ArticleProceedings of the National Academy of Sciences of the United States of America2017
Mutational landscape of antibody variable domains reveals a switch modulating the interdomain conformational dynamics and antigen binding.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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Who cites it
77 citing papers in PubMed.
- Multidimensional maturation of antibody variable domains with machine-learning assistance.mAbs · 2026Article
- ASD: antigen-specific antibody database.mAbs · 2026Article
- A Review on Applications of Artificial Intelligence (AI) in Monoclonal Antibody (mAb) Manufacturing.Molecules (Basel, Switzerland) · 2026Review
- Engineering a Second Interchain Disulfide Bond in the αβ T-Cell Receptor Constant Domain: A Powerful Strategy to Enhance Stability, Pairing Fidelity, and Therapeutic Efficacy in TCR-T Cell Therapy.Pharmaceuticals (Basel, Switzerland) · 2026Review
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- Paraplume: A fast and accurate antibody paratope prediction method provides insights into repertoire-scale binding dynamics.PLoS computational biology · 2026Article
- Learning the language of protein-protein interactions.Nature communications · 2026Article
- Machine Learning Approaches for Interpretable Antibody Property Prediction Using Structural Data.Methods in molecular biology (Clifton, N.J.) · 2026Article
- ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains.Nature methods · 2026Article
- Fitness Landscape for Antibodies 2: Benchmarking Reveals That Protein AI Models Cannot Yet Consistently Predict Developability Properties.bioRxiv : the preprint server for biology · 2025Article
- Development of a Komagataella phaffii-based expression system for high-activity anti-SARS-CoV-2 neutralizing antibodies.AMB Express · 2025Article
- AbAgym: a well-curated dataset for the mutational analysis of antibody-antigen complexes.mAbs · 2025Article
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- Separating selection from mutation in antibody language models.bioRxiv : the preprint server for biology · 2025Article
- Novel anti-VEGF scFv antibodies with superior in vitro and in vivo activities.Scientific reports · 2025Article
- Sidechain conditioning and modeling for full-atom protein sequence design with FAMPNN.Proceedings of machine learning research · 2025Article
- Engineering a protease-stable, oral single-domain antibody to inhibit IL-23 signaling.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Learning the language of protein-protein interactions.bioRxiv : the preprint server for biology · 2025Article
17 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Somatic mutations within the antibody variable domains are critical to the immense capacity of the immune repertoire. Here, via a deep mutational scan, we dissect how mutations at all positions of the variable domains of a high-affinity anti-VEGF antibody G6.31 impact its antigen-binding function. The resulting mutational landscape demonstrates that large portions of antibody variable domain positions are open to mutation, and that beneficial mutations can be found throughout the variable domains. We determine the role of one antigen-distal light chain position 83, demonstrating that mutation at this site optimizes both antigen affinity and thermostability by modulating the interdomain conformational dynamics of the antigen-binding fragment. Furthermore, by analyzing a large number of human antibody sequences and structures, we demonstrate that somatic mutations occur frequently at position 83, with corresponding domain conformations observed for G6.31. Therefore, the modulation of interdomain dynamics represents an important mechanism during antibody maturation in vivo.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.