HiC) …

[HTML] The intestinal microbiota modulates the transcriptional landscape of iNKT cells at steady-state and following antigen exposure

Abstract Invariant Natural Killer T (iNKT) cells are unconventional T cells that respond to microbe-derived glycolipid antigens. iNKT cells exert fast innate effector functions that regulate immune responses in a variety of contexts, including during …

[PDF] VisLingInstruct: Elevating Zero-Shot Learning in Multi-Modal Language Models with Autonomous Instruction Optimization

This paper presents VisLingInstruct, a novel approach to advancing Multi-Modal Language Models (MMLMs) in zero-shot learning. Current MMLMs show impressive zero-shot abilities in multi-modal tasks, but their performance depends heavily on the …

[PDF] RNAformer: A Simple Yet Effective Deep Learning Model for RNA Secondary Structure Prediction

Traditional RNA secondary structure prediction methods, based on dynamic programming, often fall short in accuracy. Recent advances in deep learning have aimed to address this, but may not adequately learn the biophysical model of RNA …

[HTML] Design and engineering of bispecific antibodies: insights and practical considerations

Bispecific antibodies (bsAbs) have attracted significant attention due to their dual binding activity, which permits simultaneous targeting of antigens and synergistic binding effects beyond what can be obtained even with combinations of conventional monospecific antibodies. Despite the tremendous therapeutic potential, the design and construction of bsAbs are often hampered by practical issues arising from the increased structural complexity as compared to conventional monospecific …

[HTML] Anfinsen Goes Neural: a Graphical Model for Conditional Antibody Design

Antibody design plays a pivotal role in advancing therapeutics. Although deep learning has made rapid progress in this field, existing methods make limited use of general protein knowledge and assume a graphical model (GM) that violates …

[PDF] A Cluster of Evolutionarily Recent KRAB Zinc Finger Proteins Protects Cancer Cells from Replicative Stress–Induced Inflammation

Heterochromatin loss and genetic instability enhance cancer progression by favoring clonal diversity, yet uncontrolled replicative stress leads to mitotic catastrophe and inflammatory responses that promote immune rejection. KRAB domain-containing …

Structure-Based Discovery of the SARS-CoV-2 Main Protease Noncovalent Inhibitors from Traditional Chinese Medicine

Traditional Chinese medicine (TCM) has been extensively employed for the treatment of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is demand for …

[HTML] Identification of SARS-CoV-2 Main Protease Inhibitors Using Chemical Similarity Analysis Combined with Machine Learning

SARS-CoV-2 Main Protease (Mpro) is an enzyme that cleaves viral polyproteins translated from the viral genome, which is critical for viral replication. Mpro is a target for anti-SARS-CoV-2 drug development. Herein, we performed a large-scale virtual …

Spotting T and B cell receptors

The antigen specificity of T and B lymphocytes is mediated by cognate antigen receptors on the cell surface. Although recent technical developments have enabled analyses of T and B cell receptors at the single-cell level, these methods have so far …

[PDF] CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes

Computational screening of naturally occurring proteins has the potential to identify efficient catalysts among the hundreds of millions of sequences that remain uncharacterized. Current experimental methods remain time, cost and labor intensive, limiting the number of enzymes they can reasonably screen. In this work, we propose a computational framework for in-silico enzyme screening. Through a contrastive objective, we train CLIPZyme to encode and align representations of …

[PDF] Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1: Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long-standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding …

[PDF] Learning the Language of Protein Structures

The AI revolution, which culminated recently in the release of GPT-4, not only impacted how we process natural language but the very same principles could readily be transferred to other sequential data such as protein sequences. Adapting these techniques to computational biology changed the way we process proteins today fundamentally. By simply feeding single amino acid sequences to large language models trained to parse and understand protein sequences, researchers …

[PDF] Scaffold-Lab: Critical Evaluation and Ranking of Protein Backbone Generation Methods in A Unified Framework

De novo protein design has undergone a rapid development in recent years, particularly in fix-backbone sequence design and backbone generation. The latter stands out as more challenging yet valuable, offering the ability to design novel …

[PDF] Genotype-histotype-phenotype correlations in hyperinsulinemic hypoglycemia

Hyperinsulinemic hypoglycemia (HH) of pancreatic origin includes congenital hyperinsulinism (CHI), insulinoma, insulinomatosis, and adult-onset non-insulinoma persistent hyperinsulinemic hypoglycemia syndrome (NI-PHHS). In this review, we describe the genotype-histotype-phenotype correlations in HH and their therapeutic implications.

[PDF] Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Donor lymphocyte infusion (DLI) is an established therapy for relapsed acute myeloid leukemia (AML) after hematopoietic stem cell transplant (HSCT), but response rates are poor (~ 20%). Interactions between leukemia and immune cells within the leukemia microenvironment may determine responsiveness to adoptive cellular immunotherapies. We hypothesized that systematic characterization of the leukemic marrow microenvironment over treatment course with DLI would define …

[PDF] Risks and potential benefits of adopti el transferred irus-specific T cells

Since multiple different T-cell receptor (TCR) sequences can bind to the same peptide-MHC combination and the number of TCR-sequences that can theoretically be generated even exceeds the number of T cells in a human body, the likelihood that many public identical (PUB-I) TCR-sequences frequently contribute to immune responses has been estimated to be low. Here, we quantitatively analyzed the TCR-repertoires of 190 purified virus-specific memory T-cell populations, directed against …

[HTML] Geometric parameters that affect the behavior of logic-gated CAR T cells

Clinical applications of CAR-T cells are limited by the scarcity of tumor-specific targets and are often afflicted with the same on-target/off-tumor toxicities that plague other cancer treatments. A new promising strategy to enforce tumor selectivity is the use of logic-gated, two-receptor systems. One well-described application is termed Tmod™, which originally utilized a blocking inhibitory receptor directed towards HLA-I target antigens to create a protective NOT gate. Here we show that the function of …

[HTML] 'Mix and Match'auto-assembly of glycosyltransferase domains delivers biocatalysts with improved substrate promiscuity

Glycosyltransferases (GT) catalyse the glycosylation of bioactive natural products, including peptides and proteins, flavonoids, sterols, and have been extensively used as biocatalysts to generate glycosides. However, the often narrow substrate specificity of wild-type GTs requires engineering strategies to expand it. The GT-B structural family is constituted by GTs that share a highly conserved tertiary structure, in which the sugar donor and acceptor substrates bind in dedicated domains. Here …

Local and Systemic Regulation of Mineralization: Role of Coupling Factors, Pyrophosphate, Polyphosphates, Vitamin D, Fetuin, Matrix Gla Protein, and Osteopontin

The chapter addresses mechanisms by which inhibitory factors regulate hard tissue deposition and explains how bone cells collectively control new bone formation at local and systemic levels. The concept is reviewed that cells of the basic multicellular unit (BMU) function cooperatively to foster bone turnover and mineralization. In addition to such coupling, several other factors are considered in the control of vertebrate mineralization, including pyrophosphate, polyphosphates, vitamin D …

Collagen-based Mineralization of Bones, Teeth, and Other Vertebrate Skeletal Tissues

The chapter considers the structure, organization, and function of two major collagen species, type I and X collagen, and their relationship to the mineralization process of vertebrate tissues. The importance of hole and overlap zones in the COLI molecule is discussed in terms of their chemistry and providing critical sites for nascent mineral formation in bone, dentin, cementum and, in some avians, tendon. At these intramolecular sites, the stereochemistry of charged amino acids comprising COLI is …

The Role of Non-collagenous Proteins and Other Matrix Molecules in Vertebrate Mineralization

The chapter examines the role of non-collagenous proteins, in particular SIBLINGs, evolved from a common gene ancestor, SPARC, in the mineralization of skeletal and dental tissues. Other important non-collagenous matrix components which are considered in the chapter include proteoglycans and SLRPs, thrombospondins, cartilage oligomeric matrix protein, osteocalcin, sclerostin, albumin and enamel matrix proteins among several others. A notable feature of many of these proteins is …

[HTML] Investigating the genetic makeup of the major histocompatibility complex (MHC) in the United Arab Emirates population through next-generation sequencing

The Human leukocyte antigen (HLA) molecules are central to immune response and have associations with the phenotypes of various diseases and induced drug toxicity. Further, the role of HLA molecules in presenting antigens significantly affects the …

[HTML] PB-LKS: a python package for predicting phage–bacteria interaction through local K-mer strategy

Bacteriophages can help the treatment of bacterial infections yet require in-silico models to deal with the great genetic diversity between phages and bacteria. Despite the tolerable prediction performance, the application scope of current approaches is …

[PDF] PINK1 is a target of T cell responses in Parkinson's disease

Parkinson's disease (PD) is associated with autoimmune T cells that recognize the protein alpha-synuclein in a subset of individuals. Multiple neuroantigens are targets of autoinflammatory T cells in classical central nervous system autoimmune diseases …

Structural vaccinology, molecular simulation and immune simulation approaches to design multi-epitopes vaccine against John Cunningham virus

Abstract The JCV (John Cunningham Virus) is known to cause progressive multifocal leukoencephalopathy, a condition that results in the formation of tumors. Symptoms of this condition such as sensory defects, cognitive dysfunction, muscle weakness …

[PDF] Empowering Federated Learning for Massive Models with NVIDIA FLARE

In the ever-evolving landscape of artificial intelligence (AI) and large language models (LLMs), handling and leveraging data effectively has become a critical challenge. Most state-of-the-art machine learning algorithms are data-centric. However, as the lifeblood of model performance, necessary data cannot always be centralized due to various factors such as privacy, regulation, geopolitics, copyright issues, and the sheer effort required to move vast datasets. In this paper, we explore …

[PDF] Graph Structure Inference with BAM: Introducing the Bilinear Attention Mechanism

In statistics and machine learning, detecting dependencies in datasets is a central challenge. We propose a novel neural network model for supervised graph structure learning, ie, the process of learning a mapping between observational data and their underlying dependence structure. The model is trained with variably shaped and coupled simulated input data and requires only a single forward pass through the trained network for inference. By leveraging structural equation models and …

[HTML] Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20+ chemistry in combination with dual unique molecular …

[HTML] Unraveling the Microscopic Mechanism of Molecular Ion Interaction with Monoclonal Antibodies: Impact on Protein Aggregation

Understanding and predicting protein aggregation represents one of the major challenges in accelerating the pharmaceutical development of protein therapeutics. In addition to maintaining the solution pH, buffers influence both monoclonal antibody (mAb) aggregation in solution and the aggregation mechanisms since the latter depend on the protein charge. Molecular-level insight is necessary to understand the relationship between the buffer–mAb interaction and mAb …

[HTML] NSF DARE—transforming modeling in neurorehabilitation: a patient-in-the-loop framework

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses …

Data mining antibody sequences for database searching in bottom-up proteomics

Mass spectrometry (MS)-based proteomics allows identifying and quantifying thousands of proteins but suffers from challenges when measuring human antibodies due to their vast variety. The mainly used bottom-up proteomics …

[HTML] Dissecting autoimmune encephalitis through the lens of intrathecal B cells

Autoimmune diseases result from attacks of the immune system against the body itself. It is the adaptive immune system with its T cells, B cells, and antibodies produced by effector B cells (ie, plasma cells) that is mainly engaged in autoimmune reactions. When the immune system attacks brain structures, autoimmune encephalitis may ensue. Autoimmune encephalitides represent a variety of severe conditions hallmarked by autoantibodies to antigens expressed either on the surface …

IDENTIFICATION OF SARS-COV-2 EPITOPES DISCRIMINATING COVID-19 INFECTION FROM CONTROL AND METHODS OF USE

The present invention is directed to peptides for use in the detection of antibodies against SARS-CoV-2, which are indicative of past SARS-CoV-2 infections. Additionally, assays and methods of distinguishing patients having had a prior …

[PDF] ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation

Protein function annotation is an important yet challenging task in biology. Recent deep learning advancements show significant potential for accurate function prediction by learning from protein sequences and structures. Nevertheless, these predictor-based methods often overlook the modeling of protein similarity, an idea commonly employed in traditional approaches using sequence or structure retrieval tools. To fill this gap, we first study the effect of inter-protein similarity modeling by …

[HTML] Protein function prediction as approximate semantic entailment

Abstract The Gene Ontology (GO) is a formal, axiomatic theory with over 100,000 axioms that describe the molecular functions, biological processes and cellular locations of proteins in three subontologies. Predicting the functions of proteins using the GO requires both learning and reasoning capabilities in order to maintain consistency and exploit the background knowledge in the GO. Many methods have been developed to automatically predict protein functions, but effectively exploiting …

Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration

The human brain is a highly complex neurological system that has been the subject of continuous exploration by scientists. With the help of modern neuroimaging techniques, there has been significant progress made in brain disorder analysis. There is an increasing interest about utilizing artificial intelligence techniques to improve the efficiency of disorder diagnosis in recent years. However, these methods rely only on neuroimaging data for disorder diagnosis and do not explore the …

[PDF] A Survey of Generative AI for De Novo Drug Design: New Frontiers in Molecule and Protein Generation

Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug design process, with various generative models already in widespread use. Generative models for de novo drug design, in particular, focus on the creation of novel biological compounds entirely from scratch, representing a promising future direction. Rapid development in the field, combined with the inherent complexity of the drug design process, creates a difficult landscape for new researchers to enter. In …

[PDF] 3D-based RNA function prediction tools in rnaglib

Understanding the connection between complex structural features of RNA and biological function is a fundamental challenge in evolutionary studies and in RNA design. However, building datasets of RNA 3D structures and making appropriate modeling choices remains time-consuming and lacks standardization. In this chapter, we describe the use of rnaglib, to train supervised and unsupervised machine learning-based function prediction models on datasets of RNA 3D structures.

[HTML] ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction

Efficient and accurate recognition of protein–DNA interactions is vital for understanding the molecular mechanisms of related biological processes and further guiding drug discovery. Although the current experimental protocols are the most precise way to determine protein–DNA binding sites, they tend to be labor-intensive and time-consuming. There is an immediate need to design efficient computational approaches for predicting DNA-binding sites. Here, we proposed ULDNA, a new …

[PDF] PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction

Compound-Protein Interaction (CPI) prediction aims to predict the pattern and strength of compound-protein interactions for rational drug discovery. Existing deep learning-based methods utilize only the single modality of protein sequences or …

[PDF] Antibody agonists trigger immune receptor signaling through local exclusion of receptor-type protein tyrosine phosphatases

Antibodies can block immune receptor engagement or trigger the receptor machinery to initiate signaling. We hypothesized that antibody agonists trigger signaling by sterically excluding large receptor-type protein tyrosine phosphatases (RPTPs) such …

[PDF] Restrained memory CD8+ T cell responses favors viral persistence and elevated IgG responses in patients with severe Long COVID.

During the COVID-19 pandemic it was widely described that certain individuals infected by SARS-CoV-2 experience persistent disease signs and symptoms, Long COVID, which in some cases is very severe with life changing consequences. To …

Mtb HLA-E tetramer sorted CD8+ T-cells have a diverse TCR repertoire

SUMMARY HLA-E molecules can present self and pathogen-derived peptides to both NK-cells and T-cells. T-cells that recognize HLA-E peptides via their T-cell receptor (TCR) are termed donor-unrestricted T-cells due to restricted allelic variation …

[PDF] Humoral and cellular immune responses against SARS-CoV-2 after third dose BNT162b2 following double-dose vaccination with BNT162b2 versus ChAdOx1 in …

Cancer patients display reduced humoral responses after double-dose COVID-19 vaccination while their cellular response is more comparable to that in healthy individuals. Recent studies demonstrated that a third vaccination dose boosts these …

[PDF] Predicting local structural properties from antibody sequence

Predicting local structural properties of antibodies at residual level is vital for detecting the presence of post-translational modifications (PTMs), which often induce structural change in the antibody, negatively impact its shelf-life and possibly lead to the loss of the therapeutic potential. In this work, we predict relative solvent accessibility (RSA) of individual residues. This property is, alongside with the type of amino acid in question, the key indicator for presence of methionine oxidations and …

[HTML] Recent Progress of Protein Tertiary Structure Prediction

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure …

[HTML] Stimulating T cell responses against patient-derived breast cancer cells with neoantigen peptide-loaded peripheral blood mononuclear cells

Breast cancer stands as a formidable global health challenge for women. While neoantigens exhibit efficacy in activating T cells specific to cancer and instigating anti-tumor immune responses, the accuracy of neoantigen prediction remains …

[PDF] Template‐specific optimization of NGS genotyping pipelines reveals allele‐specific variation in MHC gene expression

Using high‐throughput sequencing for precise genotyping of multi‐locus gene families, such as the major histocompatibility complex (MHC), remains challenging, due to the complexity of the data and difficulties in distinguishing genuine from …

[PDF] Optimization of anti-CD19 CAR T-cell production for treatment of patients with chronic lymphocytic leukemia

T cells expressing anti-CD19 chimeric antigen receptors (CARs) have activity against chronic lymphocytic leukemia (CLL), but complete response rates range from 18-29%, so improvement is needed. Peripheral blood mononuclear cells (PBMC) of CLL …

[HTML] Treatment of secondary CNS lymphoma using CD19-targeted chimeric antigen receptor (CAR) T cells

Background Aggressive B cell lymphoma with secondary central nervous system (CNS) involvement (SCNSL) carries a dismal prognosis. Chimeric antigen receptor (CAR) T cells (CAR-T) targeting CD19 have revolutionized the treatment for B cell …

[PDF] Disrupting CD38-driven T cell dysfunction restores sensitivity to cancer immunotherapy

A central problem in cancer immunotherapy with immune checkpoint blockade (ICB) is the development of resistance, which affects 50% of patients with metastatic melanoma1, 2. T cell exhaustion, resulting from chronic antigen exposure in the …

Interplay between B7–H3 and HLA class I in the clinical course of pancreatic ductal adenocarcinoma

Human leukocyte antigen (HLA) class I defects are associated with cancer progression. However, their prognostic significance is controversial and may be modulated by immune checkpoints. Here, we investigated whether the checkpoint B7 …

A breakthrough of immunoassay format for hapten: recent insights into noncompetitive immunoassays to detect small molecules

Immunoassay based on the antibodies specific for targets has advantages of high sensitivity, simplicity and low cost, therefore it has received more attention in recent years, especially for the rapid detection of small molecule chemicals present in foods, diagnostics and environments. However, limited by low molecular weight and only one antigenic determinant existed, immunoassays for these small molecule chemicals, namely hapten substances, were commonly performed in a competitive …

[HTML] Single-cell RNA sequencing reveals the dynamics and heterogeneity of lymph node immune cells during acute and chronic viral infections

Methods To explore the landscape of immune responses to acute and chronic viral infections, single-cell RNA sequencing (scRNA-seq), scTCR-seq and scBCR-seq were utilized to evaluate the longitudinal dynamics and heterogeneity of lymph node CD45+ immune cells in mouse models of acute (LCMV Armstrong) and chronic (LCMV clone 13) viral infections. Results In contrast with acute viral infection, chronic viral infection distinctly induced more robust NK cells and plasma cells at the early …

[PDF] Neural Network Design Patterns in Computer Vision IN2107 Seminar Report, Fall 2023/24

Machine learning with neural networks has become the prevalent view of visual learning in computer vision. Each year, the scientific community proposes dozens of new models as solutions for various visual tasks. To better assess these models and compare them for a better understanding of their advantages and disadvantages, a deeper understanding of the building blocks that constitute a neural network is needed. A similar problem is known in software engineering where progress in …

[PDF] Reply to comment on: Unexpectedly high prevalence of primary immune deficiency in fibromyalgia: serologic features and clinical correlates

Sir, I appreciate the opportunity to respond to Inan et al.(1)“Letter to the Editor” regarding our recent publication,“Unexpectedly high prevalence of primary immune deficiency in fibromyalgia: serologic features and clinical correlates”(2). Regrettably, this reply will emanate only from me as my long-time colleague and co-author, Dr. Earl F. Winter, died shortly before the article's formal publication. Inan et al. asks that we better identify the subtypes of primary immune deficiency (PID) seen in our FM …

[HTML] Revealing the significance of IL-2 and IL-5 in SARS-CoV-2-specific T-cell responses in kidney transplant recipients

Kidney transplant recipients (KTRs) are at an increased risk of severe COVID-19 due to compromised immune responses. Although vaccination is critical in preventing severe disease, KTRs have attenuated vaccination-induced immune responses due …

[PDF] Quantitative analysis of MHC class II peptide exchange reveals pivotal role of peptide association rate

MHC-II presents antigenic peptides to T helper cells, thus shaping adaptive immune responses. Peptide loading of MHC-II in endosomes is shaped by the susceptibility of the peptide-MHC-II complex to dissociation by the catalyst HLA-DM. For a given …

[PDF] Structure-and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody …

Rabbits produce robust antibody responses and have unique features in their antibody repertoire that make them an attractive alternative to rodents for in vivo discovery. However, the frequent occurrence of a non-canonical disulfide bond between complementarity-determining region (CDR) H1 (C35a) and CDRH2 (C50) is often seen as a liability for therapeutic antibody development, despite limited reports of its effect on antibody binding, function, and stability. Here, we describe the …

[HTML] Altered IgG4 Antibody Response to Repeated mRNA versus Recombinant Protein SARS-CoV-2 Vaccines

The four unique subclasses of human IgG, numbered in order of relative abundance, include IgG1, IgG2, IgG3, and IgG41, 2. IgG1 and IgG3 are the major contributors to rapid IgG responses to protein and membrane antigens, and are active in viral …

[HTML] Discovery of inhibitors of the SARS-CoV-2 S protein through computational drug repurposing

SARS-CoV-2 must bind its principal receptor, ACE2, on the target cell to initiate infection. This interaction is largely driven by the receptor binding domain (RBD) of the viral Spike (S) protein. Accordingly, antiviral compounds that can block …

[HTML] Additional booster doses in patients with chronic lymphocytic leukemia induce humoral and cellular immune responses to SARS‐CoV‐2 similar to natural infection …

To the Editor: In the past 3 years, SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) leading to coronavirus disease 2019 (COVID-19) has threatened the life of patients with chronic lymphocytic leukemia (CLL). Though declining over time …

Thermostability Enhancement of GH 62 α-l-Arabinofuranosidase by Directed Evolution and Rational Design

GH 62 arabinofuranosidases are known for their excellent specificity for arabinoxylan of agroindustrial residues and their synergism with endoxylanases and other hemicellulases. However, the low thermostability of some GH enzymes hampers …

[PDF] Host-Microbe Multiomic Profiling Reveals Age-Dependent COVID-19 Immunopathology

Age is a major risk factor for severe coronavirus disease-2019 (COVID-19), yet the mechanisms responsible for this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host and viral …

[HTML] Strategies for designing biocatalysts with new functions

The engineering of natural enzymes has led to the availability of a broad range of biocatalysts that can be used for the sustainable manufacturing of a variety of chemicals and pharmaceuticals. However, for many important chemical transformations there are no known enzymes that can serve as starting templates for biocatalyst development. These limitations have fuelled efforts to build entirely new catalytic sites into proteins in order to generate enzymes with functions beyond those …

Benzoic acid, 4-hydroxy-, methyl ester from Smilax zeylanica Linn emerges as a potent inhibitor of CD27/CD70 signaling pathway

Smilax zeylanica Linn is explored as a natural solution to inhibit the CD27/CD70 interaction crucial in T and B cell responses. This plant-based approach offers a cost-effective and promising drug candidate for overcoming challenges associated with anti-CD27 antibodies. The plants were macerated in an ethanol solution, and the cytotoxicity of crude extracts was determined using the MTT assay on Vero cell lines. Preliminary antiviral activity against the lentivirus plasmid was analyzed using …

Glycoengineered protein nanoparticles and uses thereof

Glycoengineered protein nanoparticles and uses thereof - University of Washington Login Sign up US Patents/Apps Other SEARCH TOOLS & RESOURCES Title: Glycoengineered protein nanoparticles and uses thereof Document Type and Number: United States Patent Application 20240042018 Kind Code: A1 Abstract: Polypeptides including the amino acid sequence of SEQ ID NO:78-80, substituted with one or more sequon, are provided, as are fusion proteins and nanoparticles formed from such …

[HTML] FMO-guided design of darunavir analogs as HIV-1 protease inhibitors

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment …

[HTML] Accelerating Antimicrobial Peptide Discovery for WHO Priority Pathogens through Predictive and Interpretable Machine Learning Models

