Monoclonal and Polyclonal Antibodies Research

This study evaluates immunogen properties to improve antibody selection by analyzing structural and functional features and developing a tool for applying these insights.

The paper develops a sensitive GLP-compliant ELISA for detecting GP101 diabody in mouse serum, achieving 15pg/mL sensitivity.

This paper describes a yeast-displayed chemically expanded antibody library and demonstrates its use in identifying function-disrupting antibodies through initial screening.

This paper describes the design and characterization of a bispecific monocyte engager targeting PSMA for prostate cancer immunotherapy, showing effective activation of monocytes and tumor cell elimination.

This paper isolates and characterizes two high-affinity nanobodies against EGFR, showing their potent anti-tumor activity in vitro.

The paper presents a rapid method to develop anti-infective biologicals effective against drug-resistant bacteria and yeasts using antibody-drug conjugates with dual modes of action.

The paper introduces AlphaPanda, an algorithm combining transformer, 3DCNN, and diffusion models for antibody sequence and structure design, achieving high-quality results with reduced training data.

This study develops a Notch inhibitory nanobody and demonstrates a strategy to enhance its efficacy through fusion with an Aerolysin domain.

This study designs antibodies without prior information across eight targets, achieving high precision, sensitivity, and specificity, validated by Cryo-EM and comparable to commercial antibodies.

This study uses AI to humanize a murine antibody by grafting only essential paratopes, reducing immunogenicity while preserving efficacy and developability.

The paper identifies clonotype-enriched mutations in the light chain of a public antibody that enhance affinity for a conserved viral epitope and increase after repeated vaccinations.

This study validates secondary nanobodies for multiplexed immunoassays and provides optimized protocols for their use.

YAbS catalogues over 2,900 commercially sponsored antibody therapeutics, from clinical entry since 2000 to approval, with milestone-date filtering for pipeline, trend and phase-length analyses; over 450 are openly accessible.

The paper develops a quantitative systems pharmacology model to analyze ADCs, showing that bystander effects are significant in vivo and highlighting key design parameters for optimizing efficacy and toxicity.

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.

This paper develops modular antibodies for sensitive and specific detection of poly-ADP-ribosylation, improving immunoblotting and enabling co-detection with mono-ADP-ribosylation in cells.

This paper describes a method for producing functional monoclonal antibodies and fragments from E. coli, making antibody production more accessible and cost-effective.

This paper develops an enhanced anti-pan-fMet antibody using fMXC tripeptides, improving specificity and affinity for detecting fMet-bearing proteins across species.

This paper introduces a high-throughput method for screening antibody neutralization using droplet arrays, demonstrating scalable functional antibody data collection against viral diseases.

The paper identifies inverted D genes and D-D fusions in human antibody repertoires, revealing new diversity and functionality through a comprehensive analysis of NGS data.

This paper introduces engineered protein-G variants and Fab scaffolds to create modular, plug-and-play antibody-based assemblies for versatile cell biology applications.

This study introduces DECODE, a high-throughput method for identifying epitopes at single amino acid resolution, demonstrating its utility in antibody-based research and disease modeling.

This paper introduces JAM, a generative system for de novo antibody design that achieves high-affinity, developable antibodies against various targets without experimental optimization.

The paper develops FAP-targeted theranostics using VNARs from a shark antibody library, showing high affinity and efficacy in vitro and in vivo.

This paper demonstrates a high-throughput method to produce and characterize thousands of single-chain antibodies on an SPR biosensor chip, providing detailed kinetic data to support antibody discovery and AI pipelines.

This study uses antibody repertoire data and machine learning to predict and engineer antibody affinities, achieving accurate predictions and successful in silico design of seven out of eight synthetic variants.

This paper introduces a bispecific antibody, IMV-M, that effectively clusters DR5 on MUC16-positive tumor cells without secondary crosslinking, showing potent anti-tumor activity in vitro and xenograft models.

The paper develops methodologies to generate and analyze immunoglobulin loci variation in rhesus macaques, revealing extensive diversity and expanding existing allele sets by 60%.

This paper introduces PANCS-binders, an in vivo selection method for discovering protein binders, and demonstrates its ability to screen billions of variants against multiple targets in two days.

This study develops a bispecific antibody-drug conjugate targeting pCAD and CDH17, showing antitumor activity in dual antigen-expressing tumors but not in single antigen-expressing tumors.