Monoclonal and Polyclonal Antibodies Research

This study shows that IGV allelic polymorphisms widely affect antibody reactivity by analyzing antibody-antigen structures and experimental data.

The paper develops a cost-effective method for epitope mapping using PURE ribosome display combined with NGS and bioinformatics, identifying the 'DVPDY' epitope in hemagglutinin.

This study develops high-throughput bactericidal assays to screen monoclonal antibodies against antimicrobial-resistant Neisseria gonorrhoeae, identifying potent antibodies validated by conventional methods.

This paper develops a human antibody fragment that reverses carfentanil-induced respiratory depression by targeting multiple opioid analogs.

The paper shows that VL domain attributes influence CDR-H3 structure and variability through steric effects using crystal structures and simulations.

This paper evaluates AlphaFold2 and binder hallucination for designing high-affinity antibodies by redesigning sequences of antigen-antibody complexes.

The paper shows that genetic variation in the immunoglobulin heavy chain locus influences the diversity and characteristics of the human antibody repertoire.

The paper introduces PSERM scoring to predict antibody variant properties from deep sequencing data, showing it outperforms traditional methods in reproducibility and correlation with experimental measurements.

This study compares the binding sites of antibodies and single-domain antibodies, showing they target similar epitope sizes and shapes but differ in paratope interactions and framework residue importance.

AB-Gen uses reinforcement learning and a generative pre-trained Transformer to design antibody sequences with multiple desirable properties, improving success rates over traditional methods.

The paper describes a method to isolate full-length IgG antibodies from combinatorial libraries in E. coli using a bifunctional antigen substrate for selection.

This paper uses a Bayesian language model to design high-affinity scFv antibody libraries, achieving 28.8-fold better binding than directed evolution.

This study identifies optimal sites for introducing N-glycans on VHH antibodies to enhance macrophage delivery, demonstrating glycan-dependent uptake in vitro and in vivo.

Consensus likelihoods from general, unsupervised protein language models evolve seven human antibodies using only a wildtype sequence and <=20 tested variants, improving binding affinity up to 160-fold.

This study uses cryo-EM to determine the structural basis of Fc receptor recognition of immunoglobulin M, identifying binding sites and explaining isotype specificity.

SpyDisplay uses SpyTag/SpyCatcher technology to enable covalent display of Fab antibodies on phage, allowing efficient selection of high-affinity clones.

The paper describes the generation and characterization of monoclonal antibodies against Xenopus proteins using refined hybridoma methods, making them available for research.

This paper develops machine learning models to predict antibody thermostability using sequence and structure features, showing better generalization with a CNN over pre-trained language models.

A fragment-based computational method designs nanobodies targeting specific epitopes with nanomolar affinities, without requiring high-resolution antigen structures.

The paper introduces FvHallucinator, a deep learning model that generates antibody CDR libraries conditioned on structure, improving binding affinity and enriching for therapeutic candidates.

The paper evaluates yeast-bacterial cell-cell interactions using flow cytometry and FACS to characterize nanobody-antigen binding.

NAb-seq provides a rapid, cost-effective, and species-independent method for sequencing full-length antibody genes from hybridoma cell lines and single B cells, outperforming Sanger sequencing in accuracy and throughput.

The paper develops a method to improve antibody thermostability by combining consensus sequence analysis with structural residue pair covariance from 3D structures.

The paper demonstrates antibody-mediated knockdown of intracellular protein expression to target specific protein variants, offering new therapeutic strategies for genotype-specific inhibition of pathogenic variants.

AbDiver enables comparison of therapeutic antibody sequences to natural antibody diversity, aiding in rational design by identifying mutation patterns and relevant sequence matches.

The paper develops nanobodies targeting the human transcobalamin-mediated vitamin B12 uptake route and shows their potential to inhibit cancer cell growth.

BioPhi provides automated tools for antibody humanization and humanness evaluation using deep learning and natural antibody repertoires, achieving results comparable to human experts.

The paper introduces two short NanoTag epitopes and their nanobodies for in vivo protein visualization and manipulation in Drosophila, demonstrating their utility in multiple assays and CRISPR-based tagging.

Llamanade is an open-source pipeline that humanizes nanobodies using sequence and structural analysis, improving their translational potential for therapeutic applications.

The paper identifies a high-homology light chain sequence from a hybridoma that is antigen-specific, highlighting challenges in variable domain sequencing.