The escalating menace of multidrug-resistant (MDR) pathogens necessitates a paradigm shift from conventional antibiotics to innovative alternatives. Antimicrobial peptides (AMPs) emerge as a compelling contender in this arena. Employing in silico methodologies, we can usher in a new era of AMP discovery, streamlining the identification process from vast candidate sequences, thereby optimizing laboratory screening expenditures. Here, we unveil cutting-edge machine learning (ML) models …

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge

Abstract The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS …

[PDF] Parathormon als potentielle Therapiestrategie der Odonto-Hypophosphatasie-Untersuchungen in einem dentogenen\(in-vitro\)-Modell

Hypophosphatasie (HPP) beschreibt eine seltene Erbkrankheit, die hauptsächlich durch heterozygote Mutationen im ALPL-Gen verursacht wird. Diese führen zu einer verminderten Aktivität der gewebeunspezifischen alkalischen Phosphatase (TNAP). Neben skelettalen Symptomen sind Zahnanomalien wie der vorzeitige Verlust von Milchzähnen ohne resorbierte Wurzel sowie eine gestörte Mineralisierung der Zahnhart-substanzen ein typisches Merkmal der HPP. Die zugrunde liegenden …

Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability

Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess …

[PDF] Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization

The promising zero-shot generalization of vision-language models such as CLIP has led to their adoption using prompt learning for numerous downstream tasks. Previous works have shown test-time prompt tuning using entropy minimization to adapt text …

FCMSTrans: Accurate Prediction of Disease-Associated nsSNPs by Utilizing Multiscale Convolution and Deep Feature Combination within a Transformer Framework

Nonsynonymous single-nucleotide polymorphisms (nsSNPs), implicated in over 6000 diseases, necessitate accurate prediction for expedited drug discovery and improved disease diagnosis. In this study, we propose FCMSTrans, a novel nsSNP predictor that innovatively combines the transformer framework and multiscale modules for comprehensive feature extraction. The distinctive attribute of FCMSTrans resides in a deep feature combination strategy. This strategy amalgamates …

Academic Surgery in the Era of Large Language Models: A Review

Importance This review aims to assess the benefits and risks of implementing large language model (LLM) solutions in an academic surgical setting. Observations The integration of LLMs and artificial intelligence (AI) into surgical practice has generated international attention with the emergence of OpenAI's ChatGPT and Google's Bard. From an administrative standpoint, LLMs have the potential to revolutionize academic practices by reducing administrative burdens and improving efficiency …

[PDF] Molecular and genetic effect of coding variants in human

Predicting the effect of missense variants is critically important in population and medical genetics. It is essential to interpret genetic variation in population screening and clinical diagnostic sequencing, to reach optimal statistical power of risk gene discovery in genetic studies of diseases and traits. A quantitative analysis of the fitness effect of all possible missense variants can provide a foundation for understanding how proteins evolve in humans and other species. In this thesis, I …

[HTML] CAR-Toner: an AI-driven approach for CAR tonic signaling prediction and optimization

Dear Editor, Tonic signaling of chimeric antigen receptors (CARs) plays a pivotal role in governing CAR-T cell fitness: inefficient tonic signaling results in poor CAR-T persistence, while excessive tonic signaling leads to CAR-T exhaustion. 1–3 Our previous work has elucidated that positively charged patches (PCPs) on the surface of the CAR antigenbinding domain facilitate CAR clustering, thereby triggering CAR tonic signals. To quantify these PCPs, which are indicative of CAR tonic signaling …

A randomized, non-comparative phase 2 study of neoadjuvant immune-checkpoint blockade in retroperitoneal dedifferentiated liposarcoma and extremity/truncal …

Based on the demonstrated clinical activity of immune-checkpoint blockade (ICB) in advanced dedifferentiated liposarcoma (DDLPS) and undifferentiated pleomorphic sarcoma (UPS), we conducted a randomized, non-comparative phase 2 trial (NCT03307616) of neoadjuvant nivolumab or nivolumab/ipilimumab in patients with resectable retroperitoneal DDLPS (n= 17) and extremity/truncal UPS (+ concurrent nivolumab/radiation therapy; n= 10). The primary end point of pathologic response …

[HTML] Gene-expression-based T-Cell-to-Stroma Enrichment (TSE) score predicts response to immune checkpoint inhibitors in urothelial cancer

Immune checkpoint inhibitors (ICI) improve overall survival in patients with metastatic urothelial cancer (mUC), but therapeutic success at the individual patient level varies significantly. Here we identify predictive markers of response, based on whole-genome DNA (n= 70) and RNA-sequencing (n= 41) of fresh metastatic biopsy samples, collected prior to treatment with pembrolizumab. We find that PD-L1 combined positivity score does not, whereas tumor mutational burden and APOBEC …

Designing proteins with language models

Protein language models learn from diverse sequences spanning the evolutionary tree and have proven to be powerful tools for sequence design, variant effect prediction and structure prediction. What are the foundations of protein language …

Data mining antibody sequences for database searching in bottom-up proteomics (preprint)

Mass spectrometry (MS)-based proteomics allows identifying and quantifying thousands of proteins but suffers from challenges when measuring human antibodies due to their vast variety. The mainly used bottom-up proteomics …

[PDF] Data mining antibody sequences for database searching in bottom-up proteomics

Mass spectrometry (MS)-based proteomics allows identifying and quantifying thousands of proteins but suffers from challenges when measuring human antibodies due to their vast variety. The mainly used bottom-up proteomics approaches rely on database searches that compare experimental values of peptides and their fragments to theoretical values derived from protein sequences in a database. While the human body can produce millions of distinct antibodies, the …

graphLambda: Fusion Graph Neural Networks for Binding Affinity Prediction

Predicting the binding affinity of protein–ligand complexes is crucial for computer-aided drug discovery (CADD) and the identification of potential drug candidates. The deep learning-based scoring functions have emerged as promising predictors of …

[PDF] Enhanced Directed Evolution in Mammalian Cells Yields a Hyperefficient Pyrrolysyl tRNA for Noncanonical Amino Acid Mutagenesis

Heterologous tRNAs used for noncanonical amino acid (ncAA) mutagenesis in mammalian cells typically show poor activity. We recently introduced a virus‐assisted directed evolution strategy (VADER) that can enrich improved tRNA mutants from …

Docking for molecules that bind in a symmetric stack to Alzheimer's disease tau fibrils with SymDOCK

Alzheimer's disease (AD) is a neurodegenerative disease characterized by the accumulation of neurofibrillary tangles of protein amyloids. One of the most prominent proteins that forms toxic amyloid deposits is tau, and tau has a paired …

[HTML] A Novel Heterozygous Variant in AICDA Impairs Ig Class Switching and Somatic Hypermutation in Human B Cells and is Associated with Autosomal Dominant HIGM2 …

B cells and their secreted antibodies are fundamental for host-defense against pathogens. The generation of high-affinity class switched antibodies results from both somatic hypermutation (SHM) of the immunoglobulin (Ig) variable region genes …

Publisher Correction: Adaptive immune receptor repertoire analysis

In the version of the article initially published, there were errors in Figs. 1–4. In Fig. 1, in the upper box,“CDR3” initially appeared as “CDR2” and “IGLJ (10)” read “IGLV (10)”. In the lower box,“TRBD” was missing from above “CDR3”. In Fig. 2a,“class …

E-pRSA: Embeddings improve the prediction of residue Relative Solvent Accessibility in protein sequence

Abstract Knowledge of the solvent accessibility of residues in a protein is essential for different applications, including the identification of interacting surfaces in protein-protein interactions and the characterization of variations. We describe E-pRSA, a …

[PDF] Decoding proteome functional information in model organisms using protein language models.

The gap between sequence information and experimental determination of function in proteins is currently unsolvable. The computational and automatic implementation of function prediction is not significantly improving function assignment, so there is a …

[PDF] ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction

Accurate prediction of compound-protein interaction (CPI) is of great importance for drug discovery. For creating generalizable CPI prediction deep learning (DL) models, the expansion of CPI data through experimental validation is crucial …

[HTML] A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics

In drug discovery, molecular dynamics (MD) simulation for protein-ligand binding provides a powerful tool for predicting binding affinities, estimating transport properties, and exploring pocket sites. There has been a long history of improving …

[PDF] Diversity of major histocompatibility complex (MHC) and natural killer cell receptor (NKR) genes and their interactions in domestic horses

The immunogenome is the part of the genome that underlies immune mechanisms and evolves under various selective pressures. Two complex regions of the immunogenome, major histocompatibility complex (MHC) and natural killer cell …

[PDF] Expanded specific T cells to hypomutated regions of the SARS-CoV-2 using mRNA electroporated antigen presenting cells.

The COVID-19 pandemic has caused about seven million deaths worldwide. Preventative vaccines have been developed including Spike gp mRNA-based vaccines that provide protection to immunocompetent patients. However, patients …

Psychological stress to ovalbumin peptide‐specific T‐cell receptor transgenic mice impairs the suppressive ability of type 1 regulatory T cell

Numerous diseases of the immune system can be traced back to the malfunctioning of the regulatory T cells. The aetiology is unclear. Psychological stress can cause disruption to the immune regulation. The synergistic effects of psychological stress …

[PDF] A Broad-Spectrum Multi-Antigen mRNA/LNP-Based Pan-Coronavirus Vaccine Induced Potent Cross-Protective Immunity Against Infection and Disease Caused by …

The first-generation Spike-alone-based COVID-19 vaccines have successfully contributed to reducing the risk of hospitalization, serious illness, and death caused by SARS-CoV-2 infections. However, waning immunity induced by these vaccines …

[PDF] Stem-like progenitor and terminally differentiated TFH-like CD4+ T cell exhaustion in the tumor microenvironment

Immune checkpoint inhibitors exert clinical efficacy against various types of cancer through reinvigoration of exhausted CD8+ T cells that attack cancer cells directly in the tumor microenvironment (TME). Using single-cell sequencing and mouse …

[PDF] Exploitation of CD3ζ to enhance TCR expression levels and antigen-specific T cell function

The expression levels of TCRs on the surface of human T cells define the avidity of TCR-HLA/peptide interactions. In this study, we have explored which components of the TCR-CD3 complex are involved in determining the surface expression levels of …

[PDF] Distinct sets of molecular characteristics define tumor-rejecting neoantigens

Challenges in identifying tumor-rejecting neoantigens limit the efficacy of neoantigen vaccines to treat cancers, including cutaneous squamous cell carcinoma (cSCC). A minority of human cSCC tumors shared neoantigens, supporting the need for …

[HTML] Unraveling the intricacies of host-pathogen interaction through single-cell genomics

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single …

[PDF] Defining human adaptive immune gene diversity

The lymphocytes (B and T cells) of the adaptive immune system undergo variable (V), diversity (D), and junctional (J) gene recombination, resulting in highly diverse antigen receptor repertoires capable of recognizing a wide variety of invading …

[PDF] Bridging Associative Memory and Probabilistic Modeling

Associative memory and probabilistic modeling are two fundamental topics in artificial intelligence. The first studies recurrent neural networks designed to denoise, complete and retrieve data, whereas the second studies learning and sampling from probability distributions. Based on the observation that associative memory's energy functions can be seen as probabilistic modeling's negative log likelihoods, we build a bridge between the two that enables useful flow of ideas in both directions. We …

[PDF] Ising on the Graph: Task-specific Graph Subsampling via the Ising Model

Reducing a graph while preserving its overall structure is an important problem with many applications. Typically, the reduction approaches either remove edges (sparsification) or merge nodes (coarsening) in an unsupervised way with no specific downstream task in mind. In this paper, we present an approach for subsampling graph structures using an Ising model defined on either the nodes or edges and learning the external magnetic field of the Ising model using a graph neural network …

[PDF] Shaping the helper T cell landscape: from naive to effectors

Functional programs selected by Th lymphocytes control the course of primary and any further secondary immune responses. The functional differentiation of Th subsets starts already in thymus during the process of MHC-II driven Th cells selection and continues upon the peripheral recognition of cognate peptide-MHC-II complexes (pMHC-II). Later, the acquired phenotype is preserved in memory antigen-specific Th clones, allowing for faster and phenotypically predetermined responses to secondary …

[HTML] AIRR-C IG Reference Sets: curated sets of immunoglobulin heavy and light chain germline genes

Introduction Analysis of an individual's immunoglobulin (IG) gene repertoire requires the use of high-quality germline gene reference sets. When sets only contain alleles supported by strong evidence, AIRR sequencing (AIRR-seq) data analysis is more accurate and studies of the evolution of IG genes, their allelic variants and the expressed immune repertoire is therefore facilitated. Methods The Adaptive Immune Receptor Repertoire Community (AIRR-C) IG Reference Sets have been developed …

Machine learning for functional protein design

Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and structure data have radically transformed computational protein design. New methods promise to escape the constraints of natural and laboratory evolution …

[HTML] Drug–target affinity prediction with extended graph learning-convolutional networks

High-performance computing plays a pivotal role in computer-aided drug design, a field that holds significant promise in pharmaceutical research. The prediction of drug–target affinity (DTA) is a crucial stage in this process, potentially accelerating drug development through rapid and extensive preliminary compound screening, while also minimizing resource utilization and costs. Recently, the incorporation of deep learning into DTA prediction and the enhancement of its accuracy have emerged as …

[PDF] MPEK: a multi-task learning based on pre-trained language model for predicting enzymatic reaction kinetic parameters

Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (k cat) and Michaelis constant (K m), key kinetic …

[PDF] Efficient and Effective Learning of Foundational Large Multi-Modal Models

The investigation of large multi-modal models (LMMs) has emerged as a focal point within the Deep Learning community, showcasing its prominence in contemporary research. LMMs exhibit the capacity to take data from diverse modalities, enabling them to execute a myriad of tasks by leveraging complementary information for enhanced predictive capabilities. The learning process of LMMs is bifurcated into two crucial stages: the computationally intensive pre-training stage, aimed at acquiring …

T cell help shapes B cell tolerance

T cell help is a crucial component of the normal humoral immune response, yet whether it promotes or restrains autoreactive B cell responses remains unclear. Here, we observe that autoreactive germinal centers require T cell help for their formation and persistence. Using retrogenic chimeras transduced with candidate TCRs, we demonstrate that a follicular T cell repertoire restricted to a single autoreactive TCR, but not a foreign antigen–specific TCR, is sufficient to initiate …

[HTML] Principles of digital sequencing using unique molecular identifiers

Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the …

Adenoid cystic carcinoma of the Bartholin's gland is underpinned by MYB-and MYBL1-rearrangements

Abstract Objective Adenoid cystic carcinoma (AdCC) of the Bartholin's gland (AdCC-BG) is a very rare gynecologic vulvar malignancy. AdCC-BGs are slow-growing but locally aggressive and are associated with high recurrence rates. Here we sought to characterize the molecular underpinning of AdCC-BGs. Methods AdCC-BGs (n= 6) were subjected to a combination of RNA-sequencing, targeted DNA-sequencing, reverse-transcription PCR, fluorescence in situ hybridization (FISH) and MYB …

[PDF] Initial Characterization of Canine T-cell Receptor Repertoires Using RNA-seq Data from Different Diseases and Tissues

The dog serves as a key translational model in cancer immunotherapy. Understanding the T cell receptor (TCR) repertoire is needed for various cancer immunotherapies. Compared to humans where> 300 million TCRs have been …

[PDF] Recurrent Fever of Unknown Origin and Unexplained Bacteremia in a Patient with a Novel 4.5 Mb Microdeletion in Xp11. 23-p11. 22

Fever of unknown origin (FUO) remains a formidable diagnostic challenge in the field of medicine. Numerous studies suggest an association between FUO and genetic factors, including chromosomal abnormalities. Here, we report a female patient with a 4.5 Mb Xp microdeletion, who presented with recurrent FUO, bacteremia, colitis, and hematochezia. To elucidate the underlying pathogenic mechanism, we employed a comprehensive approach involving single cell RNA sequencing, T cell …

[HTML] Identification of a new HLA-A* 0201-restricted cytotoxic T lymphocyte epitope from TC2N

Identification of cytotoxic T lymphocyte (CTL) epitopes from tumor related antigens is a promising approach for malignant tumor immunotherapy. TC2N, a recently identified tumor associated antigen from human glioblastoma, is regarded as a …

Safety and immunogenicity of an adjuvanted recombinant spike protein‐based severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) vaccine, SpikeVet™ …

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) can infect a broad range of animal species and has been associated with severe disease in some taxa. Few studies have evaluated optimal strategies to mitigate the risk to susceptible zoo …

[PDF] Analysis of B-cell receptor repertoire to evaluate immunogenicity of monovalent Omicron XBB. 1.5 mRNA vaccines

Monovalent Omicron XBB. 1.5 mRNA vaccines (BNT162b2 XBB. 1.5 and mRNA-1273.815) were newly developed and approved by the FDA in Autumn 2023 for preventing COVID-19. However, clinical efficacy for these vaccines is currently …

[HTML] Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions

This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have …

[PDF] Self-supervised Visualisation of Medical Image Datasets

Self-supervised learning methods based on data augmentations, such as SimCLR, BYOL, or DINO, allow obtaining semantically meaningful representations of image datasets and are widely used prior to supervised fine-tuning. A recent self …

In Vivo Stimulation of Therapeutic Antigen‐Specific T Cells in an Artificial Lymph Node Matrix

T cells are a critical mediator of antigen‐specific immune responses and are common targets for engineering anti‐tumor immunotherapy. Biomaterials scaffolds have previously been used to stimulate antigen presenting cells to elicit antigen …

Sparks of function by de novo protein design

Abstract Information in proteins flows from sequence to structure to function, with each step causally driven by the preceding one. Protein design is founded on inverting this process: specify a desired function, design a structure executing this function, and find a sequence that folds into this structure. This 'central dogma'underlies nearly all de novo protein-design efforts. Our ability to accomplish these tasks depends on our understanding of protein folding and function and our …

What does it take for an 'AlphaFold Moment'in functional protein engineering and design?

It has been three years since the ground-breaking announcement of AlphaFold2 during the CASP14 results session—a moment that sparked a profound transformation in protein research. Alpha-Fold2 was the first computational method to accurately predict protein structure from sequence, prompting extensive coverage by news media, which described it as a solution to a 50-year-old grand challenge in biology 1. CASP (Critical Assessment of protein Structure Prediction), often referred …

[PDF] EVALUATION OF THE NUTRITIVE QUALITIES OF RIPE AND UNRIPE PLANTAIN PEELS AS A POTENTIAL FEED INGREDIENT

The study examined the nutritional properties of plantain peels subjected to different processing methods which were air-drying, sun-drying, and fermentation. Each method was replicated thrice. Experimental samples were subjected to proximate analysis, phytochemical evaluation, and functional properties determination. Data collected were compared using analysis of variance and significant differences between the means were determined using Duncan's Multiple Range Test. The …

[PDF] Liver cancer detection using Artificial Intelligence

A noticeable increase in statistics of liver cancer in Egypt and all over the world. Therefore, using Artificial Intelligence (AI) to increase the detection accuracy and minimize human errors during manual classification of liver images. Where the manual classification of liver Computed Tomography (CT) scan images require a very great effort and time-consuming tasks. This study aims to improve a high-performance computer detection system. The proposed model used to detect liver …

[PDF] Stable and Accurate Atomistic Simulations of Flexible Molecules using Conformationally Generalisable Machine Learned Potentials

Computational simulation methods based on machine learned potentials (MLPs) promise to revolutionise shape prediction of flexible molecules in solution, but their widespread adoption has been limited by the way in which training data is generated. Here, we present an approach which allows the key conformational degrees of freedom to be properly represented in reference molecular datasets. MLPs trained on these datasets using a global descriptor scheme are generalisable …

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have …

[HTML] Positive epistasis drives clavulanic acid resistance in double mutant libraries of BlaC β-lactamase

Phenotypic effects of mutations are highly dependent on the genetic backgrounds in which they occur, due to epistatic effects. To test how easily the loss of enzyme activity can be compensated for, we screen mutant libraries of BlaC, a β-lactamase from Mycobacterium tuberculosis, for fitness in the presence of carbenicillin and the inhibitor clavulanic acid. Using a semi-rational approach and deep sequencing, we prepare four double-site saturation libraries and determine the relative fitness effect …

[HTML] De novo prediction of RNA 3D structures with deep generative models

We present a Deep Learning approach to predict 3D folding structures of RNAs from their nucleic acid sequence. Our approach combines an autoregressive Deep Generative Model, Monte Carlo Tree Search, and a score model to find and rank the most likely folding structures for a given RNA sequence. We show that RNA de novo structure prediction by deep learning is possible at atom resolution, despite the low number of experimentally measured structures that can be used for training. We …

Dual coiled-coil protein domain mimic and drug delivery vehicle for SARS-CoV-2

ABSTRACT SARS-CoV-2 has emerged as a strong target for the development of protein domain mimics (PDMs) as it relies on the helical protein-protein interaction (PPI) between the N-terminal α-helix of ACE2, ACE BINDER, with the SARS-CoV-2 receptor binding domain (RBD). We have recently developed an ACE BINDER-based multivalent assembled protein (ACE-MAP) that relies on fusion of a binding domain to the cartilage oligomeric matrix protein coiled-coil domain (COMPcc) by …

[PDF] Adaptation of turnip mosaic virus to Arabidopsis thaliana involves rewiring of VPg-host proteome interactions

The outcome of a viral infection depends on a complex interplay between the host physiology and the virus, mediated through numerous protein-protein interactions. In a previous study we used high-throughput yeast two-hybrid (HT-Y2H) to identify proteins in Arabidopsis thaliana that bind to the proteins encoded by the turnip mosaic virus (TuMV) genome. Furthermore, after experimental evolution of TuMV lineages in plants with mutations in defense-related or proviral genes, most …

[PDF] Epitope-specific IgE, IgG4, and IgG1 antibodies for clinical phenotyping of IgE-mediated wheat allergy

Methods Children and adolescents (n= 109) enrolled in Bangkok and New York underwent Oral Food Challenges to diagnose wheat allergy. Seventy-nine peptides were synthesized from 5 proteins, including ω-5-g, alpha/beta-gliadin (a/bg), gamma …

[HTML] Cediranib enhances the transcription of MHC-I by upregulating IRF-1

Abstract Diminished or lost Major Histocompatibility Complex class I (MHC-I) expression is frequently observed in tumors, which obstructs the immune recognition of tumor cells by cytotoxic T cells. Restoring MHC-I expression by promoting its …

Cellular reprogramming by protein degradation: The next frontier in cancer immunotherapy

In this issue of Cell Chemical Biology, Lane et al. 1 introduce a transgene-based system to express fusion proteins that recruit transcription factors to E3 ligases. This approach expands the target repertoire for engineered cell therapies as exemplified …

[HTML] Effects of immunogenic cell death-inducing chemotherapeutics on the immune cell activation and tertiary lymphoid structure formation in melanoma

Background The infiltration and activation of immune cells in the tumor microenvironment (TIME) affect the prognosis of patients with cancer. Tertiary lymphoid structure (TLS) formation favors tumour-infiltrating-lymphocyte (TIL) …

[PDF] Cancer immunotherapies transition endothelial cells into high-endothelial venules that generate TCF1+ T lymphocyte niches through a feed-forward loop

The lack of T-cell infiltrates is a major obstacle to effective immunotherapy in cancer. Conversely, the formation of tumor-associated tertiary-lymphoid-like structures (TA-TLLS), which are the local site of humoral and cellular immune responses against …

Neutralizing antibody and CD8+ T cell responses following BA. 4/5 bivalent COVID-19 booster vaccination in adults with and without prior exposure to SARS-CoV-2

As severe acute respiratory coronavirus 2 (SARS-CoV-2) variants continue to emerge, it is important to characterize immune responses against variants which can inform on protection efficacies following booster vaccination. In this study …

AMGCN: adaptive multigraph convolutional networks for traffic speed forecasting

Traffic speed forecasting is a crucial aspect of traffic management that requires an accurate multi spatiotemporal time series forecasting technique. Previous studies typically employ graph neural network (GNN)-based methods for this task, but they are limited by their focus on spatial dependence based on real geographic distance in road networks. These structures are often inadequate for accurately describing spatial dependencies in the real world. Recently, multigraph neural networks …

[PDF] Learning to Design and Engineer Proteins from Evolution, 3D Structures, and Experiments

