ArticleNature communications2023
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 197 papers, 1 of them a synthesis that pooled it.
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Who cites it
197 citing papers in PubMed, 1 synthesis or guideline pooled it, 291 citations in OpenAlex.
- Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models.Database : the journal of biological databases and curation · 2025Pooled it
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- Antibody-drug conjugate engineering: from design to efficacy and safety.Signal transduction and targeted therapy · 2026Review
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- Apoptotic Quality Control of Cellular Competence Limits Cryptic Germinal Center B Cell States.bioRxiv : the preprint server for biology · 2026Article
- The Evolution of Artificial Intelligence in Antibody Design: From Structure-Based Engineering to Generative Models.Antibodies (Basel, Switzerland) · 2026Review
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
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- Aligning protein-generative models to experimental fitness with ProteinDPO.Nature methods · 2026Article
- Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder.bioRxiv : the preprint server for biology · 2026Article
- A Multi-Model Strategy for Optimizing Hepatitis B Virus preS1 Epitope Recognition by the Antibody HzKR127.Current issues in molecular biology · 2026Article
- Pocket restraints guided by B-cell epitope prediction improve Chai-1 antibody-antigen structure modeling.Protein science : a publication of the Protein Society · 2026Article
- Charge-driven antiviral responses enhance autoreactivity in severe COVID-19.Research square · 2026Article
- Language Model Embedding Classifiers Enable Identification of Multiple Sclerosis-Associated BCRs and Repertoires.bioRxiv : the preprint server for biology · 2026Article
- Mixture diffusion model for multimodal antibody design.Briefings in bioinformatics · 2026Article
- AbTune: layer-wise selective fine-tuning of protein language models for antibodies.Briefings in bioinformatics · 2026Article
137 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Antibodies have the capacity to bind a diverse set of antigens, and they have become critical therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six hypervariable loops that are diversified through genetic recombination and mutation. Even with recent advances, accurate structural prediction of these loops remains a challenge. Here, we present IgFold, a fast deep learning method for antibody structure prediction. IgFold consists of a pre-trained language model trained on 558 million natural antibody sequences followed by graph networks that directly predict backbone atom coordinates. IgFold predicts structures of similar or better quality than alternative methods (including AlphaFold) in significantly less time (under 25 s). Accurate structure prediction on this timescale makes possible avenues of investigation that were previously infeasible. As a demonstration of IgFold's capabilities, we predicted structures for 1.4 million paired antibody sequences, providing structural insights to 500-fold more antibodies than have experimentally determined structures.
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Registered trials
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.