Monoclonal and Polyclonal Antibodies Research

This paper introduces Chai-2, a model that designs antibodies with a 16% hit rate, achieving success in 50% of targets without prior binders, and enables rapid validation in under two weeks.

This study determines the cryo-EM structures of two bispecific antibody types and shows that domain linkage rearrangement leads to activity enhancement by altering complex shape and dynamics.

This study develops a mathematical model to analyze how antibody-antigen interactions affect mAb potency, efficacy, and the avidity effect.

The paper introduces SAAINT-parser, a tool for extracting antibody and antibody-antigen interaction data from PDB, resulting in SAAINT-DB, which offers more accurate and comprehensive data than existing databases.

The paper describes a method to isolate sIgA1 from nasal secretions using jacalin-conjugated beads, confirming its identity via Western blotting and highlighting its potential as a biomarker for nasal vaccine evaluation.

This study optimizes nanobody-based quenchbodies for enhanced protein detection, achieving fluorescence increases of 1.5-2.4-fold and detecting IL-6 down to 2 nM.

The paper develops anti-VHH antibodies that target nanobody domains in CAR-T cells, enabling labeling, blocking, and activation of VHH-based CAR-T cells without disrupting antigen binding.

GLIMPSE-1, a protein language model trained on human antibody sequences, improves antibody engineering for affinity, cross-reactivity, and developability by leveraging patterns in the human repertoire.

This paper demonstrates the use of neoepitope-specific monoclonal antibody cocktails to treat B16F10 melanoma by targeting unique tumor mutations, showing in vitro and in vivo efficacy.

This study shows that genetic variations in immunoglobulin light chain loci influence the diversity of expressed light chain antibodies, affecting amino acid sequences and gene usage.

This study improves monoclonal antibody production by targeting specific antibody-secreting cells, achieving a 100% fusion yield and over 60% mAb secretion.

The paper computationally designs monomeric Fc variants with distinct pH-responsive FcRn-binding profiles, showing enhanced binding at acidic pH and weak binding at neutral pH.

The paper develops a quantitative pharmacology model to analyze how TCE drug-target trimer formation and biodistribution depend on binding kinetics and design characteristics.

This paper predicts pharmacokinetic profiles of monoclonal antibodies using sequence-based machine learning and compartmental modeling, achieving accurate predictions with reduced reliance on animal testing.

This study combines AI/physics-based computation and phage display to design high-affinity Affilin(R) proteins targeting HER3, achieving successful theranostic candidates with high affinity and stability.

This paper develops a synthetic nanobody library for radiopharmaceutical ligand discovery, demonstrating its utility through PET imaging of a calreticulin-binding nanobody.

This paper develops a kinetic model to predict IgG oligomerization and complement binding, incorporating factors like IgG concentration, antigen density, and Fc mutants.

This study develops and characterizes humanized TNFα inhibitory nanobodies with picomolar potency and low immunogenicity for therapeutic use in TNFα-mediated diseases.

The paper introduces protease-containing nanobodies controlled by antiviral drugs to manipulate intracellular protein-protein interactions.

AbBFN2 is a generative antibody foundation model that unifies diverse data sources and enables flexible conditional generation for multiple antibody design tasks.

FlowDesign improves antibody CDR design using flow matching and better priors, achieving higher affinity and neutralizing potency against HIV mutants.

This study evaluates the pharmacokinetics of a human mAb in different mouse strains to identify suitable models for preclinical testing.

This paper introduces a preferential masking strategy for antibody language models to improve prediction of non-templated residues in CDR3 regions, enhancing classification and specificity.

The paper isolates PcrV-specific B cells from cystic fibrosis patients and generates monoclonal antibodies that reduce Pseudomonas aeruginosa burden in mice.

This paper demonstrates that HER2-VEGFA bispecific antibodies induce co-phagocytosis of VEGFA and HER2-overexpressing cancer cells, enhancing antitumor responses in preclinical models.

This study develops and characterizes six nanobodies as potential therapeutics for PH1 by targeting misfolded AGT variants, showing high affinity and functional enhancement in cellular models.

The paper identifies ITGA3B1 as a therapeutic target for metastatic bladder cancer using a phenotypic screening strategy and develops an ADC targeting this integrin complex, showing antitumor efficacy in preclinical models.

The paper maps the affinity and allostery in human IgG antibody Fc region-Fc γ receptor interactions by analyzing amino acid variations and their effects on binding and effector functions.

The paper introduces an LC-MS method to analyze IgG4 repertoires with clonal resolution, revealing high diversity and persistence of IgG4 molecules in serum over time.

This paper evaluates the antitumor efficacy of humanized 16A antibody conjugates with DNA topoisomerase I inhibitors, showing potent in vitro and in vivo activity against MUC1-expressing tumors.