Naturally occurring proteins serve many crucial functions in maintaining life. They can be enzymes to catalyze essential chemical reactions, hormones to regulate various physiological processes, transporters to carry molecules across cell membranes, as well as structural components to support the shape of cells and tissues. Evolution creates new proteins primarily through the stochastic, generative mechanisms of mutation and recombination, coupled with the screening filter of …

nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework (preprint)

ABSTRACT MotivationAdaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases,(auto) immune diseases, and …

[HTML] DiscoTope-3.0: improved B-cell epitope prediction using inverse folding latent representations

Accurate computational identification of B-cell epitopes is crucial for the development of vaccines, therapies, and diagnostic tools. However, current structure-based prediction methods face limitations due to the dependency on experimentally solved structures. Here, we introduce DiscoTope-3.0, a markedly improved B-cell epitope prediction tool that innovatively employs inverse folding structure representations and a positive-unlabelled learning strategy, and is adapted for both solved and …

[PDF] De novo prediction of antibody variable domains from antigen primary structure with deep learning approaches

The COVID-19 pandemic incited an unprecedented demand for novel drug therapeutics, and in doing so, highlighted the shortcomings of therapeutic monoclonal antibody (therapeutic mAb) development pipelines, namely, the time …

[PDF] On the importance of assessing topological convergence in Bayesian phylogenetic inference

Modern phylogenetics research is often performed within a Bayesian framework, using sampling algorithms such as Markov chain Monte Carlo (MCMC) to approximate the posterior distribution. These algorithms require careful evaluation of …

[PDF] Generative AI for Controllable Protein Sequence Design: A Survey

The design of novel protein sequences with targeted functionalities underpins a central theme in protein engineering, impacting diverse fields such as drug discovery and enzymatic engineering. However, navigating this vast combinatorial search space remains a severe challenge due to time and financial constraints. This scenario is rapidly evolving as the transformative advancements in AI, particularly in the realm of generative models and optimization algorithms, have been propelling …

[HTML] Recent advances in generative biology for biotherapeutic discovery

Generative biology combines artificial intelligence (AI), advanced life sciences technologies, and automation to revolutionize the process of designing novel biomolecules with prescribed properties, giving drug discoverers the ability to escape the limitations of biology during the design of next-generation protein therapeutics. Significant hurdles remain, namely:(i) the inherently complex nature of drug discovery,(ii) the bewildering number of promising computational and …

The regulation and differentiation of regulatory T cells and their dysfunction in autoimmune diseases

The discovery of FOXP3+ regulatory T (Treg) cells as a distinct cell lineage with a central role in regulating immune responses provided a deeper understanding of self-tolerance. The transcription factor FOXP3 serves a key role in Treg cell lineage determination and maintenance, but is not sufficient to enable the full potential of Treg cell suppression, indicating that other factors orchestrate the fine-tuning of Treg cell function. Moreover, FOXP3-independent mechanisms have recently been shown …

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our …

[HTML] Impaired IgM Memory B Cell Function Is Common in Coeliac Disease but Conjugate Pneumococcal Vaccination Induces Robust Protective Immunity

Coeliac disease (CD) is associated with hyposplenism, an acquired impairment of spleen function associated with reduced IgM memory B cells and increased susceptibility to serious pneumococcal infection. Little is known about the immune …

[PDF] The release of host-derived antibodies bound to the varian t surface glycoprotein (VSG) of Trypanosoma brucei cannot be explained by pH-dependent conformational …

Background Trypanosoma brucei is a protozoan parasite that evades the mammalian host's adaptive immune response by antigenic variation of the highly immunogenic variant surface glycoprotein (VSG). VSGs form a dense surface coat that is constantly recycled through the endosomal system. Bound antibodies are separated in the endosome from the VSG and destroyed in the lysosome. For VSGs it has been hypothesized that pH-dependent structural changes of the VSG could …

[HTML] SARS-CoV-2 spike-reactive naïve B cells and pre-existing memory B cells contribute to antibody responses in unexposed individuals after vaccination

Introduction Since December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have …

[PDF] Impact of antibody architecture and paratope valency on effector functions of bispecific NKp30 x EGFR natural killer cell engagers

Natural killer (NK) cells emerged as a promising effector population that can be harnessed for anti-tumor therapy. In this work, we constructed NK cell engagers (NKCEs) based on NKp30-targeting single domain antibodies (sdAbs) that redirect …

AlphaFold2 Predicts Whether Proteins Interact Amidst Confounding Structural Compatibility

Predicting whether two proteins physically interact is one of the holy grails of computational biology, galvanized by rapid advancements in deep learning. AlphaFold2, although not developed with this goal, is promising in this respect. Here …

Leveraging Cross-Linking Mass Spectrometry for Modeling Antibody–Antigen Complexes

Elucidating antibody–antigen complexes at the atomic level is of utmost interest for understanding immune responses and designing better therapies. Cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for mapping protein …

[HTML] The Role of Force Fields and Water Models in Protein Folding and Unfolding Dynamics

Protein folding is a fascinating, not fully understood phenomenon in biology. Molecular dynamics (MD) simulations are an invaluable tool to study conformational changes in atomistic detail, including folding and unfolding processes of proteins. However, the accuracy of the conformational ensembles derived from MD simulations inevitably relies on the quality of the underlying force field in combination with the respective water model. Here, we investigate protein folding, unfolding, and …

Unlocking Precision Docking for Metalloproteins

Metalloproteins play a fundamental role in molecular biology, contributing to various biological processes. However, the discovery of high-affinity ligands targeting metalloproteins has been delayed due, in part, to a lack of suitable tools and data …

Protein language models-assisted optimization of a uracil-N-glycosylase variant enables programmable T-to-G and T-to-C base editing

Current base editors (BEs) use DNA deaminases, including cytidine deaminase in cytidine BE (CBE) or adenine deaminase in adenine BE (ABE), to facilitate transition nucleotide substitutions. Combining CBE or ABE with glycosylase enzymes can induce limited transversion mutations. Nonetheless, a critical demand remains for BEs capable of generating alternative mutation types, such as T> G corrections. In this study, we leveraged pre-trained protein language models to optimize a uracil-N …

AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles, and Binding Energetics of the SARS-CoV-2 Omicron BA. 2.86 Spike Protein with …

The latest wave of SARS-CoV-2 Omicron variants displayed a growth advantage and increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and …

[HTML] Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges

Machine learning (ML), particularly deep learning (DL), has made rapid and substantial progress in synthetic biology in recent years. Biotechnological applications of biosystems, including pathways, enzymes, and whole cells, are being probed frequently with time. The intricacy and interconnectedness of biosystems make it challenging to design them with the desired properties. ML and DL have a synergy with synthetic biology. Synthetic biology can be employed to produce large …

[PDF] Optimizing Warfarin Dosing Using Contextual Bandit: An Offline Policy Learning and Evaluation Method

Warfarin, an anticoagulant medication, is formulated to prevent and address conditions associated with abnormal blood clotting, making it one of the most prescribed drugs globally. However, determining the suitable dosage remains challenging due to individual response variations, and prescribing an incorrect dosage may lead to severe consequences. Contextual bandit and reinforcement learning have shown promise in addressing this issue. Given the wide availability of …

Integrated analysis of single-cell and bulk RNA sequencing data reveals the association between hypoxic tumor cells and exhausted T cells in predicting immune …

Continuous stimulation of tumor neoantigens and various cytokines in the tumor microenvironment leads to T cell dysfunction, but the specific mechanisms by which these key factors are distributed among different cell subpopulations and how they …

[PDF] Stereotypic T cell receptor clonotypes in the thymus and peripheral blood of Myasthenia gravis patients

Myasthenia Gravis (MG) patients with anti-acetylcholine receptor (AChR) antibodies frequently show hyperplastic thymi with ectopic germinal centers, where autoreactive B cells proliferate with the aid of T cells. In this study, thymus and peripheral blood …

Author Correction: Cross-phyla protein annotation by structural prediction and alignment

Author Correction: Cross-phyla protein annotation by structural prediction and alignment | Genome Biology Skip to main content SpringerLink Account Menu Find a journal Publish with us Track your research Search Cart 1.Home 2.Genome …

[HTML] From Code to Cure: The Impact of Artificial Intelligence in Biomedical Applications

Artificial intelligence (AI), a branch of computer science, involves developing intelligent computer programs to mimic human intelligence and automate various processes. AI has various applications in healthcare, robotics, speech recognition, data analytics, biomedical research and in many more fields. Machine learning (ML) and deep learning (DL) are subsets of AI that can be utilized to analyze vast biological datasets, and play a pivotal role in identifying complex genetic patterns …

[PDF] A Picture Guessing Game to Improve English Skill at Sdn Baruh 1

One of the difficulties students often experience in learning English is reading and speaking. Reading and speaking are activities that occur every day both at school, at home or in public places. Students in Indonesia experience difficulties when understanding reading and speaking English, mainly due to a lack of practice, the small vocabulary they have, and the lack of knowledge about appropriate English reading comprehension strategies. To improve the English language skills of …

[PDF] Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective

In long-term time series forecasting (LTSF) tasks, existing deep learning models overlook the crucial characteristic that discrete time series originate from underlying continuous dynamic systems, resulting in a lack of extrapolation and evolution capabilities. Recognizing the chaotic nature of real-world data, our model,\textbf {\textit {Attraos}}, incorporates chaos theory into LTSF, perceiving real-world time series as observations from unknown high-dimensional chaotic dynamic systems …

[PDF] Associative Memories in the Feature Space

An autoassociative memory model is a function that, given a set of data points, takes as input an arbitrary vector and outputs the most similar data point from the memorized set. However, popular memory models fail to retrieve images even when the corruption is mild and easy to detect for a human evaluator. This is because similarities are evaluated in the raw pixel space, which does not contain any semantic information about the images. This problem can be easily solved by …

[PDF] A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models

Zero-shot link prediction (ZSLP) on knowledge graphs aims at automatically identifying relations between given entities. Existing methods primarily employ auxiliary information to predict tail entity given head entity and its relation, yet face …

Quantification and Prediction of T-cell Cross-reactivity Through Experimental and Computational Methods

Frontiers | Editorial: Quantification and Prediction of T-cell Cross-reactivity Through Experimental and Computational Methods Skip to main content Top bar navigation Frontiers in Immunology About us About us Who we are Mission Values History …

[PDF] Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Household Transmission during the Omicron Era in Massachusetts: A Prospective, Case …

Background Households are a major setting for SARS-CoV-2 infections, but there remains a lack of knowledge regarding the dynamics of viral transmission, particularly in the setting of widespread pre-existing SARS-CoV-2 immunity and …

[PDF] Delineating the Effective Use of Self-Supervised Learning in Single-Cell Genomics

Self-supervised learning (SSL) has emerged as a powerful method for extracting meaningful representations from vast, unlabeled datasets, already transforming computer vision and natural language processing. Similarly, in single-cell genomics …

[HTML] Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations

The protein dynamics are common and important for their biological functions and properties, the study of which usually involves time-consuming molecular dynamics (MD) simulations in silico. Recently, generative models has been leveraged as a …

[PDF] CoSpred: Machine learning workflow to predict tandem mass spectrum in proteomics

In mass spectrometry-based proteomics, the identification and quantification of peptides and proteins is usually done using database search algorithms or spectral library matching. The use of deep learning algorithms can help improve the …

Protein structure accuracy estimation using geometry‐complete perceptron networks

Estimating the accuracy of protein structural models is a critical task in protein bioinformatics. The need for robust methods in the estimation of protein model accuracy (EMA) is prevalent in the field of protein structure prediction, where …

System Biology and Protein Structure Prediction by Computer

In the twenty-first century, whole-genome sequencing has become possible, and the amino acid sequence of all proteins can be revealed by genome sequences. If the functional dynamics of proteins can be written in equations, it should be possible to …

[HTML] Converging and evolving immuno-genomic routes toward immune escape in breast cancer

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from …

[PDF] Exploring The Interplay Between Scoring Functions and Physico-chemical Properties in Antibody-antigen Docking

The advent of antibody therapy has brought about a change in the treatment of diseases. The efficacy of antibody modeling relies on the intricate atomic interactions between antibodies and antigens. Traditional methods for determining antibody structures, such as X-ray crystallography, are costly and time-consuming. Computational docking offers a faster and more cost-effective approach to obtaining complex antibody and antigen complexes even in challenging scenarios. Rosetta, a …

[HTML] Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Vaccine Response in Adults with Predominantly Antibody Deficiency

Background Patients with predominantly antibody deficiency (PAD) have lower anti-SARS-CoV-2 spike antibody levels after initial two-dose SARS-CoV-2 vaccination as compared to healthy controls; however, anti-spike antibody responses and …

Immunological imprinting shapes the specificity of human antibody responses against SARS-CoV-2 variants (preprint)

The spike glycoprotein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to accumulate substitutions, leading to breakthrough infections of vaccinated individuals and prompting the development of updated booster vaccines …

[PDF] Full-Atom Peptide Design with Geometric Latent Diffusion

Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable. Most existing methods are either inefficient or only concerned with the target-agnostic design of 1D sequences. In this paper, we propose a generative model for full-atom\textbf {Pep} tide design with\textbf {G} eometric\textbf {LA} tent\textbf {D} iffusion (PepGLAD). We first collect a dataset consisting of both 1D sequences and 3D structures from Protein …

The interaction between particles and vascular endothelium in blood flow

Particle-based drug delivery systems have shown promising application potential to treat human diseases; however, an incomplete understanding of their interactions with vascular endothelium in blood flow prevents their inclusion into mainstream clinical applications. The flow behaviors of nano/micro-sized particles in the blood are disturbed by many external/internal factors, including blood constituents, particle properties, and endothelium bioactivities, affecting the fate of particles in vivo and …

Coeliac disease: the paradox of diagnosing a food hypersensitivity disorder with autoantibodies

Serum antibodies to the autoantigen transglutaminase 2 (TG2) are increasingly harnessed to diagnose coeliac disease. Diagnostic guidelines for children give recommendation for a no-biopsy-based diagnosis through detection of high amounts of IgA anti-TG2 antibodies in serum with confirmation of positivity in a separate blood sample by characteristic autoantibody-staining of tissue. While measurement of IgA anti-TG2 also is important in the diagnostic workup of adults, the adult guidelines still …

[PDF] CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory

Large Language Models (LLMs) struggle to handle long input sequences due to high memory and runtime costs. Memory-augmented models have emerged as a promising solution to this problem, but current methods are hindered by limited memory capacity and require costly re-training to integrate with a new LLM. In this work, we introduce an associative memory module which can be coupled to any pre-trained (frozen) attention-based LLM without re-training, enabling it to handle …

[HTML] mRNA-1273 vaccinated inflammatory bowel disease patients receiving TNF inhibitors develop broad and robust SARS-CoV-2-specific CD8+ T cell responses

Abstract SARS-CoV-2-specific CD8+ T cells recognize conserved viral peptides and in the absence of cross-reactive antibodies form an important line of protection against emerging viral variants as they ameliorate disease severity. SARS-CoV-2 …

TCR-like antibody and GITR signaling lead to effective CAR-T against solid tumor

Chimeric antigen receptor T cell (CAR-T) therapy is one of the great success stories of cellular immunotherapy for blood cancers (eg, B cell leukemias, lymphomas, and multiple myeloma) but has remained ineffective for solid tumors. The failure of CAR-T …

Interpretable Prediction of SARS-CoV-2 Epitope-specific TCR Recognition Using a Pre-Trained Protein Language Model.

The emergence of the novel coronavirus, designated as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has posed a significant threat to public health worldwide. There has been progress in reducing hospitalizations and deaths …

[HTML] Diverse cytomegalovirus US11 antagonism and MHC-A evasion strategies reveal a tit-for-tat coevolutionary arms race in hominids

Recurrent, ancient arms races between viruses and hosts have shaped both host immunological defense strategies as well as viral countermeasures. One such battle is waged by the glycoprotein US11 encoded by the persisting human …

[PDF] Enhancing Protein–Ligand Binding Affinity Predictions Using Neural Network Potentials

This letter gives results on improving protein–ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural network potential and molecular mechanics methodology (NNP/MM) …

[HTML] Text-Guided Molecule Generation with Diffusion Language Model

Text-guided molecule generation is a task where molecules are generated to match specific textual descriptions. Recently, most existing SMILES-based molecule generation methods rely on an autoregressive architecture. In this work, we propose …

[HTML] PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction

Compound-Protein Interaction (CPI) prediction aims to predict the pattern and strength of compound-protein interactions for rational drug discovery. Existing deep learning-based methods utilize only the single modality of protein sequences or …

[PDF] Type‐II IFN inhibits SARS‐CoV‐2 replication in human lung epithelial cells and ex vivo human lung tissues through indoleamine 2, 3‐dioxygenase‐mediated …

Interferons (IFNs) are critical for immune defense against pathogens. While type‐I and‐III IFNs have been reported to inhibit SARS‐CoV‐2 replication, the antiviral effect and mechanism of type‐II IFN against SARS‐CoV‐2 remain largely unknown …

[HTML] Immunogenicity and protective efficacy of a co-formulated two-in-one inactivated whole virus particle COVID-19/influenza vaccine

Due to the synchronous circulation of seasonal influenza viruses and severe acute respiratory coronavirus 2 (SARS-CoV-2) which causes coronavirus disease 2019 (COVID-19), there is need for routine vaccination for both COVID-19 and influenza to …

An In silico Study on B-cell Epitope Mapping of Acinetobacter baumannii Outer Membrane Protein K.

Background Acinetobacter baumannii is one of the main causes of nosocomial infections. No vaccine has yet been licensed for use in humans, and efforts are still ongoing. Objective In the present study, we have predicted the B-cell epitopes of A …

[PDF] Artificial Intelligence with Great Potential in Medical Informatics: A Brief Review

In the 1950s and 1960s, in molecular biology, information technology was mainly applied to the molecular evolution of proteins and DNA, and later expanded to multiple fields such as sequence alignment, protein structure prediction, and gene splicing. Entering the 21st century, the completion of the Human Genome Project marks the arrival of the era of biomedical big data, providing a large amount of data for the application of artificial intelligence in this field. Especially in recent years, the …

[PDF] Nuclear pore dysfunction and disease: a complex opportunity

The separation of genetic material from bulk cytoplasm has enabled the evolution of increasingly complex organisms, allowing for the development of sophisticated forms of life. However, this complexity has created new categories of dysfunction, including those related to the movement of material between cellular compartments. In eukaryotic cells, nucleocytoplasmic trafficking is a fundamental biological process, and cumulative disruptions to nuclear integrity and nucleocytoplasmic transport are …

[PDF] Protein crystallography for computation-supported enzyme redesign

The main focus of the thesis is the application of structural analysis as validation method of computational protein design strategies. The thesis investigates the structure-function relationships of enzymes, and x-ray crystallography is used to critically validate theoretically designed mutations aimed to improve enzyme's stability or catalytic properties.

[HTML] Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations

We introduce a computational approach for the design of target-specific peptides. Our method integrates a Gated Recurrent Unit-based Variational Autoencoder with Rosetta FlexPepDock for peptide sequence generation and binding affinity assessment. Subsequently, molecular dynamics simulations are employed to narrow down the selection of peptides for experimental assays. We apply this computational strategy to design peptide inhibitors that specifically target β-catenin and NF-κB …

[HTML] Emerging Landscape of Supercharged Proteins and Peptides for Drug Delivery

Although groundbreaking biotechnological techniques such as gene editing have significantly progressed, the effective and targeted transport of therapeutic agents into host cells remains a major obstacle to the development of biotherapeutics. Confronting the unique challenge posed by large macromolecules such as proteins, peptides, and nucleic acids adds complexity to this issue. Recent findings reveal that the supercharging of proteins and peptides not only enables control over critical …

Research progress of LSD1-based dual-target agents for cancer therapy

Abstract Lysine-specific demethylase 1 (LSD1) is a histone lysine demethylase that is significantly overexpressed or dysregulated in different cancers and plays important roles in cell growth, invasion, migration, immune escape, angiogenesis, gene regulation, and transcription. Therefore, it is a superb target for the discovery of novel antitumor agents. However, because of their innate and acquired resistance and low selectivity, LSD1 inhibitors are associated with limited therapeutic efficacy …

[HTML] Towards bone regeneration: Understanding the nucleating ability of proline-rich peptides in biomineralisation

Obtaining rapid mineralisation is a challenge in current bone graft materials, which has been attributed to the difficulty of guiding the biological processes towards osteogenesis. Amelogenin, a key protein in enamel formation, inspired the design of two intrinsically disordered peptides (P2 and P6) that enhance in vivo bone formation, but the process is not fully understood. In this study, we have elucidated the mechanism by which these peptides induce improved mineralisation. Our …

[PDF] HLA-A* 03: 01 is associated with visceral leishmaniasis development in people living with HIV in Ethiopia

Human immunodeficiency virus (HIV) co-infection is a major challenge for visceral leishmaniasis (VL) control, particularly in Ethiopia where the incidence of both pathogens is high. VL-HIV often leads to high rates of antileishmanial treatment …

Population Diversity at the Single-Cell Level

Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and …

[HTML] Deep-Learning Uncovers certain CCM Isoforms as Transcription Factors

Background: Cerebral Cavernous Malformations (CCMs) are brain vascular abnormalities associated with an increased risk of hemorrhagic strokes. Familial CCMs result from autosomal dominant inheritance involving three genes: KRIT1 (CCM1), MGC4607 (CCM2), and PDCD10 (CCM3). CCM1 and CCM3 form the CCM Signal Complex (CSC) by binding to CCM2. Both CCM1 and CCM2 exhibit cellular heterogeneity through multiple alternative spliced isoforms, where exons from the …

[PDF] FastFold: Optimizing AlphaFold Training and Inference on GPU Clusters

Protein structure prediction helps to understand gene translation and protein function, which is of growing interest and importance in structural biology. The AlphaFold model, which used transformer architecture to achieve atomic-level accuracy in protein structure prediction, was a significant breakthrough. However, training and inference of AlphaFold model are challenging due to its high computation and memory cost. In this work, we present FastFold, an efficient …

[PDF] Interpretable Atomistic Prediction and Functional Analysis of Conformational Ensembles and Allosteric States in Protein Kinases Using AlphaFold2 Adaptation with …

The groundbreaking achievements of AlphaFold2 (AF2) approaches in protein structure modeling marked a transformative era in structural biology. Despite the success of AF2 tools in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and fold-switching systems. The recent NMR-based structural determination of the unbound ABL kinase in the active state and two inactive low-populated …

[HTML] CD4+ T cells produce IFN-I to license cDC1s for induction of cytotoxic T-cell activity in human tumors

CD4+ T cells can" help” or" license” conventional type 1 dendritic cells (cDC1s) to induce CD8+ cytotoxic T lymphocyte (CTL) anticancer responses, as proven in mouse models. We recently identified cDC1s with a transcriptomic imprint of CD4+ T …

[PDF] Responses of Helper T Cell Subsets at Diagnosis and After Discharge in Patients with Non-Severe COVID-19: A Prospective Observational Study

Objective: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus responsible for Coronavirus Disease 2019 (COVID-19), elicits a strong immune response similar to that seen in other viral infections. The predominant cell type in …

[PDF] Cellular Immunity of SARS-CoV-2 in the Borriana COVID-19 Cohort: A Nested Case-Control Study

Our goal was to determine the cellular immune response (CIR) among a random sample of the Borriana COVID-19 cohort (Spain) to identify its associated factors and their relationship with infection, reinfection and sequelae. We conducted a nested …

[PDF] Actives from the Micro-Immunotherapy Medicine 2LMIREG® Reduce the Expression of Cytokines and Immune-Related Markers Including Interleukin-2 and HLA-II …

Introduction Micro-immunotherapy (MI) is a therapeutic option employing low doses (LD) and ultra-low doses (ULD) of cytokines and immune factors to help the organism at modulating the immune responses. In an overpowering inflammatory …

HLA peptide‐binding pocket diversity modulates immunological complications after cord blood transplant in acute leukaemia

Pocket motifs and their amino acid positions of HLA molecules are known to govern antigen presentation to effector cells. Our objective was to analyse their influence on the risk of graft‐versus‐host disease (GVHD) and relapse after umbilical cord blood …

Publisher Correction: Advancing T cell-based cancer therapy with single-cell technologies

Publisher Correction: Advancing T cell-based cancer therapy with single-cell technologies Publisher Correction: Advancing T cell-based cancer therapy with single-cell technologies Nat Med. 2024 Feb 5. doi: 10.1038/s41591-024-02841-x. Online …

