Monoclonal and Polyclonal Antibodies Research

Benchmarking Generative Large Language Models for de novo Antibody Design and Agentic Evaluation

This study benchmarks compact transformer models for de novo antibody design, finding no significant architectural differences in performance at small scales.

Structure-Function Analysis of the FCRL5-IgG1 Fc Complex Reveals an Unappreciated Effect of Fc-Silent Antibodies on B cells

This study shows Fc-silencing mutations in therapeutic antibodies do not block FCRL5 binding, potentially affecting B cell function through novel Fc-FCRL5 interactions.

The Synthetic Epitope Atlas: High-Throughput Design and Validation of De Novo Antibody-Antigen Complexes

The paper generates and validates synthetic epitope proteins to improve de novo antibody design by combining computational design with high-throughput experimental binding data.

Agent-Guided De Novo Design of Nanobody Binders Against a Novel Cancer Target

The paper presents a computational workflow for designing nanobody binders against a novel cancer target, achieving sub-nanomolar affinities without experimental structure or prior antibody data.

KyDab - a comprehensive database of antibody discovery selection campaigns.

KyDab is a database of antibody discovery selection campaigns that provides full-funnel selection data for AI model development and evaluation.

Fc-Free Single Chain Antibody mRNA Therapy for Airway Infection of Multidrug-Resistant Pseudomonas Aeruginosa

This study develops mRNA-based Fc-free scFv antibodies targeting Pseudomonas aeruginosa's type III secretion system, showing efficacy in treating multidrug-resistant airway infections in mice.

Separating selection from mutation in antibody language models

This paper introduces a model that separates mutation and selection processes in antibody language models to improve prediction of mutation effects on antibody function.

Deep learning assessment of nativeness and pairing likelihood for antibody and nanobody design with AbNatiV2

This paper introduces AbNatiV2 and p-AbNatiV2, deep learning models for assessing nativeness and pairing likelihood in antibodies and nanobodies, showing improved performance on held-out tests.

Combining a homogenous KIM-1-DM1 antibody drug conjugate with sunitinib in renal cell carcinoma

This study combines a homogenous KIM-1-targeted ADC with sunitinib to treat RCC, showing synergistic antitumor efficacy in a mouse model.

Structure-Guided Computational Analysis of Linker effects in an scFv Targeting Guanylyl Cyclase C

The paper evaluates how different linker designs affect the structure and function of an anti-GUCY2C scFv using computational methods.

Discovering Novel Therapeutic VHHs for Emerging Viruses: Perspectives from VEEV Selection Strategies

This paper reports four novel VHHs against VEEV E2 protein selected using computational and biochemical strategies, showing they can bind and sequester viral particles, acting as viral sponges.

Development of Motif-Specific Monoclonal Antibodies for Global Protein Citrullination Detection with Minimal Cross-Reactivity to Homocitrullination

This paper develops monoclonal antibodies specific for citrullination, showing high sensitivity and minimal cross-reactivity with homocitrullination.

Effects of protein interface mutations on protein quality and affinity

The paper disentangles protein-interaction and protein-quality effects in antibody-antigen binding using deep mutational scanning and evaluates models for their ability to predict these effects.

Computational mapping of antibody-receptor energy landscapes to predict membrane internalization

This study uses molecular dynamics simulations to predict antibody internalization by mapping energy landscapes between antibodies and JAM-A receptors, identifying key interactions that drive endocytosis.

SpeciefAI: Multi-species mRNA-level Antibody Framework Generation using Transformers

SpeciefAI generates species-specific mRNA and protein sequences for antibodies and nanobodies using a transformer model trained on six species.

De novo design of therapeutic scFvs and multi-specific engagers from sequence alone

This paper introduces IASO, a sequence-centric framework for designing therapeutic scFvs and multi-specific engagers using only antigen sequence, demonstrating its ability to identify novel binders and overcome drug resistance.

Mechanistic Basis for the Selective Recognition of the Fcγ Receptor IIa by Monoclonal Antibody IV.3

This paper elucidates the mechanistic basis for the selective recognition of FcγRIIa by monoclonal antibody IV.3 through a combination of experimental and computational methods.

Comprehensive Mapping of Immune Nanobody Repertoires with NanoMAP

The paper develops NanoMAP, a pipeline for analyzing nanobody repertoires, showing it outperforms standard methods in identifying coherent clonal families and detecting high-affinity nanobodies.

Cloning, expression and characterisation of antigen-specific recombinant bat immunoglobulin from the black flying fox (Pteropus alecto)

The paper generates antigen-specific recombinant bat antibodies from Pteropus alecto to study bat antibody immunity and provides new diagnostic tools.

Developability Evaluation of Single-Domain Antibody Chelator Conjugates for Diagnostic Radiotracers

The paper evaluates the developability of single-domain antibody chelator conjugates for diagnostic radiotracers using stability and functional assays.

Toward Site-Specific Characterization of Structural Perturbations on Glycosylated Fc Using NMR at Natural Abundance

This paper presents a methyl group assignment for the Fc fragment of an IgG1 antibody using NMR, enabling structural analysis of glycosylated Fc without isotopic labelling.

CaptureBody - an anti-CD45 x anti-IgG bispecific antibody enables accurate unmixing for spectral flow cytometry

The paper introduces CaptureBody, a bispecific antibody for spectral flow cytometry that improves unmixing accuracy by using cells instead of compensation particles.

Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologies

This study compares mRNA and yeast display technologies for evaluating ML-designed miniprotein binders, finding mRNA display better enriches slow dissociating binders and achieves higher library coverage.

ASD: Antigen-Specific Antibody Database

The paper develops the ASD database to aggregate antibody-antigen interaction data from multiple sources, providing a standardized resource for computational model development.

Cell-Based Immunization Combined with Single-Round Cell Panning Enables Discovery of PSMA-Targeting Nanobodies from Phage Display Libraries

This study demonstrates that non-targeted immunization and panning can isolate PSMA-targeting nanobodies from phage display libraries.

Evolutionary Divergence and Structural Differentiation of Multiple Immunoglobulin M Genes in Gekkota (Squamata: Reptilia)

This study identifies multiple IgM gene variants in geckos and analyzes their evolutionary origin and functional divergence through sequence and structural comparisons.

Integrated Cytotoxic and Safety Mechanism of IMV-M (TM), a MUC16 x DR5 Bispecific Antibody

This study evaluates the cytotoxic mechanism of IMV-M, a MUC16 x DR5 bispecific antibody, showing that multivalent MUC16 binding is required for cytotoxicity and that CA125 does not neutralize its activity.

Ophiuchus-Ab: A Versatile Generative Foundation Model for Advanced Antibody-Based Immunotherapy

Ophiuchus-Ab is a generative foundation model for antibody design that captures inter-chain dependencies and predicts antibody properties like developability and binding affinity.

alpseq: an open-source workflow to turbocharge nanobody discovery with high-throughput sequencing

alpseq is an open-source pipeline for processing NGS data from nanobody libraries, enabling efficient analysis and identification of enriched sequences.

Integrated single-cell analyses of affinity-tested B-cells enable the identification of a gene signature to predict antibody affinity.

The paper identifies a transcriptomic signature, 'High Signature', that predicts high-affinity antibodies from B-cells without sequence analysis.