MMV method: a new approach to compare protein sequences under binary representation

In the present work, a new form of descriptor using minimal moment vector (MMV) is introduced to compare protein sequences in the frequency domain under their component wise binary representations. From every sequence, 20 different binary …

Codon-tRNA Coadaptation Bias for Identifying Strong Native Promoters in Komagataella phaffii

Promoters are crucial elements for engineering microbial production strains used in bioprocesses. For the increasingly popular chassis Komagataella phaffii (formerly Pichia pastoris), a limited number of well-characterized promoters constrain the data …

Llm comparative assessment: Zero-shot nlg evaluation through pairwise comparisons using large language models

Current developments in large language models (LLMs) have enabled impressive zero-shot capabilities across various natural language tasks. An interesting application of these systems is in the automated assessment of natural language …

[PDF] PQA: Zero-shot Protein Question Answering for Free-form Scientific Enquiry with Large Language Models

We introduce the novel task of zero-shot Protein Question Answering (PQA) for free-form scientific enquiry. Given a previously unseen protein sequence and a natural language question, the task is to deliver a scientifically accurate answer. This task …

[PDF] Analysing The Impact of Sequence Composition on Language Model Pre-Training

Most language model pre-training frameworks concatenate multiple documents into fixed-length sequences and use causal masking to compute the likelihood of each token given its context; this strategy is widely adopted due to its simplicity and …

[HTML] pXg: Comprehensive identification of noncanonical MHC-I-associated peptides from de novo peptide sequencing using RNA-Seq reads

Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as ncMAPs (noncanonical MHC-I-associated peptides), that bind to major …

[HTML] AbImmPred: An immunogenicity prediction method for therapeutic antibodies using AntiBERTy-based sequence features

Due to the unnecessary immune responses induced by therapeutic antibodies in clinical applications, immunogenicity is an important factor to be considered in the development of antibody therapeutics. To a certain extent, there is a lag in using wet-lab experiments to test the immunogenicity in the development process of antibody therapeutics. Developing a computational method to predict the immunogenicity at once the antibody sequence is designed, is of great significance for the screening in …

[HTML] Fast-Track Discovery of SARS-CoV-2-Neutralizing Antibodies from Human B Cells by Direct Functional Screening

As the COVID-19 pandemic revealed, rapid development of vaccines and therapeutic antibodies are crucial to guarantee a quick return to the status quo of society. In early 2020, we deployed our droplet microfluidic single-cell-based …

Identification of IgE Epitope on Major Dog Allergen Can f 1

Methods Anti-Can f 1 hIgE 1J11 mAb was generated from B cell via human hybridoma technology and expressed in CHO cells as fragment antigen binding (Fab). Natural Can f 1 was extracted from the dog's dander and complexed with hIgE …

[HTML] Changes in the Adaptive Cellular Repertoire after Infection with Different SARS-CoV-2 VOCs in a Cohort of Vaccinated Healthcare Workers

Background: Currently approved vaccines are highly effective in protecting against hospitalization and severe COVID-19 infections. How pre-existing immunity responds to new variants with mutated antigens is crucial information for elucidating …

Chronic malaria exposure is associated with inhibitory markers on T cells that correlate with atypical memory and marginal zone-like B cells

Chronic immune activation from persistent malaria infections can induce immunophenotypic changes associated with T cell exhaustion. However, associations between T and B cells during chronic exposure remain undefined. We …

Robust asymmetric non-negative matrix factorization for clustering nodes in directed networks

Directed networks appear in an expanding array of applications, for example, the world wide web, social networks, transaction networks, and citation networks. A critical task in analyzing directed networks is clustering, where the goal is partitioning the network's nodes based on their similarities while accounting for the direction of relationships between nodes. Non-negative matrix factorization (NMF) and its variations have been used to cluster the nodes in directed networks by …

Impact of Glycosylation on Protein–Protein Self-Interactions of Monoclonal Antibodies

Protein self-interactions measured via second osmotic virial coefficients (B 22) and dynamic light scattering interaction parameter values (k D) are often used as metrics for assessing the favorability of protein candidates and different formulations during …

Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers

Excitement at the prospect of using data-driven generative models to sample configurational ensembles of biomolecular systems stems from the extraordinary success of these models on a diverse set of high-dimensional sampling tasks. Unlike …

[PDF] RNA threading with secondary structure and sequence profile

Motivation RNA threading aims to identify remote homologies for template-based modeling of RNA 3D structure. Existing RNA alignment methods primarily rely on secondary structure alignment. They are often time-and memory-consuming, limiting …

[PDF] Directed evolution of a bacterial leucyl tRNA in mammalian cells for enhanced noncanonical amino acid mutagenesis

The E. coli leucyl-tRNA synthetase (EcLeuRS)/tRNAEcLeu pair has been engineered to genetically encode a structurally diverse group of enabling noncanonical amino acids (ncAAs) in eukaryotes, including those with …

Large language models for science and medicine

Large language models (LLMs) are a type of machine learning model that learn statistical patterns over text, such as predicting the next words in a sequence of text. Both general purpose and task‐specific LLMs have demonstrated potential across …

[HTML] Full-Atom Peptide Design with Geometric Latent Diffusion

Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable. Most existing methods are either inefficient or only concerned with the target-agnostic design of 1D …

[PDF] LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons

Data scarcity in low-resource languages can be addressed with word-to-word translations from labeled task data in high-resource languages using bilingual lexicons. However, bilingual lexicons often have limited lexical overlap with task …

[PDF] LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition

Despite the impressive capabilities of large language models (LLMs), their performance on information extraction tasks is still not entirely satisfactory. However, their remarkable rewriting capabilities and extensive world knowledge offer valuable …

[PDF] Interpretable Prediction of SARS-CoV-2 Epitope-specific TCR Recognition Using a Pre-Trained Protein Language Model

The emergence of the novel coronavirus, designated as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has posed a significant threat to public health worldwide. There has been progress in reducing hospitalizations and deaths …

[PDF] Comparison of RNA-Seq and microarray in the prediction of protein expression and survival prediction

Gene expression profiling using RNA-sequencing (RNA-seq) and microarray technologies is widely used in cancer research to identify biomarkers for clinical endpoint prediction. We compared the performance of these two methods in …

[PDF] Protein Structure Prediction Using A New Optimization-Based Evolutionary and Explainable Artificial Intelligence Approach

Protein structure prediction (PSP) is an important scientific problem because it helps humans to understand how proteins perform their biological functions. This paper models the PSP problem as a multi-objective optimization problem with three fast …

[PDF] ProT-Diff: A Modularized and Efficient Approach to De Novo Generation of Antimicrobial Peptide Sequences through Integration of Protein Language Model and …

Antimicrobial Peptides (AMPs) represent a promising class of antimicrobial agents crucial for combating antibiotic-resistant pathogens. Despite the emergence of deep learning approaches for AMP discovery, there remains a gap in efficiently generating …

Discovery of Two Novel Immunoepitopes and Development of Peptide-based Sarcoidosis Immunoassay

Rationale: Sarcoidosis is a systemic granulomatous disorder associated with hypergammaglobulinemia and the presence of autoantibodies. The specific antigens initiating granulomatous inflammation in sarcoidosis are unknown and there is no specific test available to diagnose sarcoidosis. To discover novel sarcoidosis antigens, we developed a high-throughput T7 phage display library derived from the sarcoidosis cDNA and identified numerous clones differentiating sarcoidosis from …

Progress and Challenges in Computational Structure-Based Design and Development of Biological Drugs

At the same time, with the fast-paced infusion of artificial intelligence in various research areas that impact daily life, we are witnessing a new chapter being written in biological drug design (Kim et al., 2023). A wide range of nonlinear models, from machine learning to unsupervised deep neural networks and language models, is now emerging. These models, fueled by still modest but expanding biological and structural datasets, are complementing classical methods (Baek et al., 2021; Jumper …

[PDF] On Organizational Principles of Neural Systems

How do we understand natural intelligence? Inspired by classical embodied cognition and the emerging multimodal interaction, we study the organizational principles of neural systems at three levels (device/implementation, circuit/algorithm, and system/computational) in this survey paper. Our main contributions consist of 1) Device/Implementation level: reproducibility of macroscopic states in polychronization neural group (PNG) serves as the physical basis of associative …

[PDF] Lung-resident memory B cells maintain allergic IgE responses in the respiratory tract

Allergen-specific IgE is a key mediator of allergic asthma. However, the tissue sites and cell types that support IgE production at the mucosa remained undefined. Here, we reveal that inhaled allergens induce the formation of IgG1+ lung-resident memory …

[HTML] P53-Independent G1-Cell Cycle Arrest Increases SARS-CoV-2 RNA Replication

While having already killed more than 7 million of people worldwide in 4 years, SARS-CoV-2, the etiological agent of COVID-19, is still circulating and evolving. Understanding the pathogenesis of the virus is of capital importance. It was shown …

MALT1 inhibition suppresses antigen-specific T cell responses

The aim of this study was to assess the potential use of a selective small molecule MALT1 inhibitor in solid tumor treatment as an immunotherapy targeting regulatory T-cells (Tregs). In vitro, MALT1 inhibition suppressed the proteolytic cleavage of the …

[PDF] PRMT1 acts as a suppressor of MHC-I and anti-tumor immunity

Cancer immunotherapies have demonstrated remarkable success; however, the majority of patients do not respond or develop resistance. Here, we conduct epigenetic gene-targeted CRISPR-Cas9 screens to identify epigenomic factors that …

[HTML] Quantification and prediction of T-cell cross-reactivity through experimental and computational methods

T-cell receptor (TCR) molecules play a central role in adaptive cellular immunity, enabling T-cell lymphocytes to recognize peptide-loaded Major Histocompatibility Complexes (pMHCs) at the surface of other cells (Figure 1). In turn, this molecular interaction can trigger T-cell activation and function (eg, cytotoxicity or immunomodulation)(1). The specificity of the TCRpMHC interaction is essential for the efficiency of cellular immunity against infectious pathogens and cancer cells, as …

[PDF] Rational protein engineering to enhance MHC-independent T cell receptors

Chimeric antigen receptor (CAR)-based therapies have pioneered synthetic cellular immunity against cancer, however remain limited in their scope and long-term efficacy. Emerging data suggest that dysregulated CAR-driven T cell activation …

Immune Cell Infiltration Types as Biomarkers for the Recurrence Diagnosis and Prognosis of Bladder Cancer

This study aimed to investigate the role of infiltrating immune cell types in diagnosing and predicting bladder cancer recurrence. This study mainly applied some algorithms, including Estimate the Proportion of Immune and Cancer Cells (EPIC), support vector machine-recursive feature elimination (SVM-RFE), random forest out-of-bag (RF-OOB) and least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. We found six immune infiltrating cell types significantly …

Race, Telomeres, and Genomic Insights Into Pulmonary Fibrosis

Pulmonary fibrosis pathophysiology is increasingly recognized to be influenced by the biology of telomeres, a field that has now grown in prominence with the widespread adoption of affordable next-generation sequencing over the past decade, leading to an improved understanding of telomere-related mechanisms underlying pulmonary fibrosis. Despite these advancements, notable gaps in knowledge persist. Firstly, individuals with telomere biology disorders or shortening …

[PDF] A human lymphoma organoid model for evaluating and targeting the follicular lymphoma tumor immune microenvironment

Heterogeneity in the tumor microenvironment (TME) of follicular lymphomas (FLs) can affect clinical outcomes. Current immunotherapeutic strategies, including antibody-and cell-based therapies, variably overcome pro-tumorigenic mechanisms for sustained disease control. Modeling the intact FL TME, with its native, syngeneic tumor-infiltrating leukocytes, is a major challenge. Here, we describe an organoid culture method for cultivating patient-derived lymphoma organoids (PDLOs), which …

[HTML] Chicken γδ T cells proliferate upon IL-2 and IL-12 treatment and show a restricted receptor repertoire in cell culture

In chickens, γδ T cells represent a large fraction of peripheral T cells; however, their function remains largely unknown. Here, we describe the selective in vitro expansion of γδ T cells from total splenocytes by stimulation with the cytokines IL-2 and IL-12. Under these conditions, γδ T cells proliferated preferentially and reached frequencies of> 95% within three weeks. Although IL-2 alone also triggered proliferation, an increased proliferation rate was observed in combination with IL-12 …

B Cell–mediated Immune Regulation and the Quest for Transplantation Tolerance

Pathophysiologic function of B cells in graft rejection has been well recognized in transplantation. B cells promote alloantigen-specific T-cell response and secrete antibodies that can cause antibody-mediated graft failures and rejections. Therefore, strategies targeting B cells, for example, B-cell depletion, have been used for the prevention of both acute and chronic rejections. Interestingly, however, recent mounting evidence indicates that subsets of B cells yet to be further identified can …

Deep learning in modeling protein complex structures: From contact prediction to end-to-end approaches

Protein–protein interactions play crucial roles in many biological processes. Traditionally, protein complex structures are normally built by protein–protein docking. With the rapid development of artificial intelligence and its great success in monomer protein structure prediction, deep learning has widely been applied to modeling protein–protein complex structures through inter-protein contact prediction and end-to-end approaches in the past few years. This article reviews the recent …

[PDF] Identification of a Potential Entry-Fusion Complex Based on Sequence Homology of African Swine Fever and Vaccinia Virus

African swine fever virus (ASFV) belongs to the family of Asfarviridae, part of the group of nucleocytoplasmic large DNA viruses (NCLDV). Little is known about the internalization of ASFV in the host cell and the fusion membrane events that take place at early stages of the infection.

Impact of chemical properties of the solid-liquid-adsorbate interfaces on the entropy-enthalpy compensation involved in adsorption

Despite extensive studies on the thermodynamic mechanism governing molecular adsorption at the solid-water interface, a comprehensive understanding on the crucial role of interface properties in mediating the entropy-enthalpy compensation during adsorption is lacking, particularly at a quantitative level. Herein, we employed two types of surface models (hydroxyapatite and graphene) along with a series of amino acids to successfully elucidate how distinct interfacial features dictate the …

[PDF] Do antibody CDR loops change conformation upon binding?

Antibodies have increasingly been developed as drugs with over 100 now licensed in the US or EU. During development, it is often necessary to increase or reduce the affinity of an antibody and rational attempts to do so rely on having a structure of the antibody-antigen complex often obtained by modeling. The antigen-binding site consists primarily of six loops known as complementarity-determining regions (CDRs), and an open question has been whether these loops change their …

Bioinformatics analysis and validation of the interaction between PML protein and TAB1 protein

Objective To analyze the interaction between PML protein and TAB1 protein using bioinformatic approaches and experimentally verify the results. Methods Using Rosetta software, a 3D model of TAB1 protein was constructed through a comparative modeling approach; the secondary structure of PML protein was retrieved in the PDB database and its crystal structure and 3D structure were resolved. Zdock 3.0. 2 software was used to perform protein-protein docking of PML …

[HTML] Phage-assisted evolution of highly active cytosine base editors with enhanced selectivity and minimal sequence context preference

TadA-derived cytosine base editors (TadCBEs) enable programmable C• G-to-T• A editing while retaining the small size, high on-target activity, and low off-target activity of TadA deaminases. Existing TadCBEs, however, exhibit residual A• T-to-G• C editing at certain positions and lower editing efficiencies at some sequence contexts and with non-SpCas9 targeting domains. To address these limitations, we use phage-assisted evolution to evolve CBE6s from a TadA-mediated dual cytosine and …

[PDF] An Overview of Bioinformatics and Its Application: A Ray of Hope Towards Microbial Biotechnology

A new era in the analysis of biological data has been sparked by the revolutionary development in processing speed and memory capacity. With the sequencing of hundreds of microbial and numerous eukaryotic genomes—including a clearer draft of the human genome—better control over microbes is anticipated. The objectives are very high and include the creation of sensible medications and antimicrobial agents, the creation of novel, improved bacterial strains for bioremediation and …

[PDF] Teaching research data management with DataLad: a multi-year, multi-domain effort

Research data management has become an indispensable skill in modern neuroscience. Researchers can benefit from following good practices as well as from having proficiency in using particular software solutions. But as these domain-agnostic skills are commonly not included in domain-specific graduate education, community efforts increasingly provide early career scientists with opportunities for organised training and materials for self-study. Investing effort in user documentation …

[PDF] Multiscale Mineralization in the Leopard Gecko Eggshell

Reptilian (non‐avian) eggshell biomineralization is markedly different from avian eggshells. Despite discontinuous/variable mineralization, the reptilian eggshell (like in birds) is responsible for protective and developmental functions of the egg as part of a highly successful reproduction strategy. Using multiscale imaging and characterization methods including X‐ray and electron microscopy/tomography, a 3D overview of eggshell ultrastructure in the gekkotan Eublepharis macularius–the …

Atom-ProteinQA: Atom-Level Protein Model Quality Assessment through Fine-grained Joint Learning

Motivation Protein model quality assessment (ProteinQA) is a fundamental task that is essential for biologically relevant applications, ie, protein structure refinement, protein design, etc. Previous works aimed to conduct ProteinQA only on the global …

An immunogenetic basis for lung cancer risk

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population …

[HTML] Anti-Vα24Jα18 TCR antibody tunes iNKT cell responses to target and kill CD1d-negative tumors in an FcγRII (CD32)-dependent manner

Invariant natural killer T (iNKT) cells play an essential role in antitumor immunity by exerting cytotoxicity and producing massive amounts of cytokines. iNKT cells express invariant T-cell receptors (TCR) to recognize their cognate glycolipid antigens such …

CD4+ T cells from individuals with type 1 diabetes respond to a novel class of deamidated peptides formed in pancreatic islets

The β-cell plays a crucial role in the pathogenesis of type 1 diabetes, in part through the posttranslational modification of self-proteins by biochemical processes such as deamidation. These neoantigens are potential triggers for breaking immune …

Risk factors for graft-versus-host-disease after donor lymphocyte infusion following T-cell depleted allogeneic stem cell transplantation

Unmodified donor lymphocyte infusions (DLI) after allogeneic stem cell transplantation (alloSCT) can boost the beneficial Graft-versus-Leukemia (GvL) effect but may also induce severe Graftversus-Host-Disease (GvHD). To improve the …

[PDF] Single-Cell CD4 and CD8 T Cell Secretome Profiling Reveals Temporal and Niche Differences in Acute Myeloid Leukemia Following Immune Checkpoint Blockade …

Acute myeloid leukemia (AML) is a heterogeneous malignancy of the blood primarily treated with intensive chemotherapy. The allogeneic T cell anti-leukemic activity via donor lymphocyte infusions and stem cell transplantation suggests a potential role …

[HTML] Adjuvant dendritic cell therapy in stage IIIB/C melanoma: the MIND-DC randomized phase III trial

Autologous natural dendritic cells (nDCs) treatment can induce tumor-specific immune responses and clinical responses in cancer patients. In this phase III clinical trial (NCT02993315), 148 patients with resected stage IIIB/C melanoma were …

[PDF] Single-cell transcriptomics reveals a pivotal role of DOCK2 in Sjögren's disease

Sjögren's disease (SjD) is an autoimmune condition characterized by the dysfunction of the salivary and lacrimal glands. This study utilized single-cell RNA sequencing to analyze the immune cell composition and dynamics within the salivary glands of SjD …

[PDF] A handle on mass coincidence errors in de novo sequencing of antibodies by bottom-up proteomics

Antibody sequences can be determined at 99% accuracy directly from the polypeptide product using bottom-up proteomics techniques. This circumvents the need to isolate the antibody-producing B-cell clone and enables reverse engineering …

[HTML] Inter-epitope spacer variation within polytopic L2-based human papillomavirus antigens affects immunogenicity

The human papillomavirus minor capsid protein L2 is being extensively explored in pre-clinical studies as an attractive vaccine antigen capable of inducing broad-spectrum prophylactic antibody responses. Recently, we have developed two HPV …

[PDF] Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy

With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the …

[PDF] Regulation of temporal cytokine production by co-stimulation receptors in TCR-T cells is lost in CAR-T cells

CD8+ T cells contribute to immune responses by producing cytokines when their T cell receptors (TCRs) recognise peptide antigens on major-histocompability-complex (pMHC) class I. However, excessive cytokine production can be harmful. For …

[PDF] Language Model and Its Interpretability in Biomedicine: A Scoping Review

With advancements in large language models, artificial intelligence (AI) is undergoing a paradigm shift where AI models can be repurposed with minimal effort across various downstream tasks. This provides great promise in learning generally useful representations from biomedical corpora, at scale, which would empower AI solutions in healthcare and biomedical research. Nonetheless, our understanding of how they work, when they fail, and what they are capable of remains underexplored …

[PDF] PreMode predicts mode of action of missense variants by deep graph representation learning of protein sequence and structural context

Accurate prediction of the functional impact of missense variants is fundamentally important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a …

[PDF] A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features

Goal: The purpose of this study is to evaluate the importance of cardiorespiratory variables within a Reinforcement Learning (RL) recommendation system aimed at establishing optimal strategies for drug treatment of septic patients in the intensive care unit (ICU). Methods: We developed a RL framework in order to establish drug administration strategies for septic patients by exclusively using a set of cardiorespiratory variables. We then compared this model with other equivalent …

[PDF] Pseudotyped virus infection of multiplexed ACE2 libraries reveals SARS-CoV-2 variant shifts in receptor usage

Pairwise compatibility between virus and host proteins can dictate the outcome of infection. During transmission, both inter-and intraspecies variabilities in receptor protein sequences can impact cell susceptibility. Many viruses possess mutable viral …

In silico designing of novel epitope-based peptide vaccines against HIV-1

The HIV-1 virus has been regarded as a catastrophe for human well-being. The global incidence of HIV-1-infected individuals is increasing. Hence, development of effective immunostimulatory molecules has recently attracted an increasing attention …

GDilatedDTA: Graph dilation convolution strategy for drug target binding affinity prediction

Traditional drug development methods require a huge amount of time. The utilization of deep learning methods for predicting drug–target binding affinity (DTA) has the potential to expedite the drug screening process, thereby accelerating drug …

Multiple environmental antigens may trigger autoimmunity in psoriasis through T-cell receptor polyspecificity

Psoriasis is a T-cell mediated autoimmune skin disease. HLA-C* 06: 02 is the main psoriasis-specific risk gene. Using a Vα3S1/Vβ13S1 T-cell receptor (TCR) from a lesional psoriatic CD8+ T-cell clone we had discovered that, as an underlying …

Computational Analysis of B-Cell Receptor (BCR) Immune Repertoires with Abalign

The widespread application of high-throughput sequencing technology has generated massive sequences of B-cell receptor (BCR) immune repertoires. Computational analysis of these data has gained significant attention due to the …

[PDF] Tissue-Resident Memory T Cell Signatures from Single-Cell Analysis Associated with Better Melanoma Prognosis

Tissue-resident memory T cells (T RM) are a specialized T cell population residing in peripheral tissues. The presence and potential impact of T RM in the tumor immune microenvironment (TIME) remain to be elucidated. Here, we systematically …

[HTML] Decoding the transcriptional heterogeneity, differentiation lineage, clinical significance in tissue-resident memory CD8 T cell of the small intestine by single-cell …

Resident memory T (Trm) cells which are specifically located in non-lymphoid tissues showed distinct phenotypes and functions compared to circulating memory T cells and were vital for the initiation of robust immune response within tissues. However …

[HTML] Computational prediction of MHC class I epitopes for most common viral diseases in cattle (< i style=" mso-bidi-font-style: normal"> Bos taurus</i>)< span style=" font …

Viral diseases like foot-and-mouth disease (FMD), calf scour (CS), bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR) etc. affect the growth and milk production of cattle (Bos taurus) causing severe economic loss.Epitope-based …

Enhancing chimeric antigen receptor T cell therapy by modulating the p53 signaling network with Δ133p53α

Chimeric antigen receptor (CAR) T cell dysfunction is a major barrier to achieving lasting remission in hematologic cancers, especially in chronic lymphocytic leukemia (CLL). We have shown previously that Δ133p53α, an endogenous isoform of the …

[PDF] Degradation of IKAROS prevents epigenetic progression of T cell exhaustion in a novel antigen-specific assay

In cancer, chronic antigen stimulation drives effector T cells to exhaustion, limiting the efficacy of T cell therapies. Recent studies have demonstrated that epigenetic rewiring governs the transition of T cells from effector to exhausted states and makes …

[HTML] Dynamics of SARS-CoV-2 immunity after vaccination and breakthrough infection in rituximab-treated rheumatoid arthritis patients: a prospective cohort study

Background SARS-CoV-2 vaccination in rheumatoid arthritis (RA) patients treated with B cell-depleting drugs induced limited seroconversion but robust cellular response. We aimed to document specific T and B cell immunity in response to …

[PDF] Multi-compartmental diversification of neutralizing antibody lineages dissected in SARS-CoV-2 spike-immunized macaques

The continued evolution of SARS-CoV-2 underscores the need to understand qualitative aspects of the humoral immune response elicited by spike immunization. Here, we combined monoclonal antibody (mAb) isolation with deep B cell receptor …

[HTML] Probabilistically-sound beam search with masked language models

Beam search with masked language models (MLMs) is challenging in part because joint probability distributions over sequences are not readily available, unlike for autoregressive models. Nevertheless, estimating such distributions has applications in many domains, including protein engineering and ancient text restoration. We present probabilistically-sound methods for beam search with MLMs. First, we clarify the conditions under which it is theoretically sound to perform text infilling with MLMs …

[PDF] ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing

Large Language Models (LLMs), including GPT-x and LLaMA2, have achieved remarkable performance in multiple Natural Language Processing (NLP) tasks. Under the premise that protein sequences constitute the protein language, Protein Large Language Models (ProLLMs) trained on protein corpora excel at de novo protein sequence generation. However, as of now, unlike LLMs in NLP, no ProLLM is capable of multiple tasks in the Protein Language Processing (PLP) field. This …

[PDF] Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based …

Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens ignore 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms …

[HTML] Subunits of an E3 Ligase Complex as Degrons for Efficient Degradation of Cytosolic, Nuclear, and Membrane Proteins

Protein degradation is a highly regulated cellular process crucial to enable the high dynamic range of the response to external and internal stimuli and to balance protein biosynthesis to maintain cell homeostasis. Within mammalian cells, hundreds of E3 …

[PDF] Detection, isolation and characterisation of phage-host complexes using BONCAT and click chemistry

Phages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation, and predicting host specificity of phages. A new workflow using …

Corrigendum: Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence

Frontiers | Corrigendum: Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence Skip to main content Top bar navigation Frontiers in Immunology About us About us Who we are Mission Values …

Revolutionizing and identifying novel drug targets in Citrobacter koseri via subtractive proteomics and development of a multi-epitope vaccine using reverse …

Citrobacter koseri is a gram-negative rod that has been linked to infections in people with significant comorbidities and immunocompromised immune systems. It is most commonly known to cause urinary tract infections. Thus, the development of an …

[PDF] Protein Function Prediction Through Multi-view Multi-label Latent Tensor Reconstruction

Background:: While the advent of high-throughput sequencing technologies has accelerated the pace of discovery of proteins, the functions of the majority of them remain unknown. This is mainly due to the time and resource limitations of rigorous …

[PDF] A Brief Review of Big Data in Healthcare: Challenges and Issues, Recent Developments, and Future Directions

Big data is improving the healthcare industry and creating opportunities for improved patient care, personalized medicine, and advanced research. This brief review article aims to survey the challenges and issues connected with big data in healthcare, discuss recent developments in the field, and highlight future directions for helping big data to enhance healthcare outcomes by understanding these aspects, participants can make informed decisions and contribute to the advancement of big …

Dissecting the role of CAR signaling architectures on T cell activation and persistence using pooled screening and single-cell sequencing

Chimeric antigen receptor (CAR) T cells represent a promising approach for cancer treatment, yet challenges remain such as limited efficacy due to a lack of T cell persistence. Given its critical role in promoting and modulating T cell responses, it is …

[PDF] Long-Context Language Modeling with Parallel Context Encoding

Extending large language models (LLMs) to process longer inputs is crucial for numerous applications. However, the considerable computational cost of transformers, coupled with limited generalization of positional encoding, restricts the …

[HTML] CoCoNat: A Deep Learning–Based Tool for the Prediction of Coiled-coil Domains in Protein Sequences

Coiled-coil domains (CCDs) are structural motifs observed in proteins in all organisms that perform several crucial functions. The computational identification of CCD segments over a protein sequence is of great importance for its functional …

[PDF] Grasping the Essentials: Tailoring Large Language Models for Zero-Shot Relation Extraction

Relation extraction (RE), a crucial task in NLP, aims to identify semantic relationships between entities mentioned in texts. Despite significant advancements in this field, existing models typically rely on extensive annotated data for training, which can be …

[PDF] Large Language Models as Zero-shot Dialogue State Tracker through Function Calling

Large language models (LLMs) are increasingly prevalent in conversational systems due to their advanced understanding and generative capabilities in general contexts. However, their effectiveness in task-oriented dialogues (TOD), which requires not …

[PDF] LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting

Time-series forecasting (TSF) finds broad applications in real-world scenarios. Prompting off-the-shelf Large Language Models (LLMs) demonstrates strong zero-shot TSF capabilities while preserving computational efficiency. However, existing …

[PDF] Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models

Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks and exhibited impressive reasoning abilities by applying zero-shot Chain-of-Thought (CoT) prompting. However, due to the evolving nature of sentence …

[PDF] Chimera: A Lossless Decoding Method for Accelerating Large Language Models Inference by Fusing all Tokens

Large language models (LLMs) have demonstrated remarkable capabilities across various tasks. However, their widespread application is hindered by the resource-intensive decoding process. To address this challenge, current approaches have …

[PDF] Discovery and Characterization of a Pan-betacoronavirus S2-binding antibody

Three coronaviruses have spilled over from animal reservoirs into the human population and caused deadly epidemics or pandemics. The continued emergence of coronaviruses highlights the need for pan-coronavirus interventions for effective pandemic preparedness. Here, using LIBRA-seq, we report a panel of 50 coronavirus antibodies isolated from human B cells. Of these antibodies, 54043-5 was shown to bind the S2 subunit of spike proteins from alpha-, beta-, and …

[PDF] " Multimodal Immunomonitoring of Hematopoietic Stem Cell Transplantation and Cellular Therapies for Hematological Malignancies

Allogeneic hematopoietic stem cell transplantation (HSCT) and other cellular therapies are a broadly used therapeutic strategy employed against a wide range of hematological malignancies. However, these therapies are associated with significant toxicities and their efficacy is still not optimal. Our ability to study the immune system at steady state, during physiological responses and in immunopathological diseases greatly increased during the last decades thanks to …

[PDF] Identification of apolipoprotein B-reactive CDR3 motifs allow tracking of atherosclerosisrelated memory CD4+ T cells in multiple donors

Atherosclerosis is a major pathological condition that underlies many cardiovascular diseases (CVD). Its etiology involves breech of tolerance to self, leading to clonal expansion of autoreactive apolipoprotein B (APOB)-reactive CD4+ T cells that correlates with clinical CVD. The T cell receptor (TCR) sequences that mediate activation of APOB-specific CD4+ T cells are unknown. In a previous study, we had profiled the hypervariable complementarity determining region 3 (CDR3) of CD4+ T …

[PDF] Role of Ligand Design on the Stability of Metal Complexes and Its Catalytic Properties-A Mini-Review

The role of ligand design is a serious criterion for forming metal complexes and their stability, as well as the catalytic properties. This has been a hot topic for at least 30 years. Nine electronic databases, including China National Knowledge Infrastructure (CNKI), Wan Fang Data, PubMed, Science Direct, Scopus, Web of Science, Springer Link, Sci Finder, and Google Scholar were searched from 2011 to 2023 and without language restrictions in this review. Based on the findings, the metal complex …

[PDF] Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning

Graph learning plays a pivotal role and has gained significant attention in various application scenarios, from social network analysis to recommendation systems, for its effectiveness in modeling complex data relations represented by graph structural data. In reality, the real-world graph data typically show dynamics over time, with changing node attributes and edge structure, leading to the severe graph data distribution shift issue. This issue is compounded by the diverse and complex nature …

[PDF] How to Sustain a Scientific Open-Source Software Ecosystem: Learning from the Astropy Project

Scientific open-source software (OSS) has greatly benefited research communities through its transparent and collaborative nature. Given its critical role in scientific research, ensuring the sustainability of such software has become vital. Earlier studies have proposed sustainability strategies for conventional scientific software and open-source communities. However, it remains unclear whether these solutions can be easily adapted to the integrated framework of scientific OSS and its larger …

[PDF] Structure-Function Analysis of Factor VII Activating Protease (FSAP)

A blood clot in brain vessels can cause a stroke, a major cause of death and disability. Previous research showed that Factor VII Activating Protease (FSAP), a blood protease, improved stroke outcome in mice by accelerating clot lysis and exhibiting neuroprotective effects. However, the molecular mechanisms underlying the actions of FSAP remain unclear. This thesis aims to bridge this gap by conducting a comprehensive biochemical analysis of FSAP and its interactions with substrates …

[PDF] Advancing Drug-Target Interactions Prediction: Leveraging a Large-Scale Dataset with a Rapid and Robust Chemogenomic Algorithm.

Predicting drug-target interactions (DTIs) is crucial for drug discovery, and heavily relies on supervised learning techniques. In the context of DTI prediction, supervised learning algorithms use known DTIs to learn associations between molecule and protein features, allowing for the prediction of new interactions based on learned patterns. In this paper, we present a novel approach addressing two key challenges in DTI prediction: the availability of large, high-quality training datasets and the …

[PDF] Statistical Models for Large Scale Genomic Data

Sequencing technologies transformed how scientists examine biological systems at both macroscopic and microscopic level. For example, population-scale genome sequencing has cataloged millions of common and rare genetic variants in humans and enabled genotype imputation; new spatial transcriptomics technologies can resolve the sequences and locations of individual transcripts in tissues at submicron resolution. The massive amount of data generated by these technologies poses new …

The S2 subunit of spike encodes diverse targets for functional antibody responses to SARS-CoV-2

The SARS-CoV-2 virus responsible for the COVID-19 global pandemic has exhibited a striking capacity for viral evolution that drives continued evasion from vaccine and infection-induced immune responses. Mutations in the receptor binding domain of …

[HTML] A functional identification platform reveals frequent, spontaneous neoantigen-specific T cell responses in patients with cancer

The clinical impact of tumor-specific neoantigens as both immunotherapeutic targets and biomarkers has been impeded by the lack of efficient methods for their identification and validation from routine samples. We have developed a platform …

[PDF] Integrating circulating T follicular memory cells and autoantibody repertoires for characterization of autoimmune disorders

Introduction. Autoimmune diseases are heterogeneous and often lack specific or sensitive diagnostic tests. Increased percentages of CD4+ CXCR5+ PD1+ circulating T follicular helper (cTfh) cells and skewed distributions of cTfh subtypes have been …

[HTML] Rise in broadly cross-reactive adaptive immunity against human β-coronaviruses in MERS-recovered patients during the COVID-19 pandemic

To develop a universal coronavirus (CoV) vaccine, long-term immunity against multiple CoVs, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, Middle East respiratory syndrome (MERS)–CoV, and future CoV …

[PDF] FS-mutant: A Few-shot Learning Benchmark for Protein Mutants Mining

AI-assisted protein engineering means using machine learning models to mine mutants of a protein from its huge mutant library. Existed techniques, such as supervised models and zero-shot models, have received a lot of attention. The supervised approaches require a lot of data for optimal performance while the zero-shot models do not need assay-labeled data but their performance cannot be improved with labeled data increasing. In practice, researchers only have a small …

[PDF] Exploring the conformational space of protein-protein complex with transformer-based generative model

Protein-protein interactions are the basis of many protein functions, and understanding the contact and conformational changes of protein-protein interactions is crucial for linking protein structure to biological function. Although …

[PDF] An unusual dual sugar-binding lectin domain controls the substrate specificity of a mucin-type O-glycosyltransferase

N-acetylgalactosaminyl-transferases (GalNAc-Ts) initiate mucin-type O-glycosylation, an abundant and complex posttranslational modification that regulates host-microbe interactions, tissue development, and metabolism. GalNAc-Ts contain a lectin domain consisting of three homologous repeats (α, β, and γ), where α and β can potentially interact with O-GalNAc on substrates to enhance activity toward a nearby acceptor Thr/Ser. The ubiquitous isoenzyme GalNAc-T1 modulates heart …

[HTML] A novel major facilitator superfamily-type tripartite efflux system CprABC mediates resistance to polymyxins in Chryseobacterium sp. PL22-22A

Background: Polymyxin B (PMB) and polymyxin E (colistin, CST) are polymyxin antibiotics, which are considered last-line therapeutic options against multidrug-resistant Gram-negative bacteria in serious infections. However, there is increasing risk of resistance to antimicrobial drugs. Effective efflux pump inhibitors (EPIs) should be developed to help combat efflux pump-mediated antibiotic resistance. Methods: Chryseobacterium sp. PL22-22A was isolated from aquaculture sewage under …

[PDF] Targeting high-risk multiple myeloma genotypes with optimized anti-CD70 CAR-T cells

Despite the success of BCMA-targeting CAR-Ts in multiple myeloma, patients with high-risk cytogenetic features still relapse most quickly and are in urgent need of additional therapeutic options. Here, we identify CD70, widely recognized as a favorable immunotherapy target in other cancers, as a specifically upregulated cell surface antigen in high risk myeloma tumors. We use a structure-guided design to define a CD27-based anti-CD70 CAR-T design that outperforms all tested scFv …

[HTML] Cryo-EM analysis of S. aureus TarL, a polymerase in wall teichoic acid biogenesis central to virulence and antibiotic resistance

Wall teichoic acid (WTA), a covalent adduct of Gram-positive bacterial cell wall peptidoglycan, contributes directly to virulence and antibiotic resistance in pathogenic species. Polymerization of the Staphylococcus aureus WTA ribitol-phosphate chain is catalyzed by TarL, a member of the largely uncharacterized TagF-like family of membrane-associated enzymes. We report the cryo–electron microscopy structure of TarL, showing a tetramer that forms an extensive membrane …

[HTML] Archaeal histone-based chromatin structures regulate transcription elongation rates

Many archaea encode and express histone proteins to compact their genomes. Archaeal and eukaryotic histones share a near-identical fold that permits DNA wrapping through select histone-DNA contacts to generate chromatin-structures that must be traversed by RNA polymerase (RNAP) to generate transcripts. As archaeal histones can spontaneously assemble with a single histone isoform, single-histone chromatin variants provide an idealized platform to detail the impacts of distinct …

A VRC13-like bNAb response is associated with complex escape pathways in HIV-1 envelope

The rational design of HIV-1 immunogens to trigger the development of broadly neutralizing antibodies (bNAbs) requires understanding the viral evolutionary pathways influencing this process. An acute HIV-1-infected individual exhibiting> 50% plasma neutralization breadth developed neutralizing antibody specificities against the CD4-binding site (CD4bs) and V1V2 regions of Env gp120. Comparison of pseudoviruses derived from early and late autologous env sequences …

[HTML] Structure-based engineering of Tor complexes reveals that two types of yeast TORC1 produce distinct phenotypes

Certain proteins assemble into diverse complex states, each having a distinct and unique function in the cell. Target of rapamycin (Tor) complex 1 (TORC1) plays a central role in signalling pathways that allow cells to respond to the environment, including nutritional status signalling. TORC1 is widely recognised for its association with various diseases. The budding yeast Saccharomyces cerevisiae has two types of TORC1, Tor1-containing TORC1 and Tor2-containing TORC1, which comprise …

[HTML] Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic Assays

With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive, lab experiments are necessary for their optimization. This paper presents a transfer learning design of experiments workflow to make this development feasible. By combining a transfer learning surrogate model with Bayesian …

Computational Analysis of B‐Cell Receptor (BCR) Immune Repertoires with Abalign

The widespread application of high‐throughput sequencing technology has generated massive sequences of B‐cell receptor (BCR) immune repertoires. Computational analysis of these data has gained significant attention due to the …

[PDF] Bat humoral immunity and its role in viral pathogenesis, transmission, and zoonosis

Bats harbor viruses that can cause severe disease and death in humans including filoviruses (eg, ebola virus), henipaviruses (eg, Hendra virus) and coronaviruses (eg, SARS-CoV). Bats often tolerate these viruses without noticeable adverse immunological effects or succumbing to disease. Previous studies have largely focused on the role of the bat innate immune response to control viral pathogenesis, but little is known about bat adaptive immunity. A key component of adaptive …

[PDF] TCRpred: incorporating T-cell receptor repertoire for clinical outcome prediction

T-cell receptor (TCR) plays critical roles in recognizing antigen peptides and mediating adaptive immune response against disease. High-throughput technologies have enabled the sequencing of TCR repertoire at the single nucleotide level, allowing researchers to characterize TCR sequences with high resolutions. The TCR sequences provide important information about patients' adaptive immune system, and have the potential to improve clinical outcome …

[HTML] An integrative mechanistic model of thymocyte dynamics

Background The thymus plays a central role in shaping human immune function. A mechanistic, quantitative description of immune cell dynamics and thymic output under homeostatic conditions and various patho-physiological scenarios are of particular interest in drug development applications, eg, in the identification of potential therapeutic targets and selection of lead drug candidates against infectious diseases. Methods We here developed an integrative mathematical model of …

[HTML] Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings

Can we pre-train a generalist agent from a large amount of unlabeled offline trajectories such that it can be immediately adapted to any new downstream tasks in a zero-shot manner? In this work, we present a functional reward encoding (FRE) as …

DisPredict3. 0: Prediction of intrinsically disordered regions/proteins using protein language model

Intrinsically disordered proteins (IDPs) or protein regions (IDRs) do not have a stable three-dimensional structure, even though they exhibit important biological functions. They are structurally and functionally very different from ordered proteins and can cause many critical diseases. Accurate identification of disordered proteins/regions significantly impacts fields such as drug design, protein engineering, protein design, and related research. However, experimental identification of IDRs is complex and …

MSF-PFP: A Novel Multisource Feature Fusion Model for Protein Function Prediction

Protein function prediction is essential for disease treatment and drug development; yet, traditional biological experimental methods are less efficient in annotating protein function, and existing automated methods fail to fully leverage protein multisource data. Here, we present MSF-PFP, a computational framework that fuses multisource data features to predict protein function with high accuracy. Our framework designs specific models for feature extraction based on the characteristics …

[PDF] Diffusion Language Models Are Versatile Protein Learners

This paper introduces diffusion protein language model (DPLM), a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequences. We first pre-train scalable DPLMs from evolutionary-scale protein sequences within a generative self-supervised discrete diffusion probabilistic framework, which generalizes language modeling for proteins in a principled way. After pre-training, DPLM exhibits the ability to generate structurally plausible, novel …

[HTML] TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence Generation

Designing protein sequences with specific biological functions and structural stability is crucial in biology and chemistry. Generative models already demonstrated their capabilities for reliable protein design. However, previous models are limited to the unconditional generation of protein sequences and lack the controllable generation ability that is vital to biological tasks. In this work, we propose TaxDiff, a taxonomic-guided diffusion model for controllable protein sequence generation that combines …

[HTML] Dynamic establishment of recipient resident memory T cell repertoire after human intestinal transplantation

Background Understanding formation of the human tissue resident memory T cell (TRM) repertoire requires longitudinal access to human non-lymphoid tissues. Methods By applying flow cytometry and next generation sequencing to serial blood, lymphoid tissue, and gut samples from 16 intestinal transplantation (ITx) patients, we assessed the origin, distribution, and specificity of human TRMs at phenotypic and clonal levels. Findings Donor age≥ 1 year and blood T cell macrochimerism (peak …

[PDF] StaPep: an open-source tool for the structure prediction and feature extraction of hydrocarbon-stapled peptides

Many tools exist for extracting structural and physiochemical descriptors from linear peptides to predict their properties, but similar tools for hydrocarbon-stapled peptides are lacking. Here, we present StaPep, a Python-based toolkit designed for …

[PDF] An EBV-related CD4 TCR immunotherapy inhibits tumor growth in an HLA-DP5+ nasopharyngeal cancer mouse model

Adoptive transfer of T cell receptor-engineered T cells (TCR-T) is a promising strategy for immunotherapy against solid tumors. However, the potential of CD4+ T cells in mediating tumor regression has been neglected. Nasopharyngeal cancer is …

[PDF] Bivalent mRNA COVID vaccines elicit predominantly cross-reactive CD4+ T cell clonotypes

Bivalent COVID vaccines containing mRNA for ancestral and Omicron BA. 5 spike proteins do not induce stronger T cell responses to Omicron BA. 5 spike proteins than monovalent vaccines that contain only ancestral spike mRNA. The reasons for …

[HTML] Bob1 maintains T follicular helper cells for long-term humoral immunity

Humoral immunity is vital for host protection, yet aberrant antibody responses can trigger harmful inflammation and immune-related disorders. T follicular helper (Tfh) cells, central to humoral immunity, have garnered significant attention for unraveling …

Understanding the basis of thermostability for enzyme “Nanoluc” towards designing industry-competent engineered variants

As a leading contender in the study of luminescence, nanoluciferase has recently attracted attention and proven effective in a wide variety of research areas. Although numerous attempts have been made to improve activity, there has yet to be a …

Mass spectrometry study on SARS-CoV-2 recombinant vaccine with comprehensive separation techniques to characterize complex heterogeneity

Abstract SARS-CoV-2, the causative agent of COVID-19, has imposed a major public health threat, which needs effective therapeutics and vaccination strategies. Several potential candidate vaccines being rapidly developed are in clinical evaluation and …

[HTML] Production and Immunogenicity Assessment of LTp50: An Escherichia coli-Made Chimeric Antigen Targeting S1-and S2-Epitopes from the SARS-CoV-2/BA. 5 Spike …

Subunit vaccines stand as a leading approach to expanding the current portfolio of vaccines to fight against COVID-19, seeking not only to lower costs but to achieve long-term immunity against variants of concern and have the main attributes that …

[HTML] T cell specificity and cross-reactivity–implications in physiology and pathology

T cells are pivotal in orchestrating adaptive immune responses against a myriad of threats. Their ability to recognize antigens presented by specialized antigen-presenting cells (APCs), discern between self and non-self, and regulate and execute tailored immune responses lies at the heart of our immunological defenses. At the forefront of T cell function is the T cell receptor (TCR), a complex molecular machinery tasked with the daunting challenge of discriminating between an …

[PDF] scGREAT: Transformer-Based Deep-Language Model for Gene Regulatory Network Inference from Single-Cell Transcriptomics

Gene regulatory networks (GRNs) involve complex and multi-layer regulatory interactions between regulators and their target genes. Precise knowledge of GRNs is important in understanding cellular processes and molecular functions. Recent …

[HTML] FGBERT: Function-Driven Pre-trained Gene Language Model for Metagenomics

Metagenomic data, comprising mixed multi-species genomes, are prevalent in diverse environments like oceans and soils, significantly impacting human health and ecological functions. However, current research relies on K-mer representations …

An ensemble‐based approach to estimate confidence of predicted protein–ligand binding affinity values

When designing a machine learning‐based scoring function, we access a limited number of protein‐ligand complexes with experimentally determined binding affinity values, representing only a fraction of all possible protein‐ligand complexes …

[PDF] Canine major histocompatibility complex class I (MHC-I) diversity landscape

The genes of the Major Histocompatibility Complex class I (MHC-I) are among the most diverse in the mammalian genome, playing a crucial role in immunology. Understanding the diversity landscape of MHC-I is therefore of paramount …

[HTML] Self-supervised Visualisation of Medical Image Datasets

Self-supervised learning methods based on data augmentations, such as SimCLR, BYOL, or DINO, allow obtaining semantically meaningful representations of image datasets and are widely used prior to supervised fine-tuning. A recent self …

APE-Gen2. 0: Expanding Rapid Class I Peptide–Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide …

The recognition of peptides bound to class I major histocompatibility complex (MHC-I) receptors by T-cell receptors (TCRs) is a determinant of triggering the adaptive immune response. While the exact molecular features that drive the TCR recognition …

[PDF] The antibodies 3D12 and 4D12 recognise distinct epitopes and conformations of HLA-E

The commonly used antibodies 3D12 and 4D12 recognise the human leukocyte antigen E (HLA-E) protein. These antibodies bind distinct epitopes on HLA-E and differ in their ability to bind alleles of the major histocompatibility complex E (MHC-E) …

Anti-PD-1 therapy triggers Tfh cell–dependent IL-4 release to boost CD8 T cell responses in tumor-draining lymph nodes

Anti-PD-1 therapy targets intratumoral CD8+ T cells to promote clinical responses in cancer patients. Recent evidence suggests an additional activity in the periphery, but the underlying mechanism is unclear. Here, we show that anti-PD-1 mAb enhances …

[HTML] CD39hi identifies an exhausted tumor-reactive CD8+ T cell population associated with tumor progression in human gastric cancer

The ectonucleotidase CD39 has been regarded as a promising immune checkpoint in solid tumors. However, the expression of CD39 by tumor-infiltrating CD8+ T cells as well as their potential roles and clinical implications in human gastric cancer (GC) …

Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system

The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge—gathered from decades of detailed biochemical studies—allows us to obtain functional insights, focusing on …

[HTML] DeepMCGCN: Multi-channel Deep Graph Neural Networks

Graph neural networks (GNNs) have shown powerful capabilities in modeling and representing graph structural data across various graph learning tasks as an emerging deep learning approach. However, most existing GNNs focus on single-relational graphs and fail to fully utilize the rich and diverse relational information present in real-world graph data. In addition, deeper GNNs tend to suffer from overfitting and oversmoothing issues, leading to degraded model performance. To …

[PDF] Sequence modeling and design from molecular to genome scale with Evo

The genome is a sequence that completely encodes the DNA, RNA, and proteins that orchestrate the function of a whole organism. Advances in machine learning combined with massive datasets of whole genomes could enable a biological foundation model that accelerates the mechanistic understanding and generative design of complex molecular interactions. We report Evo, a genomic foundation model that enables prediction and generation tasks from the molecular to genome …

[PDF] Substrate Scope Contrastive Learning: Repurposing Human Bias to Learn Atomic Representations

Learning molecular representation is a critical step in molecular machine learning that significantly influences modeling success, particularly in data-scarce situations. The concept of broadly pre-training neural networks has advanced fields such as computer vision, natural language processing, and protein engineering. However, similar approaches for small organic molecules have not achieved comparable success. In this work, we introduce a novel pre-training strategy, substrate scope …

[HTML] Descriptor-augmented machine learning for enzyme-chemical interaction predictions

Descriptors play a pivotal role in enzyme design for the greener synthesis of biochemicals, as they could characterize enzymes and chemicals from the physicochemical and evolutionary perspective. This study examined the effects of various descriptors on the performance of Random Forest model used for enzyme-chemical relationships prediction. We curated activity data of seven specific enzyme families from the literature and developed the pipeline for evaluation the machine …

[PDF] BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning

Recent research trends in computational biology have increasingly focused on integrating text and bio-entity modeling, especially in the context of molecules and proteins. However, previous efforts like BioT5 faced challenges in generalizing across diverse tasks and lacked a nuanced understanding of molecular structures, particularly in their textual representations (eg, IUPAC). This paper introduces BioT5+, an extension of the BioT5 framework, tailored to enhance biological …

[PDF] Short-term load forecasting for power systems with high-penetration renewables based on multivariate data slicing transformer neural network

Introduction: The characteristics of intermittency and volatility brought by a high proportion of renewable energy impose higher requirements on load forecasting in modern power system. Currently, load forecasting methods mainly include statistical models and machine learning methods, but they exhibit relative rigidity in handling the uncertainty, volatility, and nonlinear relationships of new energy, making it difficult to adapt to instantaneous load changes and the complex impact of …

[HTML] Utilizing murine dendritic cell line DC2. 4 to evaluate the immunogenicity of subunit vaccines in vitro

Subunit vaccines hold substantial promise in controlling infectious diseases, due to their superior safety profile, specific immunogenicity, simplified manufacturing processes, and well-defined chemical compositions. One of the most important end …

[HTML] Modulation of cytomegalovirus immune evasion identifies direct antigen presentation as the predominant mode of CD8 T-cell priming during immune reconstitution …

Cytomegalovirus (CMV) infection is the most critical infectious complication in recipients of hematopoietic cell transplantation (HCT) in the period between a therapeutic hematoablative treatment and the hematopoietic reconstitution of the …

Innovations and trends in antibody repertoire analysis

Highlights•Functional screens integrate with single cell BCR-sequencing and transcriptomics.•Bottom-up and top-down MS enable comprehensive profiling of circulating antibodies.•Antibody repertoire studies drive artificial intelligence aimed at therapeutic design.Monoclonal antibodies have revolutionized the treatment of human diseases, which has made them the fastest-growing class of therapeutics, with global sales expected to reach $346.6 billion USD by 2028. Advances in …

[PDF] Investigating the mechanisms of antibody binding to alpha-synuclein for the treatment of Parkinson's Disease

Parkinson's Disease (PD) is an idiopathic neurodegenerative disorder with the second-highest prevalence rate behind Alzheimer's Disease. The pathophysiological hallmarks of PD are both degeneration of dopaminergic neurons in the substantia nigra pars compacta and the inclusion of misfolded alpha-synuclein (α-syn) aggregates known as Lewy bodies. Despite decades of research for potential PD treatments, none have been developed, and developing new therapeutic agents is a …

[HTML] Protocol for structural modeling of antibody to human leukocyte antigen interaction using discovery and targeted cross-linking mass spectrometry

Cross-linking mass spectrometry (XL-MS) provides low-resolution structural information to model protein structures. Here, we present a protocol to identify cross-links of purified antibody binding to purified human leukocyte antigen (HLA). We …

Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques

The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory activity, making them promising candidates for therapeutic applications. Identifying their binding mode is essential for their development. Experimental structural techniques are effective to get such information, but they are …

[HTML] Protein Multimer Structure Prediction via Prompt Learning

Understanding the 3D structures of protein multimers is crucial, as they play a vital role in regulating various cellular processes. It has been empirically confirmed that the multimer structure prediction~(MSP) can be well handled in a step-wise …

IsoForma: An R Package for Quantifying and Visualizing Positional Isomers in Top-Down LC-MS/MS Data

Proteoforms, the different forms of a protein with sequence variations including post-translational modifications (PTMs), execute vital functions in biological systems, such as cell signaling and epigenetic regulation. Advances in top-down mass …

AI-Assisted Methods for Protein Structure Prediction and Analysis

Proteins are the workhorses of cells. Their sequence is determined by the genetic code embedded in the DNA, which translates it faithfully into a string of amino acids known as the primary structure of proteins. But for proteins to achieve functional …

[PDF] Expanding the repertoire reveals recurrent, cryptic and hematopoietic HLA class I minor histocompatibility antigens

Allogeneic stem cell transplantation (alloSCT) is a curative treatment for hematological malignancies. After HLA-matched alloSCT, anti-tumor immunity is caused by donor T cells recognizing polymorphic peptides, designated minor …

[PDF] Protective effect and molecular mechanisms of human non-neutralizing cross-reactive spike antibodies elicited by SARS-CoV-2 mRNA vaccination

Neutralizing antibodies correlate with protection against SARS-CoV-2. Recent studies, however, show that binding antibody titers, in the absence of robust neutralizing activity, also correlate with protection from disease progression. Non …

[PDF] HDAC1 controls the generation and maintenance of effector-like CD8+ T cells during chronic viral infection

CD8+ T cell exhaustion is a complex process that involves the differentiation of persistently activated CD8+ T cells into functionally distinct cell subsets. Here, we investigated the role of the key epigenetic regulator histone deacetylase 1 (HDAC1) …

[PDF] The follicular dendritic cell: At the germinal center of autoimmunity?

Autoimmune diseases strain healthcare systems worldwide as their incidence rises, and current treatments put patients at risk for infections. An increased understanding of autoimmune diseases is required to develop targeted therapies that do not impair …

[PDF] Compartment-Specific Antibody Correlates of Protection to SARS-CoV-2 Omicron in Macaques

Antibodies represent a primary mediator of protection against respiratory viruses such as SARS-CoV-2. Serum neutralizing antibodies (NAbs) are often considered a primary correlate of protection. However, detailed antibody profiles including …

[PDF] mRNA-delivered consensus allergens induce a neutralizing IgG response against food and pollen allergens

Pollen-food allergy syndrome (PFAS) affects a significant proportion of the global population with a major health and socioeconomic impact. Patients are generally treated against the major sensitized allergen which does not warrant protection …

[PDF] Computational and Machine Learning Methods for Understanding Gene Regulation and Variant Effects

The field of genomics has been advancing at a fast pace ever since the development ofhigh-throughput sequencing technologies. While we have access to more data than ever before, the number of open questions has only increased. In this dissertation, I present novel machine learning techniques to draw insights from genomic data. First, I tackle the analysis of alternative splicing—a crucial but overlooked step in gene regulation—from short-read single-cell RNA-seq data. To …

[PDF] Illuminating the functional landscape of the dark proteome across the Animal Tree of Life through natural language processing models

Understanding how coding genes and their functions evolve over time is a key aspect of evolutionary biology. Protein coding genes poorly understood or characterized at the functional level may be related to important evolutionary innovations, potentially leading to incomplete or inaccurate models of evolutionary change, and limiting the ability to identify conserved or lineage-specific features. Homology-based methodologies often fail to transfer functional annotations in a …

A Transferability-Based Method for Evaluating the Protein Representation Learning

Self-supervised pre-trained language models have recently risen as a powerful approach in learning protein representations, showing exceptional effectiveness in various biological tasks, such as drug discovery. Amidst the evolving trend in protein language model development, there is an observable shift towards employing large-scale multimodal and multitask models. However, the predominant reliance on empirical assessments using specific benchmark datasets for evaluating these …

[PDF] PocketGen: Generating Full-Atom Ligand-Binding Protein Pockets

Designing small-molecule-binding proteins, such as enzymes and biosensors, is crucial in protein biology and bioengineering. Generating high-fidelity protein pockets areas where proteins interact with ligand molecules, is challenging due to …

[PDF] Evaluating generalizability of artificial intelligence models for molecular datasets

Deep learning has made rapid advances in modeling molecular sequencing data. Despite achieving high performance on benchmarks, it remains unclear to what extent deep learning models learn general principles and generalize to previously …

[PDF] Proteasomal cleavage prediction: state-of-the-art and future directions

Epitope vaccines are a promising approach for precision treatment of pathogens, cancer, autoimmune diseases, and allergies. Effectively designing such vaccines requires accurate proteasomal cleavage prediction to ensure that the epitopes included in the vaccine trigger an immune response. The performance of proteasomal cleavage predictors has been steadily improving over the past decades owing to increasing data availability and methodological advances. In this review, we …

Prediction of SUMOylation Sites in Proteins From Language Model Representations

Sumoylation is an essential post-translational modification intimately involved in a diverse range of eukaryotic cellular mechanisms and plays a significant role in DNA repair. Some researchers hypothesize that a high level of SUMOylation events in cancer cells improves cells' chances for survival under stress conditions by regulating tumor-related proteins.

[PDF] Эффективность и безопасность препарата BCD-180, моноклонального антитела к TRBV9+ T-лимфоцитам, у пациентов с активным рентгенологическим …

Аннотация Цель исследования–оценить клиническую эффективность, безопасность, фармакокинетику, фармакодинамику и иммуногенность препарата сенипрутуг (BCD-180) у пациентов с активным рентгенологическим аксиальным спондилоартритом (р-аксСпА, или анкилозирующий спондилит).

[PDF] Circulating Tumor Reactive KIR+ CD8+ T cells Suppress Anti-Tumor Immunity in Patients with Melanoma

Effective anti-tumor immunity is largely driven by cytotoxic CD8+ T cells that can specifically recognize tumor antigens. However, the factors which ultimately dictate successful tumor rejection remain poorly understood. Here we identify a subpopulation of CD8+ T cells which are tumor antigen-specific in patients with melanoma but resemble KIR+ CD8+ T cells with a regulatory function (Tregs). These tumor antigen-specific KIR+ CD8+ T cells are detectable in both the tumor and the …

Multi-omic profiling of follicular lymphoma reveals changes in tissue architecture and enhanced stromal remodeling in high-risk patients

Follicular lymphoma (FL) is a generally incurable malignancy that evolves from developmentally blocked germinal center (GC) B cells. To promote survival and immune escape, tumor B cells undergo significant genetic changes and extensively remodel the lymphoid microenvironment. Dynamic interactions between tumor B cells and the tumor microenvironment (TME) are hypothesized to contribute to the broad spectrum of clinical behaviors observed among FL patients. Despite the urgent …

Exploring the molecular and immune-landscape of lung cancer associated with cystic airspaces

To explore the molecular biological characteristics of lung cancer associated with cystic airspaces (LCCA) and its potential roles on prognosis. A total of 165 LCCAs and 201 non-LCCAs were enrolled in this study. Bulk RNA sequencing was implemented in eight LCCAs and nine non-LCCAs to explore the differentially expressed genes. TCGA data were used to analyze LCCA-specific genes that associated with overall survival (OS). The median age was 60 (IQR 53 to 65) years in …

Murine MHC-Deficient Nonobese Diabetic Mice Carrying Human HLA-DQ8 Develop Severe Myocarditis and Myositis in Response to Anti–PD-1 Immune Checkpoint …

Myocarditis has emerged as an immune-related adverse event of immune checkpoint inhibitor (ICI) cancer therapy associated with significant mortality. To ensure patients continue to safely benefit from life-saving cancer therapy, an …

[PDF] Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers …

[HTML] Cancer neoepitopes viewed through negative selection and peripheral tolerance: a new path to cancer vaccines

A proportion of somatic mutations in tumors create neoepitopes that can prime T cell responses that target the MHC I–neoepitope complexes on tumor cells, mediating tumor control or rejection. Despite the compelling centrality of neoepitopes to cancer …

[PDF] Intranasal Epitope‐Polymer Vaccine Lodges Resident Memory T Cells Protecting against Influenza Virus

Intranasal vaccines, unlike injectable vaccines, boost immunity along the respiratory tract; this can significantly limit respiratory virus replication and shedding. There remains a need to develop mucosal adjuvants and vaccine delivery systems that are …

[HTML] A Multidisciplinary Structural Approach to the Identification of the Haemophilus influenzae Type b Capsular Polysaccharide Protective Epitope

Glycoconjugate vaccines so far licensed are generally composed of a native or size-reduced capsular polysaccharide conjugated to carrier proteins. Detailed information on the structural requirements necessary for CPS recognition is becoming the key to …

[PDF] Neutralization of SARS-CoV-2 BA. 2.86 and JN. 1 by CF501 adjuvant-enhanced immune responses targeting the conserved epitopes in ancestral RBD

The emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariants BA. 2.86 and JN. 1 raise concerns regarding their potential to evade immune surveillance and spread globally. Here, we test sera from rhesus …

[HTML] Reanalysis of Immunopeptidomics Datasets Provides Mechanistic Insight into TAPBPR-Mediated Peptide Editing on HLA-A,-B and-C Molecules

Background Major histocompatibility class I (MHC-I, human leukocyte antigen [HLA]-I in humans) molecules present small fragments of the proteome on the cell surface for immunosurveillance, which is pivotal to control infected and malignant cells …

[PDF] Profiling of linear B-cell epitopes against human coronaviruses in pooled sera sampled early in the COVID-19 pandemic

Background: Antibodies play a key role in the immune defence against infectious pathogens. Understanding the underlying process of B cell recognition is not only of fundamental interest; it supports important applications within diagnostics and …

[HTML] Protein embedding based alignment

Purpose Despite the many progresses with alignment algorithms, aligning divergent protein sequences with less than 20–35% pairwise identity (so called" twilight zone") remains a difficult problem. Many alignment algorithms have been using substitution …

[HTML] Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge

Accurate prediction of protein-ligand binding structures, a task known as molecular docking is crucial for drug design but remains challenging. While deep learning has shown promise, existing methods often depend on holo-protein structures (docked …

[HTML] Exploring Free Energies of Specific Protein Conformations Using the Martini Force Field

Coarse-grained (CG) level molecular dynamics simulations are routinely used to study various biomolecular processes. The Martini force field is currently the most widely adopted parameter set for such simulations. The functional form of this and …

[PDF] Ensemble-based enzyme design can recapitulate the effects of laboratory directed evolution in silico

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we use …

[PDF] PTM-Mamba: A PTM-Aware Protein Language Model with Bidirectional Gated Mamba Blocks

Proteins serve as the workhorses of living organisms, orchestrating a wide array of vital functions. Post-translational modifications (PTMs) of their amino acids greatly influence the structural and functional diversity of different protein types and uphold …

[PDF] A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models

The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them appropriately in biomedical research, such as protein-protein interaction studies, protein design, and drug discovery. With the advent of more accurate protein complex (multimer) prediction tools, such as AlphaFold2-Multimer and ESMFold, the …

[PDF] Rational structure-guided design of a blood stage malaria vaccine immunogen presenting a single epitope from PfRH5

Despite recent success in licencing of two malaria vaccines, there continues to be an urgent need for improved vaccine immunogens as the world aims for malaria eradication. The invasion of erythrocytes by Plasmodium falciparum is an essential step in the life cycle of the parasite, preceding symptoms of disease and parasite transmission. Antibodies which target the PfRH5 protein are highly effective at preventing erythrocyte invasion and the most effective growth-inhibitory antibodies …

Cyclization Scaffolding for Improved Vaccine Immunogen Stability: Application to Tau Protein in Alzheimer's Disease

Effective scaffolding of immunogens is crucial for generating conformationally selective antibodies through active immunization, particularly in the treatment of protein misfolding diseases such as Alzheimer's and Parkinson's disease. Previous computational work has revealed that a disorder-prone region of the tau protein, when in a stacked form, is predicted to structurally resemble a small, soluble protofibril, having conformational properties similar to those of experimental in vitro …

[PDF] Real-Time Determination of Intracellular cAMP Reveals Functional Coupling of Gs Protein to the Melatonin MT1 Receptor

Melatonin is a neuroendocrine hormone that regulates the circadian rhythm and many other physiological processes. Its functions are primarily exerted through two subtypes of human melatonin receptors, termed melatonin type-1 (MT1) and type-2 (MT2) receptors. Both MT1 and MT2 receptors are generally classified as Gi-coupled receptors owing to their well-recognized ability to inhibit cAMP accumulation in cells. However, it remains an enigma as to why melatonin stimulates cAMP production in a …

[PDF] Applications of ML/DL overcoming current challenges in structure-based drug design

In the rapidly evolving landscape of drug discovery and development, the application of structure-based drug design (SBDD) methods has become increasingly crucial. Despite the advancements in this field, several challenges continue to impede progress, particularly in the areas of binding heterogeneity, targeted ligand development, and the exploration of the vast chemical space for drug-like molecules. This dissertation addresses these challenges by integrating traditional SBDD …

Induction of durable remission by dual immunotherapy in SHIV-infected ART-suppressed macaques

The eradication of the viral reservoir represents the major obstacle to the development of a clinical cure for established HIV-1 infection. Here, we demonstrate that the administration of Anktiva (N-803) and broadly neutralizing antibodies …

TGF-β specifies TFH versus TH17 cell fates in murine CD4+ T cells through c-Maf

T follicular helper (TFH) cells are essential for effective antibody responses, but deciphering the intrinsic wiring of mouse TFH cells has long been hampered by the lack of a reliable protocol for their generation in vitro. We report that transforming …

PhenoLinker: Phenotype-Gene Link Prediction and Explanation using Heterogeneous Graph Neural Networks

The association of a given human phenotype to a genetic variant remains a critical challenge for biology. We present a novel system called PhenoLinker capable of associating a score to a phenotype-gene relationship by using heterogeneous …

Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols

Successful immunotherapy relies on triggering complex responses involving T cell dynamics in tumors and the periphery. Characterizing these responses remains challenging using static human single-cell atlases or mouse models. To address this …

[HTML] Single-cell RNA sequencing reveals myeloid and T cell co-stimulation mediated by IL-7 anti-cancer immunotherapy

Background Immune checkpoint inhibitors unleash inhibitory signals on T cells conferred by tumors and surrounding stromal cells. Despite the clinical efficacy of checkpoint inhibitors, the lack of target expression and persistence of …

Antigen Presenting Cell Mimetic Lipid Nanoparticles for Rapid mRNA CAR T Cell Cancer Immunotherapy

CAR T cell therapy has achieved remarkable clinical success for the treatment of hematological malignancies. However, producing these bespoke cancer‐killing cells is a complicated ex vivo process involving leukapheresis, artificial T cell activation …

[PDF] Spatial analysis reveals combinative role for natural killer and CD8 T cells in antitumor immunity despite profound MHC class I loss in non-small cell lung cancer

Background. MHC class I (MHC-I) loss is frequent in NSCLC and renders tumor cells resistant to T cell lysis. NK cells kill MHC-I deficient tumor cells, and although previous studies indicate their presence in NSCLC tumor margins, they were also …

[HTML] Altered receptor binding, antibody evasion and retention of T cell recognition by the SARS-CoV-2 XBB. 1.5 spike protein

Abstract The XBB. 1.5 variant of SARS-CoV-2 has rapidly achieved global dominance and exhibits a high growth advantage over previous variants. Preliminary reports suggest that the success of XBB. 1.5 stems from mutations within its spike …

[HTML] Computational drug repositioning identifies niclosamide and tribromsalan as inhibitors of Mycobacterium tuberculosis and Mycobacterium abscessus

Tuberculosis (TB) is still a major global health challenge, killing over 1.5 million people each year, and hence, there is a need to identify and develop novel treatments for Mycobacterium tuberculosis (M. tuberculosis). The prevalence of …

Regulatory T cells targeting a pathogenic MHC class II: Insulin peptide epitope postpone spontaneous autoimmune diabetes

© 2024 Obarorakpor_, Patel, Boyarov, Amarsaikhan, Cepeda, Eastes, Robertson, Johnson, Yang, Tang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution …

High-resolution epitope mapping of commercial antibodies to ANCA antigens by yeast surface display

Epitope mapping provides critical insight into antibody-antigen interactions. Epitope mapping of autoantibodies from patients with autoimmune diseases can help elucidate disease immunogenesis and guide the development of antigen-specific …

[PDF] Accurate cell type annotation for single‐cell chromatin accessibility data via contrastive learning and reference guidance

Recent advances in single‐cell chromatin accessibility sequencing (scCAS) technologies have resulted in new insights into the characterization of epigenomic heterogeneity and have increased the need for automatic cell type annotation …

Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials.

This letter gives results on improving protein-ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural network potential and molecular mechanics methodology (NNP/MM). We …

[PDF] MARS and RNAcmap3: The Master Database of All Possible RNA Sequences Integrated with RNAcmap for RNA Homology Search

Recent success of AlphaFold2 in protein structure prediction relied heavily on co-evolutionary information derived from homologous protein sequences found in the huge, integrated database of protein sequences (Big Fantastic Database). In …

[HTML] Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation

We introduce Bonito, an open-source model for conditional task generation: the task of converting unannotated text into task-specific training datasets for instruction tuning. Our goal is to enable zero-shot task adaptation of large language models on …

Nano-Differential Scanning Fluorimetry as a tool for assessment of refolded antibody fragments: a case study for anti-Pfs25 single-chain antibodies.

Abstract Differential Scanning Fluorimetry (DSF) is a valuable and versatile tool in the field of protein and antibody stability studies, providing valuable insights into their thermal stability and aids in the optimization of experimental conditions for varied applications. Antibody fragments provide armamentarium for researchers and practitioners across various fields, enabling advancements in medicine, diagnostics, research, and industrial applications. In the present study, single chain, m4B7 and …

[HTML] Learning Associative Memories with Gradient Descent

This work focuses on the training dynamics of one associative memory module storing outer products of token embeddings. We reduce this problem to the study of a system of particles, which interact according to properties of the data distribution and correlations between embeddings. Through theory and experiments, we provide several insights. In overparameterized regimes, we obtain logarithmic growth of the``classification margins.''Yet, we show that imbalance in token frequencies and …

[PDF] Modeling of Multiport Heteroassociative Memory (MBHM) on the Basis of Equivalence Models Implemented on Vector-Matrix Multipliers

The work is devoted to consideration of issues related to associative processing of information for the purpose of hardware and software implementation of relevant mathematical, simulation and physical models of associative memory. On the basis of a review of known publications, including those in which equivalence models of associative and heteroassociative memory were considered and their advantages were shown, the need for further research of such models of AM or HAM and …

[PDF] Deep Graph Learning-Based Surrogate Model for Inverse Modeling of Fractured Reservoirs

Inverse modeling can estimate uncertain parameters in subsurface reservoirs and provide reliable numerical models for reservoir development and management. The traditional simulationbased inversion method usually requires numerous numerical simulations, which is time-consuming. Recently, deep learning-based surrogate models have been widely studied as an alternative to numerical simulation, which can significantly improve the solving efficiency of inversion. However, for reservoirs …

Big Data Analytics in Healthcare Sector: Potential Strength and Challenges

In current era with rapid advancement in data acquisition and sensing technologies healthcare institute and hospitals have started collecting enormous data about their patients. The issue with healthcare data is that it has an unprecedented diversity in terms of its data formats, data types, and the rate at which it needs be analysed to deliver the required data. This variety is not just limited by its amount. Given the variety and number of sources that really are constantly expanding, it is now difficult …

[PDF] Prenatal Exposure to Psychotropics and Analgesics on Cognitive, Linguistic and Educational Outcomes–a Systematic Review with Focus on Validity and Reliability of …

Objective: To provide an overview of the observational studies on cognitive, linguistic, and educational outcomes following prenatal exposure to psychotropics and analgesics, including reporting of outcome measure validity and reliability. Study …

[PDF] DeepSP: Deep Learning-Based Spatial Properties to Predict Monoclonal Antibody Stability

Therapeutic antibody development, manufacturing, and administration face challenges due to high viscosities and aggregation tendencies often observed in highly concentrated antibody solutions. This poses a particular problem for subcutaneous administration, which requires low-volume and high-concentration formulations. The spatial charge map (SCM (mAbs, 8 (1)(2015), pp. 43-48)) and spatial aggregation propensity (SAP (PNAS. 2009; 106: 11937-42) are two …

[PDF] Exploring drug sensitivity and Enhertu resistance in breast cancer tissue using ex vivo cultures.

Ex vivo tumor tissue cultures, such as organoids or explants, hold promise as a drug screening platform for functional precision diagnostics. In this project, we have employed such cultures to investigate functional and molecular properties of breast cancer (BC) tissue with distinct sensitivity to Enhertu, an antibody-drug conjugate (ADC). ADCs are a novel class of cancer therapy, that combines the specificity of monoclonal antibodies with the cytotoxic effects of chemotherapeutic drugs. As of …

[HTML] LAP: Liability Antibody Profiler by sequence & structural mapping of natural and therapeutic antibodies

Antibody-based therapeutics must not undergo chemical modifications that would impair their efficacy or hinder their developability. A commonly used technique to de-risk lead biotherapeutic candidates annotates chemical liability motifs on their …

[PDF] Exploring molecular determinants and pharmacokinetic properties of IgG1-scFv bispecific antibodies

Bispecific antibodies (BsAbs) capable of recognizing two distinct epitopes or antigens offer promising therapeutic options for various diseases by targeting multiple pathways. The favorable pharmacokinetic (PK) properties of monoclonal antibodies (mAbs) are crucial, as they directly influence patient safety and therapeutic efficacy. For numerous mAb therapeutics, optimization of neonatal Fc receptor (FcRn) interactions and elimination of unfavorable molecular properties …

[HTML] Inactivation of cytidine triphosphate synthase 1 prevents fatal auto-immunity in mice

De novo synthesis of the pyrimidine, cytidine triphosphate (CTP), is crucial for DNA/RNA metabolism and depends on the CTP synthetases, CTPS1 and− 2. Partial CTPS1 deficiency in humans has previously been shown to lead to immunodeficiency, with impaired expansion of T and B cells. Here, we examine the effects of conditional and inducible inactivation of Ctps1 and/or Ctps2 on mouse embryonic development and immunity. We report that deletion of Ctps1, but not …

[PDF] Capacity of the Hebbian-Hopfield network associative memory

In\cite {Hop82}, Hopfield introduced a\emph {Hebbian} learning rule based neural network model and suggested how it can efficiently operate as an associative memory. Studying random binary patterns, he also uncovered that, if a small fraction of errors is tolerated in the stored patterns retrieval, the capacity of the network (maximal number of memorized patterns, $ m $) scales linearly with each pattern's size, $ n $. Moreover, he famously predicted $\alpha_c=\lim_ {n\rightarrow\infty}\frac …

[PDF] Enhancing TCR specificity predictions by combined pan-and peptide-specific training, loss-scaling, and sequence similarity integration

Predicting the interaction between Major Histocompatibility Complex (MHC) class I-presented peptides and T-cell receptors (TCR) holds significant implications for vaccine development, cancer treatment, and autoimmune disease therapies …

[HTML] Notch2 controls developmental fate choices between germinal center and marginal zone B cells upon immunization

Sustained Notch2 signals induce trans-differentiation of Follicular B (FoB) cells into Marginal Zone B (MZB) cells in mice, but the physiology underlying this differentiation pathway is still elusive. Here, we demonstrate that most B cells receive …

[PDF] Th17 cells with a pathogenic signature in joints of ZAP-70 mutant arthritic mice harbor unique TCR repertoires that share features with WT Tregs

Autoimmune diseases such as rheumatoid arthritis (RA) represent a significant source of worldwide morbidity and disability. Despite extensive research, the molecular mechanisms underlying the development of self-reactive T cells and the …

PRMT5 Promotes T follicular helper Cell Differentiation and Germinal Center Responses during Influenza Virus Infection

Protein arginine methyltransferases (PRMTs) modify diverse protein targets and regulate numerous cellular processes; yet, their contributions to individual effector T cell responses during infections are incompletely understood. In this study, we …

Peripheral blood TCRβ repertoire, IL15, IL2 and soluble ligands for NKG2D activating receptor predict efficacy of ICI in lung cancer

The development of immune checkpoints inhibitors (ICIs) has changed the therapeutic paradigm of lung cancer (LC), becoming the standard of treatment for previously untreated advanced non-small cell lung cancer (NSCLC) without …

[PDF] Physics-driven structural docking and protein language models accelerate antibody screening and design for broad-spectrum antiviral therapy

Therapeutic antibodies have become one of the most influential therapeutics in modern medicine to fight against infectious pathogens, cancer, and many other diseases. However, experimental screening for highly efficacious targeting …

[PDF] Defining the T cell transcriptional landscape in pediatric liver transplant rejection at single cell resolution

Acute cellular rejection (ACR) affects> 80% of pediatric liver transplant recipients within 5 years, and late ACR is associated with graft failure. Traditional anti-rejection therapy for late ACR is ineffective and has remained unchanged for six decades …

Protein Design Using Structure-Prediction Networks: AlphaFold and RoseTTAFold as Protein Structure Foundation Models

Designing proteins with tailored structures and functions is a long-standing goal in bioengineering. Recently, deep learning advances have enabled protein structure prediction at near-experimental accuracy, which has catalyzed progress in protein …

[PDF] Evaluating the representational power of pre-trained DNA language models for regulatory genomics

The emergence of genomic language models (gLMs) offers an unsupervised approach to learn a wide diversity of cis-regulatory patterns in the non-coding genome without requiring labels of functional activity generated by wet-lab …

[PDF] Training Language Model Agents without Modifying Language Models

Researchers and practitioners have recently reframed powerful Large Language Models (LLMs) as agents, enabling them to automate complex tasks largely via the use of specialized functions. To facilitate the development of LLM agents, we present …

[PDF] Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models

Multi-modal foundation models like OpenFlamingo, LLaVA, and GPT-4 are increasingly used for various real-world tasks. Prior work has shown that these models are highly vulnerable to adversarial attacks on the vision modality. These …

[PDF] An integrative approach to protein sequence design through multiobjective optimization

With recent methodological advances in the field of computational protein design, in particular those based on deep learning, there is an increasing need for frameworks that allow for coherent, direct integration of different models and objective functions …

[PDF] Repetition Improves Language Model Embeddings

Recent approaches to improving the extraction of text embeddings from autoregressive large language models (LLMs) have largely focused on improvements to data, backbone pretrained language models, or improving task …

[PDF] InstructEdit: Instruction-based Knowledge Editing for Large Language Models

Knowledge editing for large language models can offer an efficient solution to alter a model's behavior without negatively impacting the overall performance. However, the current approach encounters issues with limited generalizability across tasks …

[HTML] The Da Vinci Code of Large Pre-trained Language Models: Deciphering Degenerate Knowledge Neurons

This study explores the mechanism of factual knowledge storage in pre-trained language models (PLMs). Previous research suggests that factual knowledge is stored within multi-layer perceptron weights, and some storage units exhibit …

[HTML] Engineering β-catenin-derived peptides for α-catenin binding

The complex formed by the β-catenin and α-catenin adaptor proteins acts as a molecular bridge that enables E-cadherin-based cell–cell adhesion assembly and maintenance in the epithelial tissue. This occurs through the interaction between the intracellular domain of E-cadherin and β-catenin on the one hand and between F-actin and α-catenin on the other hand. In addition to its role in cell–cell adhesion formation, it has been reported that E-cadherin mediates breast cancer cell …

Computational Mutagenesis of Antibody Fragments: Disentangling Side Chains from ΔΔ G Predictions

The development of highly potent antibodies and antibody fragments as binding agents holds significant implications in fields such as biosensing and biotherapeutics. Their binding strength is intricately linked to the arrangement and composition of residues at the binding interface. Computational techniques offer a robust means to predict the three-dimensional structure of these complexes and to assess the affinity changes resulting from mutations. Given the interdependence of …

[PDF] Towards Bone Regeneration: Understanding the Nucleating Ability of Proline-rich peptides in Biomineralisation

Obtaining rapid mineralisation is a challenge in current bone graft materials, which has been attributed to the difficulty of guiding the biological processes towards osteogenesis. Amelogenin, a key protein in enamel formation, inspired the design of two intrinsically disordered peptides (P2 and P6) that enhance in vivo bone formation, but the process is not fully understood. In this study, we have elucidated the mechanism by which these peptides induce improved mineralisation. Our …

Advancement in Bioinformatics Tools in the Era of Genome Editing-Based Functional Genomics

The discovery of the Sanger DNA sequencing technique has paved the way toward a new dimension in the field of molecular biology and the genesis of genomics. Further advancement in DNA sequencing technology has led to whole genome sequencing of several crop plants starting from the genome of rice, a major stable crop of the world. Subsequently, the development of next-generation sequencing technologies in the last couple of decades has contributed to the genomic revolution by generating …

[PDF] RSC Medicinal Chemistry

Proteins involved in immune checkpoint pathways, such as CTLA4, PD1, and PD-L1, have become important targets for cancer immunotherapy; however, development of small molecule drugs targeting these pathways has proven difficult due to the nature of their protein–protein interfaces. Here, using a hierarchy of computational techniques, we design a cyclic peptide that binds CTLA4 and follow this with experimental verification of binding and biological activity, using bio-layer …

[PDF] The Impact of Crystal Phase Transition on the Hardness and Structure of Kidney Stones

Calcium oxalate kidney stones, the most prevalent type of kidney stones, undergo a multi-step process of crystal nucleation, growth, aggregation, and secondary transition. The secondary transition has been rather overlooked, and thus, the effects on the disease and the underlying mechanism remain unclear. Here, we show, by periodic micro-CT images of human kidney stones in an ex vivo incubation experiment, that the growth of porous aggregates of calcium oxalate dihydrate (COD) …

[HTML] ДОННЫЕ ОТЛОЖЕНИЯ ПОВЕРХНОСТНЫХ ВОДОТОКОВ МАЛМЫЖСКОГО ГОРНОГО МАССИВА

Методами рентгено-флюоресцентного, электронно-микроскопического, седиментационного анализов и лазерной дифрактометрии изучен состав донных отложений поверхностных водотоков участка Малмыжской гряды, выделенного под строительство горно-обогатительного комбината (Хабаровский край, Россия). Установлено, что донные отложения береговой зоны водотоков исследуемого участка характеризуются близким валовым …

[PDF] MAJOR ARTICLE

Immune cell interactions are pivotal events in immune response, ensuring appropriate immune activation and regulation either through secreting molecular messengers or direct cell-cell contact. For instance, the interactions between circulating monocytes and other immune cells participate in all stages of COVID-19 progression [1-3]. In COVID-19 patients, monocytes are attracted to sites of injury for macrophage replenishment and further recruit cytotoxic T cells and neutrophils by …

[HTML] A preliminary study of IgG4 expression and its prognostic significance in oral squamous cell carcinoma

IgG4, which plays a pivotal role in the progression of phenotypically diverse tumors, serves as a prognostic marker because of its influence on cancer immunity. Nevertheless, the functions of IgG4 in tongue squamous cell carcinoma (TSCC) remained to be identified. To evaluate the significance of IgG4 expression in TSCC, we performed immunohistochemical analysis of patients with TSCC (n= 50) to evaluate the correlation of IgG4 expression with patients' clinicopathological features …

[HTML] Recurrent UBE3C-LRP5 translocations in head and neck cancer with therapeutic implications

Head and neck cancer is a major cause of morbidity and mortality worldwide. The identification of genetic alterations in head and neck cancer may improve diagnosis and treatment outcomes. In this study, we report the identification and functional characterization of UBE3C-LRP5 translocation in head and neck cancer. Our whole transcriptome sequencing and RT-PCR analysis of 151 head and neck cancer tumor samples identified the LRP5-UBE3C and UBE3C-LRP5 fusion transcripts in 5.3% of …

[HTML] TCR β chain repertoire characteristic between healthy human CD4+ and CD8+ T cells

T cell is vital in the adaptive immune system, which relays on T-cell receptor (TCR) to recognize and defend against infection and tumors. T cells are mainly divided into well-known CD4+ and CD8+ T cells, which can recognize short peptide antigens presented by major histocompatibility complex (MHC) class II and MHC class I respectively in humoral and cell-mediated immunity. Due to the Human Leukocyte Antigen (HLA) diversity and restriction with peptides complexation, TCRs are quite …

[PDF] RiNALMo: General-Purpose RNA Language Models Can Generalize Well on Structure Prediction Tasks

Ribonucleic acid (RNA) plays a variety of crucial roles in fundamental biological processes. Recently, RNA has become an interesting drug target, emphasizing the need to improve our understanding of its structures and functions. Over the years …

[PDF] EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is …

[PDF] A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications

Geometric graph is a special kind of graph with geometric features, which is vital to model many scientific problems. Unlike generic graphs, geometric graphs often exhibit physical symmetries of translations, rotations, and reflections, making them …

[HTML] Machine learning-aided design and screening of an emergent protein function in synthetic cells

Abstract Recently, utilization of Machine Learning (ML) has led to astonishing progress in computational protein design, bringing into reach the targeted engineering of proteins for industrial and biomedical applications. However, the …

[PDF] PNAbind: Structure-based prediction of protein-nucleic acid binding using graph neural networks

The recognition and binding of nucleic acids (NAs) by proteins depends upon complementary chemical, electrostatic and geometric properties of the protein-NA binding interface. Structural models of protein-NA complexes provide insights into …

[PDF] Enhanced Drug Discovery Using Deep Learning with Integration of Distinct Data Modalities

Drug discovery stands as an important yet formidable challenge, requiring the optimization of molecular properties and the selection of optimal compounds. Traditional experimental and clinical trial approaches are marked by slow progression and high costs. Recent advances in deep learning techniques have shown considerable potential, promising to discover molecular properties and drug-target interactions. However, existing deep learning techniques for drug discovery …

[HTML] Computational Methods for Alignment and Integration of Spatially Resolved Transcriptomics Data

Most of the complex biological regulatory activities occur in three dimensions (3D). To better analyze biological processes, it is essential not only to decipher the molecular information of numerous cells but also to understand how their spatial contexts influence their behavior. With the development of spatially resolved transcriptomics (SRT) technologies, SRT datasets are being generated to simultaneously characterize gene expression and spatial arrangement information …

[PDF] A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks

Systematic characterization of biological effects to genetic perturbation is essential to the application of molecular biology and biomedicine. However, the experimental exhaustion of genetic perturbations on the genome-wide scale is challenging. Here, we show that TranscriptionNet, a deep learning model that integrates multiple biological networks to systematically predict transcriptional profiles to three types of genetic perturbations based on transcriptional profiles induced by genetic …

Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network

Accurately predicting protein-ATP binding residues is critical for protein function annotation and drug discovery. Computational methods dedicated to the prediction of binding residues based on protein sequence information have exhibited notable advancements in predictive accuracy. Nevertheless, these methods continue to grapple with several formidable challenges, including limited means of extracting more discriminative features and inadequate algorithms for integrating protein and …

Heterogeneous sampled subgraph neural networks with knowledge distillation to enhance double-blind compound-protein interaction prediction

Identifying binding compounds against a target protein is crucial for large-scale virtual screening in drug development. Recently, network-based methods have been developed for compound-protein interaction (CPI) prediction. However, they are difficult to be applied to unseen (ie, never-seen-before) proteins and compounds. In this study, we propose SgCPI to incorporate local known interacting networks to predict CPI interactions. SgCPI randomly samples the local CPI network of the query …

[PDF] Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey

The integration of biomolecular modeling with natural language (BL) has emerged as a promising interdisciplinary area at the intersection of artificial intelligence, chemistry and biology. This approach leverages the rich, multifaceted descriptions of biomolecules contained within textual data sources to enhance our fundamental understanding and enable downstream computational tasks such as biomolecule property prediction. The fusion of the nuanced narratives expressed through natural …

[HTML] Seq-RBPPred: Predicting RNA-Binding Proteins from Sequence

RNA-binding proteins (RBPs) can interact with RNAs to regulate RNA translation, modification, splicing, and other important biological processes. The accurate identification of RBPs is of paramount importance for gaining insights into the intricate mechanisms underlying organismal life activities. Traditional experimental methods to predict RBPs require a lot of time and money, so it is important to develop computational methods to predict RBPs. However, the existing approaches for RBP …

[HTML] Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions

Augmentation is an effective alternative to utilize the small amount of labeled protein data. However, most of the existing work focuses on design-ing new architectures or pre-training tasks, and relatively little work has studied data augmentation for …

[PDF] A novel lentiviral vector-based approach to generate chimeric antigen receptor T cells targeting Aspergillus fumigatus

Invasive aspergillosis (IA) is a common and deadly mold infection in immunocompromised patients. As morbidity and mortality of IA are primarily driven by poor immune defense, adjunct immunotherapies, such as chimeric antigen …

[HTML] Evidence for immune activation in pathogenesis of the HLA class II associated disease, podoconiosis

Available evidences suggest that podoconiosis is triggered by long term exposure of bare feet to volcanic red clay soil particles. Previous genome-wide studies in Ethiopia showed association between the HLA class II region and disease …

Unraveling the therapeutic benefit of sequenced chemo-immunotherapy

Combination immune-checkpoint inhibition with chemotherapy is a clinical standard, yet concurrent administration may limit the full benefit of immunotherapy by blunting the proliferation and differentiation of CD8 T cells. Identifying patients in whom …

CD4+ T cell activation distinguishes response to anti-PD-L1+ anti-CTLA4 therapy from anti-PD-L1 monotherapy

Cancer patients often receive a combination of antibodies targeting programmed death-ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen-4 (CTLA4). We conducted a window-of-opportunity study in head and neck squamous cell …

[PDF] Single-cell transcriptomics reveals altered myeloid cell profiles associated with the early establishment of leishmania reservoirs

Current drug regimens to treat visceral leishmaniasis (VL) are associated with a significant frequency of infection relapses, particularly in immunosuppressed patients. Understanding the cellular and tissue-specific persistence of Leishmania …

[PDF] Crosstalk between CD64+ MHCII+ macrophages and CD4+ T cells drives joint pathology during chikungunya

Communications between immune cells are essential to ensure appropriate coordination of their activities. Here, we observed the infiltration of activated macrophages into the joint-footpads of chikungunya virus (CHIKV)-infected animals …

Enhancing Generalizability in Protein–Ligand Binding Affinity Prediction with Multimodal Contrastive Learning

Improving the generalization ability of scoring functions remains a major challenge in protein–ligand binding affinity prediction. Many machine learning methods are limited by their reliance on single-modal representations, hindering a comprehensive …

[HTML] Dissecting the Conformational Stability of a Glycan Hairpin

Systematic structural studies of model oligopeptides revealed important aspects of protein folding and offered design principles to access non-natural materials. In the same way, the rules that regulate glycan folding could be established by studying …

CarbDisMut: database on neutral and disease-causing mutations in human carbohydrate-binding proteins

Protein-carbohydrate interactions are involved in several cellular and biological functions. Integrating structure and function of carbohydrate-binding proteins with disease-causing mutations help to understand the molecular basis of diseases …

Salp-J Colony Optimization-based advanced hybrid ensemble deep predictor with LSTM for protein structure prediction

Protein structure prediction (PSP) is a key concern in computational biology, which is considered a challenging task that is vital to determine the structure and the protein function since each protein possesses a definite shape, whereas the protein …

An efficient method for detecting membrane protein oligomerization and complex using 05SAR‐PAGE

Oligomerization is an important feature of proteins, which gives a defined quaternary structure to complete the biological functions. Although frequently observed in membrane proteins, characterizing the oligomerization state remains complicated …

β-Barrel formation examined through β-hairpin interactions with lipid vesicles

The interactions of β-structures with membranes are not as well understood as those of α-helical structures. Porin-type β-barrels are membrane-spanning structures that form a pore in a phospholipid bilayer. These β-barrels are most often formed by 4–6 …

Cryo-EM structures of the glycosyltransferase ArnC reveal the mechanistic basis of catalysis for undecaprenyl phosphate glycosylation leading to polymyxin resistance

Polymyxins are “last line of defense” antibiotics used in the treatment of multi-drug resistant gram-negative infections. However, resistance to polymyxins and other natural cationic antimicrobial peptides can develop through active modifications of …

[PDF] Phospho-Tune: Enhanced Structural Modeling of Phosphorylated Protein Interactions

In computational biology, accurate prediction of phosphopeptide-protein complex structures is essential for understanding cellular functions and advancing drug discovery and personalized medicine. While AlphaFold has significantly improved …

[PDF] Finding identical sequence repeats in multiple protein sequences: An algorithm

In recent years, several experimental evidences suggest that amino acid repeats are closely linked to many disease conditions, as they have a significant role in evolution of disordered regions of the polypeptide segments. Even though many algorithms …

[HTML] Equivariant Pretrained Transformer for Unified Geometric Learning on Multi-Domain 3D Molecules

Pretraining on a large number of unlabeled 3D molecules has showcased superiority in various scientific applications. However, prior efforts typically focus on pretraining models on a specific domain, either proteins or small molecules, missing the …

[HTML] Improving chemical reaction yield prediction using pre-trained graph neural networks

Graph neural networks (GNNs) have proven to be effective in the prediction of chemical reaction yields. However, their performance tends to deteriorate when they are trained using an insufficient training dataset in terms of quantity or diversity. A …

Predicting protein conformational ensembles using deep generative models

Machine learning has achieved remarkable success in prediction of the native protein structures from sequence information alone. However, proteins are inherently dynamic and there is a pressing need for accurate predictions of dynamic structural …

Differential protein-protein interactions underlie signaling mediated by the TCR and a 4-1BB domain–containing CAR

Cells rely on activity-dependent protein-protein interactions to convey biological signals. For chimeric antigen receptor (CAR) T cells containing a 4-1BB costimulatory domain, receptor engagement is thought to stimulate the formation of …

[HTML] Psc-cpi: Multi-scale protein sequence-structure contrasting for efficient and generalizable compound-protein interaction prediction

Compound-Protein Interaction (CPI) prediction aims to predict the pattern and strength of compound-protein interactions for rational drug discovery. Existing deep learning-based methods utilize only the single modality of protein sequences or …

[HTML] A Cancer Nanovaccine for Co-Delivery of Peptide Neoantigens and Optimized Combinations of STING and TLR4 Agonists

Immune checkpoint blockade (ICB) has revolutionized cancer treatment and led to complete and durable responses, but only for a minority of patients. Resistance to ICB can largely be attributed to insufficient number and/or function of antitumor CD8+ …

[HTML] The immunobiology of SARS-CoV-2 infection and vaccine responses: potential influences of cross-reactive memory responses and aging on efficacy and off-target …

Immune responses to both SARS-CoV-2 infection and its associated vaccines have been highly variable within the general population. The increasing evidence of long-lasting symptoms after resolution of infection, called post-acute sequelae of COVID …

[PDF] Bioengineered small extracellular vesicles deliver multiple SARS‐CoV‐2 antigenic fragments and drive a broad immunological response

The COVID‐19 pandemic highlighted the clear risk that zoonotic viruses pose to global health and economies. The scientific community responded by developing several efficacious vaccines which were expedited by the global need for vaccines …

[HTML] Different pain phenotypes are associated with anti-Caspr2 autoantibodies

Autoantibodies against contactin-associated protein 2 (Caspr2) not only induce limbic autoimmune encephalitis but are also associated with pain conditions. Here, we analyzed clinical data on pain in a large cohort of patients included into the …

[PDF] Dissecting the role of CAR signaling architectures on T cell activation and persistence using pooled screening and single-cell sequencing

Chimeric antigen receptor (CAR) T cells represent a promising approach for cancer treatment, yet challenges remain such as limited efficacy due to a lack of T cell persistence. Given its critical role in promoting and modulating T cell responses, it is …

Abstract P40: Therapeutic anti-B-cell Receptor antibody, WBMP-4, modulates malignant B-cell signaling and induces apoptosis

Abstract The B-cell Receptor (BCR), comprising CD79a/b and membrane Ig, initiates a driver pathway of cell survival and proliferation, and is a rational drug target for B-cell-derived leukemia/lymphoma. Furthermore, within these cancers, the malignant …

[PDF] The Majority of SARS-CoV-2 Plasma Cells are Excluded from the Bone Marrow Long-Lived Compartment 33 Months after mRNA Vaccination

The goal of any vaccine is to induce long-lived plasma cells (LLPC) to provide life-long protection. Natural infection by influenza, measles, or mumps viruses generates bone marrow (BM) LLPC similar to tetanus vaccination which affords safeguards for …

Relevance of lymphocyte proliferation to PHA in severe combined immunodeficiency (SCID) and T cell lymphopenia

Severe combined immunodeficiency (SCID) is characterized by a severe deficiency in T cell numbers. We analyzed data collected (n= 307) for PHA-based T cell proliferation from the PIDTC SCID protocol 6901, using either a radioactive or flow …

[PDF] Signaling via a CD27-TRAF2-SHP-1 axis during naive T cell activation promotes memory-associated gene regulatory networks

The interaction of the tumor necrosis factor receptor (TNFR) family member CD27 on naive CD8+ T (Tn) cells with homotrimeric CD70 on antigen-presenting cells (APCs) is necessary for T cell memory fate determination. Here, we examined CD27 …

Adapted large language models can outperform medical experts in clinical text summarization

Analyzing vast textual data and summarizing key information from electronic health records imposes a substantial burden on how clinicians allocate their time. Although large language models (LLMs) have shown promise in natural language processing …

[HTML] Immunisation efficacy of a stabilised SARS-CoV-2 spike glycoprotein in two geriatric animal models

Age is associated with reduced efficacy of vaccines and linked to higher risk of severe COVID-19. Here we determined the impact of ageing on the efficacy of a SARS-CoV-2 vaccine based on a stabilised Spike glycoprotein (S-29) that had …

[HTML] Frequency, kinetics and determinants of viable SARS-CoV-2 in bioaerosols from ambulatory COVID-19 patients infected with the Beta, Delta or Omicron variants

Airborne transmission of SARS-CoV-2 aerosol remains contentious. Importantly, whether cough or breath-generated bioaerosols can harbor viable and replicating virus remains largely unclarified. We performed size-fractionated aerosol sampling …

Invention of MK-7845, a SARS-CoV-2 3CL Protease Inhibitor Employing a Novel Difluorinated Glutamine Mimic

As SARS-CoV-2 continues to circulate, antiviral treatments are needed to complement vaccines. The virus's main protease, 3CLPro, is an attractive drug target in part because it recognizes a unique cleavage site, which features a glutamine …

[HTML] Discovery of CMX990: A Potent SARS-CoV-2 3CL Protease Inhibitor Bearing a Novel Warhead

There remains a need to develop novel SARS-CoV-2 therapeutic options that improve upon existing therapies by an increased robustness of response, fewer safety liabilities, and global-ready accessibility. Functionally critical viral main …

[HTML] Discordant Antigenic Properties of Soluble and Virion SARS-CoV-2 Spike Proteins

Efforts to develop vaccine and immunotherapeutic countermeasures against the COVID-19 pandemic focus on targeting the trimeric spike (S) proteins of SARS-CoV-2. Vaccines and therapeutic design strategies must impart the characteristics of virion …

[HTML] The host-targeted antiviral drug Zapnometinib exhibits a high barrier to the development of SARS-CoV-2 resistance

Host targeting antiviral drugs (HTA) are directed against cellular mechanisms which can be exploited by viruses. These mechanisms are essential for viral replication, because missing functions cannot be compensated by the virus. However, this …

AbDPP: Target-oriented antibody design with pretraining and prior biological structure knowledge

Antibodies represent a crucial class of complex protein therapeutics and are essential in the treatment of a wide range of human diseases. Traditional antibody discovery methods, such as hybridoma and phage display technologies, suffer from …

Local and Global Variability in Developing Human T-Cell Repertoires

The adaptive immune response relies on T cells that combine phenotypic specialization with diversity of T-cell receptors (TCRs) to recognize a wide range of pathogens. TCRs are acquired and selected during T-cell maturation in the thymus …

The S2 subunit of spike encodes diverse targets for functional antibody responses to SARS-CoV-2 (preprint)

The SARS-CoV-2 virus responsible for the COVID-19 global pandemic has exhibited a striking capacity for viral evolution that drives continued evasion from vaccine and infection-induced immune responses. Mutations in the receptor binding domain of …

Biopsy proteome scoring to determine mucosal remodeling in celiac disease

Background & aims Histological evaluation of gut biopsies is a cornerstone for diagnosis and management of celiac disease (CeD). Despite its wide use, the method depends on proper biopsy orientation, and it suffers from inter-observer …

[PDF] CD8+ T cell memory induced by successive SARS-CoV-2 mRNA vaccinations is characterized by shifts in clonal dominance

Summary mRNA vaccines against the spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) elicit strong T cell responses. However, a clonal-resolution analysis of T cell responses to mRNA vaccination has not been …

[HTML] Prediction of tumor-reactive T cell receptors from scRNA-seq data for personalized T cell therapy

The identification of patient-derived, tumor-reactive T cell receptors (TCRs) as a basis for personalized transgenic T cell therapies remains a time-and cost-intensive endeavor. Current approaches to identify tumor-reactive TCRs analyze tumor …

[PDF] ERG and c-MYC regulate a critical gene network in BCR:: ABL1-driven B cell acute lymphoblastic leukemia

Philadelphia chromosome–positive B cell acute lymphoblastic leukemia (B-ALL), characterized by the BCR:: ABL1 fusion gene, remains a poor prognosis cancer needing new therapeutic approaches. Transcriptomic profiling identified up-regulation of oncogenic transcription factors ERG and c-MYC in BCR:: ABL1 B-ALL with ERG and c-MYC required for BCR:: ABL1 B-ALL in murine and human models. Profiling of ERG-and c-MYC–dependent gene expression and analysis of ChIP-seq …

[HTML] Genetic fusion of CCL11 to antigens enhances antigenicity in nucleic acid vaccines and eradicates tumor mass through optimizing T-cell response

Nucleic acid vaccines have shown promising potency and efficacy for cancer treatment with robust and specific T-cell responses. Improving the immunogenicity of delivered antigens helps to extend therapeutic efficacy and reduce dose-dependent toxicity. Here, we systematically evaluated chemokine-fused HPV16 E6/E7 antigen to improve the cellular and humoral immune responses induced by nucleotide vaccines in vivo. We found that fusion with different chemokines shifted the nature of the …

[PDF] Similarity Network Analysis of the Adaptive Immune Response in the Proximal Airway

Objectives Recent immunologic study of the adaptive immune repertoire in the subglottic airway demonstrated high‐frequency T cell clones that do not overlap between individuals. However, the anatomic distribution and antigenic target of the T cell repertoire in the proximal airway mucosa remain unresolved. Methods Single‐cell RNA sequencing of matched scar and unaffected mucosa from idiopathic subglottic stenosis patients (iSGS, n= 32) was performed and compared with airway …

[PDF] Development of a new genotype–phenotype linked antibody screening system

Antibodies are powerful tools for the therapy and diagnosis of various diseases. In addition to conventional hybridoma-based screening, recombinant antibody-based screening has become a common choice; however, its application is hampered by two factors: 1) screening starts only after Ig gene cloning and recombinant antibody production, and 2) the antibody is composed of paired chains, heavy and light, commonly expressed from two independent expression vectors. Here, we introduce …

[HTML] Integrating Optical Genome Mapping and Whole Genome Sequencing in Somatic Structural Variant Detection

Structural variants drive tumorigenesis by disrupting normal gene function through insertions, inversions, translocations, and copy number changes, including deletions and duplications. Detecting structural variants is crucial for revealing their roles in tumor development, clinical outcomes, and personalized therapy. Presently, most studies rely on short-read data from next-generation sequencing that aligns back to a reference genome to determine if and, if so, where a structural variant occurs …

[PDF] Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space

Proteins are a diverse class of biomolecules responsible for wide-ranging cellular functions, from catalyzing reactions to recognizing pathogens. The ability to evolve proteins rapidly and inexpensively toward improved properties is a common …

[PDF] Cross-Domain Relation Adaptation

We consider the challenge of establishing relationships between samples in distinct domains, A and B, using supervised data that captures the intrinsic relationships within each domain. In other words, we present a semi-supervised setting in which there are no labeled mixed-domain pairs of samples. Our method is derived based on a generalization bound and incorporates supervised terms for each domain, a domain confusion term on the learned features, and a consistency term for domain …

[PDF] Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling

Large-scale sequence modeling has sparked rapid advances that now extend into biology and genomics. However, modeling genomic sequences introduces challenges such as the need to model long-range token interactions, the effects of upstream and downstream regions of the genome, and the reverse complementarity (RC) of DNA. Here, we propose an architecture motivated by these challenges that builds off the long-range Mamba block, and extends it to a BiMamba component that …

[PDF] Transformer-Based Deep Learning Model with Latent Space Regularization for CRISPR-Cas Protein Sequence Classification

The discovery of the CRISPR-Cas system has significantly advanced genome editing, offering vast applications in medical treatments and life sciences research. Despite their immense potential, the existing CRISPR-Cas proteins still face …

[HTML] Diffusion on language model embeddings for protein sequence generation

Protein design requires a deep understanding of the inherent complexities of the protein universe. While many efforts lean towards conditional generation or focus on specific families of proteins, the foundational task of unconditional generation …

[PDF] AbFlex: Designing antibody complementarity determining regions with flexible CDR definition

Motivation Antibodies are proteins that the immune system produces in response to foreign pathogens. Designing antibodies that specifically bind to antigens is a key step in developing antibody therapeutics. The complementarity determining regions …

[HTML] Teaching Large Language Models to Reason with Reinforcement Learning

Reinforcement Learning from Human Feedback (\textbf {RLHF}) has emerged as a dominant approach for aligning LLM outputs with human preferences. Inspired by the success of RLHF, we study the performance of multiple algorithms that learn from …

[HTML] One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models

Large pre-trained Vision-Language Models (VLMs) like CLIP, despite having remarkable generalization ability, are highly vulnerable to adversarial examples. This work studies the adversarial robustness of VLMs from the novel perspective of …

[PDF] Protein Embeddings Predict Binding Residues in Disordered Regions

The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Today's methods predicting …

[PDF] X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in Classification

In recent years, few-shot and zero-shot learning, which learn to predict labels with limited annotated instances, have garnered significant attention. Traditional approaches often treat frequent-shot (freq-shot; labels with abundant instances), few …

[HTML] SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues

Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches …

[HTML] Preference optimization of protein language models as a multi-objective binder design paradigm

We present a multi-objective binder design paradigm based on instruction fine-tuning and direct preference optimization (DPO) of autoregressive protein language models (pLMs). Multiple design objectives are encoded in the language model through direct optimization on expert curated preference sequence datasets comprising preferred and dispreferred distributions. We show the proposed alignment strategy enables ProtGPT2 to effectively design binders conditioned on …

[PDF] Developing a Novel Pharmacoviral Anti-Cancer Strategy Combining Targeted Immunotherapy and Oncolytic Rhabdovirus VSV∆ 51

Oncolytic viruses (OVs) are attenuated viruses that have been engineered to selectively infect and kill cancer cells. OVs exert anti-tumour effects through different mechanisms that reprogram the tumour microenvironment and stimulate anti-tumour immunity. While OVs can treat many cancers, a major challenge is heterogeneity of treatment responses and tumour resistance to OV infection. To address this hurdle, the Diallo lab identified several compounds, termed viral enhancers, that improve …

[HTML] Research overview on the genetic mechanism underlying the biosynthesis of polysaccharide in tuber plants

Tuber plants are of great significance in the world as human food crops. Polysaccharides, important metabolites in tuber plants, also serve as a source of innovative drugs with significant pharmacological effects. These drugs are particularly known for their immunomodulation and antitumor properties. To fully exploit the potential value of tuber plant polysaccharides and establish a synthetic system for their targeted synthesis, it is crucial to dissect their metabolic processes …

[HTML] SGNet: Folding Symmetrical Protein Complex with Deep Learning

Deep learning has made significant progress in protein structure prediction, advancing the development of computational biology. However, despite the high accuracy achieved in predicting single-chain structures, a significant number of large homo-oligomeric assemblies exhibit internal symmetry, posing a major challenge in structure determination. The performances of existing deep learning methods are limited since the symmetrical protein assembly usually has a long sequence, making …

[HTML] A Protein Misfolding Shaking Amplification-based method for the spontaneous generation of hundreds of bona fide prions

Prion diseases are a group of rapidly progressing neurodegenerative disorders caused by the misfolding of the endogenous prion protein (PrPC) into a pathogenic form (PrPSc). This process, despite being the central event underlying these disorders, remains largely unknown at a molecular level, precluding the prediction of new potential outbreaks or interspecies transmission incidents. In this work, we present a method to generate bona fide recombinant prions de novo, allowing a …

[HTML] Guinea fowl eggshell structural analysis at different scales reveals how organic matrix induces microstructural shifts that enhance its mechanical properties

Guinea fowl eggshells have an unusual structural arrangement that is different from that of most birds, consisting of two distinct layers with different microstructures. This bilayered organization, and distinct microstructural characteristics, provides it with exceptional mechanical properties. The inner layer, constituting about one third of the eggshell thickness, contains columnar calcite crystal units arranged vertically as in most bird shells. However, the thicker outer layer has a more complex …

Transition Path Sampling Study of Engineered Enzymes That Catalyze the Morita–Baylis–Hillman Reaction: Why Is Enzyme Design so Difficult?

It is hoped that artificial enzymes designed in laboratories can be efficient alternatives to chemical catalysts that have been used to synthesize organic molecules. However, the design of artificial enzymes is challenging and requires a detailed molecular-level analysis to understand the mechanism they promote in order to design efficient variants. In this study, we computationally investigate the mechanism of proficient Morita–Baylis–Hillman enzymes developed using a …

Multi-strategy orthogonal enhancement and analysis of aldo-keto reductase thermal stability

Given their outstanding efficiency and selectivity, enzymes are integral in various domains such as drug synthesis, the food industry, and environmental management. However, the inherent instability of natural enzymes limits their widespread industrial application. In this study, we underscore the efficacy of enhancing protein thermal stability through comprehensive protein design strategies, encompassing elements such as the free energy of protein folding, internal forces within proteins, and the …

[HTML] Eggshell microstructure, shell quality indices, mineralogy, and UV-Vis absorbance of domestic eggs of Iran

The structure and quality of eggshells (ES) vary around a mean value depending on different items, and these variations are important in their many industrial and technological applications as will be mentioned (vide infra). Five commercial egg brands of different laying hens are examined and their quality indices, morphological microstructure, elemental composition, and light absorbance at 200–700 nm UV/Vis spectra were compared. The ES layers include a limiting membrane, inner and outer …

[PDF] Immunization of cows with HIV envelope trimers generates broadly neutralizing antibodies to the V2-apex from the ultralong CDRH3 repertoire

The generation of broadly neutralizing antibodies (bnAbs) to specific HIV epitopes of the HIV Envelope (Env) is one of the cornerstones of HIV vaccine research. The current animal models we use have been unable to reliable produce a broadly …

Subcapsular sinus macrophages maximize germinal center development in non-draining lymph nodes during blood-borne viral infection

Lymph node (LN) germinal centers (GCs) are critical sites for B cell activation and differentiation. GCs develop after specialized CD169+ macrophages residing in LN sinuses filter antigens (Ags) from the lymph and relay these Ags into proximal B cell …

[HTML] Differential Impact of CD43 and CD28 on T-Cell Differentiation Depending on the Order of Engagement with the TCR

The combination of signals from the T-cell receptor (TCR) and co-stimulatory molecules triggers transcriptional programs that lead to proliferation, cytokine secretion, and effector functions. We compared the impact of engaging the TCR with …

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T cells are key players in humoral immune responses. Upon infection with a pathogen, CD4 T cells utilize their T cell receptor (TCR) to survey for peptides bound to MHC class II molecules (pMHCII) presented by professional antigen presenting …

[HTML] B cell receptor repertoire analysis in primary Sjogren's syndrome salivary glands identifies repertoire features associated with clinical activity

Primary Sjogren's syndrome (pSS) is a complex autoimmune disease featuring damage to salivary and lacrimal glands, with the possibility of manifestations across multiple organs. Antibody-producing B cells have long been appreciated to play a …

[PDF] Machine learning predictions of T cell antigen specificity from intracellular calcium dynamics

Adoptive T cell therapies rely on the production of T cells with an antigen receptor that directs their specificity toward tumor-specific antigens. Methods for identifying relevant T cell receptor (TCR) sequences, predominantly achieved through the …

[PDF] Central tolerance shapes the neutralizing B cell repertoire against a persisting virus in its natural host

Viral mimicry of host cell structures has been postulated to curtail the B cell receptor (BCR) repertoire against persisting viruses through tolerance mechanisms. This concept awaits, however, experimental testing in a setting of natural virus–host relationship. We engineered mouse models expressing a monoclonal BCR specific for the envelope glycoprotein of lymphocytic choriomeningitis virus (LCMV), a naturally persisting mouse pathogen. When the heavy chain of the LCMV …

[PDF] Zeolitic imidazolate frameworks activate endosomal Toll-like receptors and potentiate immunogenicity of SARS-CoV-2 spike protein trimer

Nanomaterials offer unique opportunities to engineer immunomodulatory activity. In this work, we report the Toll-like receptor agonist activity of a nanoscale adjuvant zeolitic imidazolate framework–8 (ZIF-8). The accumulation of ZIF-8 in endosomes …

[PDF] Primer Design and Amplification of IgM Antibody Repertoire of Philippine Carabao (Bubalus kerabau Fitzinger, 1860) for Construction of Phage Display Library

Antibody display library is a robust platform for the production of recombinant or monoclonal antibodies that are of great value in diagnostics and therapeutics. A naïve library constructed based on immunoglobulin M (IgM) can reflect the natural immunity of the animal and can offer broad antigen targets. As a natural host of various zoonotic pathogens, the Philippine carabao (Bubalus kerabau Fitzinger, 1860) offers great potential as a surrogate model for molecular biology and …

RAIN: a Machine Learning-based identification for HIV-1 bNAbs

Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infection. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoire is still lacking. Here, we developed a straightforward computational method for Rapid Automatic Identification of bNAbs (RAIN) based on Machine Learning methods. In contrast to other approaches using one-hot encoding amino acid sequences or structural alignment for prediction, RAIN …

[PDF] A proteome-wide quantitative guide for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs

The intricate molecular environment of the native membrane profoundly influences every aspect of membrane protein (MP) biology. Despite this, the most prevalent method of studying MPs uses detergent-like molecules that disrupt and remove this …

RDC for Membrane Proteins

Rapid progress of lipidic cubic phase crystallography and cryo-electron microscopy in the past decade has drastically lowered the barrier of obtaining high resolution structures of membrane proteins. There are, however, areas of membrane biology …

The receptor binding domain of SARS-CoV-2 Omicron subvariants targets Siglec-9 to decrease its immunogenicity by preventing macrophage phagocytosis

The development of a vaccine specific to severe acute respiratory syndrome coronavirus 2 Omicron has been hampered due to its low immunogenicity. Here, using reverse mutagenesis, we found that a phenylalanine-to-serine mutation at …

[HTML] GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks

Graph neural networks (GNNs), and especially message-passing neural networks, excel in various domains such as physics, drug discovery, and molecular modeling. The expressivity of GNNs with respect to their ability to discriminate non-isomorphic …

[PDF] GDOP: A graph convolutional network-based drug" on-target" pathway prediction algorithm

Since most compounds do not induce changes in the transcriptomic levels of their target proteins in vivo, traditional gene set enrichment analysis methods can only retrieve downstream differentially expressed genes, which offer little hints to their …

[PDF] MS1Former: A robust deep learning framework is used to identify nuances in LC-MS data for diagnosis of hepatocellular carcinoma

Clinical proteomics analysis is of great significance for analyzing pathological mechanisms and discovering disease-related biomarkers. Using computational methods to accurately predict disease types can effectively improve patient disease …

[HTML] Synthetic development of a broadly neutralizing antibody against snake venom long-chain α-neurotoxins

Snakebite envenoming is a major global public health concern for which improved therapies are urgently needed. The antigenic diversity present in snake venom toxins from various species presents a considerable challenge to the development of a …

Colorimetric and surface-enhanced Raman scattering dual-mode lateral flow immunosensor using phage-displayed shark nanobody for the detection of crustacean …

Tropomyosin (TM) is the primary allergenic protein responsible for crustacean food allergies, and thus sensitive and rapid methods are required for the screening of crustacean TM in food. In this study, using the phage-displayed shark nanobody …

[HTML] AviTag-nanobody based enzyme immunoassays for sensitive determination of aflatoxin B1 in cereal

Abstract Aflatoxin B 1 (AFB 1) is a well-known carcinogen for human health, and requires sensitive and rapid methods for monitoring. Here, we developed an Avi-tagged nanobody (AviTag-Nb) and incorporated it into the biotin-streptavidin …

Convolutional Neural Networks Guided Raman Spectroscopy as a Process Analytical Technology (PAT) Tool for Monitoring and Simultaneous Prediction of …

Background Charge related heterogeneities of monoclonal antibody (mAb) based therapeutic products are increasingly being considered as a critical quality attribute (CQA). They are typically estimated using analytical cation exchange …

Using capillary electrophoresis sodium dodecyl sulfate (CE‐SDS) and liquid chromatograph mass spectrometry (LC–MS) to identify glycosylated heavy chain …

The size variant, which can be measured by capillary electrophoresis sodium dodecyl sulfate (CE‐SDS), is a critical quality attribute of monoclonal antibodies (mAbs). The CE‐SDS size heterogeneity can hardly be identified by tandem mass …

[HTML] Capture of fully assembled secretory immunoglobulin a by affinity chromatography with nanobodies as ligands

Secretory immunoglobulin A (sIgA) has a big potential for passive immunization and other therapeutic applications. This complex molecule with a molecular mass of 410 kDa consists of two IgA monomers linked by a connecting chain (J) and a secretory …

[PDF] Cyclic β2, 3-amino acids improve the serum stability of macrocyclic peptide inhibitors targeting the SARS-CoV-2 main protease

Due to their constrained conformations, cyclic β2, 3-amino acids (cβAA) are key building blocks that can fold peptides into compact and rigid structures, improving peptidase resistance and binding affinity to target proteins, due to their constrained …

[HTML] Ubiquitin Ligase Parkin Regulates the Stability of SARS-CoV-2 Main Protease and Suppresses Viral Replication

The highly infectious coronavirus SARS-CoV-2 relies on the viral main protease (Mpro, also known as 3CLpro or Nsp5) to proteolytically process the polyproteins encoded by the viral genome for the release of functional units in the host cells to …

[HTML] Impact of SARS-CoV-2 spike stability and RBD exposure on antigenicity and immunogenicity

The spike protein (S) of SARS-CoV-2 induces neutralizing antibodies and is the key component of current COVID-19 vaccines. The most efficacious COVID-19 vaccines are genetically-encoded spikes with a double proline substitution in the hinge region …

[HTML] Impaired innate and adaptive immune responses to BNT162b2 SARS-CoV-2 vaccination in systemic lupus erythematosus

Understanding the immune responses to SARS-CoV-2 vaccination is critical to optimizing vaccination strategies for individuals with autoimmune diseases, such as systemic lupus erythematosus (SLE). Here, we comprehensively analyzed innate …

Improved Innate Immune Function in Patients with Chronic Lymphocytic Leukemia Treated with Targeted Therapy in Clinical Trials