ArticleBioinformatics advances2025
AntiFold: improved structure-based antibody design using inverse folding.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Tokenizing loops of antibodies.mAbs · 2026Article
- Article
- Inverse FoldDir: Structure-conditioned Protein Sequence Design by Dirichlet Flow Matching.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
- Multi-objective antibody design and optimization using machine learning.Nature reviews bioengineering · 2026Article
- CLDN18.2 antibody design with protein language models: A deep learning optimization framework.PLoS computational biology · 2026Article
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Machine learning enables efficient and effective affinity maturation of nanobodies.bioRxiv : the preprint server for biology · 2026Article
- AI-assisted protein design to rapidly convert antibody sequences to intrabodies targeting diverse peptides and histone modifications.Science advances · 2026Article
- AI-Driven De Novo Binder Design: From Structure Prediction to Closed-Loop Optimization.Computational and structural biotechnology journal · 2026Review
- Nanobodies in biomedicine: from molecular characteristics to fabrication and clinical translation.Military Medical Research · 2026Review
- CoV-UniBind: a unified antibody binding database for SARS-CoV-2.Bioinformatics advances · 2026Article
- Benchmarking antigen-aware inverse folding methods for antibody design.Bioinformatics advances · 2026Article
- Article
- De novo design of epitope-specific antibodies via a structure-driven computational workflow.Nature communications · 2025Article
- Experimental Study and Molecular Modeling of Antibody Interactions with Different Fluoroquinolones.International journal of molecular sciences · 2025Article
- Article
- AntiBMPNN: Structure-Guided Graph Neural Networks for Precision Antibody Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Therapeutic Antibodies for Infectious Diseases: Recent Past, Present, and Future.Biochemistry · 2025Review
- Functional and epitope specific monoclonal antibody discovery directly from immune sera using cryo-EM.Science advances · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: The design and optimization of antibodies requires an intricate balance across multiple properties. Protein inverse folding models, capable of generating diverse sequences folding into the same structure, are promising tools for maintaining structural integrity during antibody design. Here, we present AntiFold, an antibody-specific inverse folding model, fine-tuned from ESM-IF1 on solved and predicted antibody structures. AntiFold outperforms existing inverse folding tools on sequence recovery across complementarity-determining regions, with designed sequences showing high structural similarity to their solved counterpart. It additionally achieves stronger correlations when predicting antibody-antigen binding affinity in a zero-shot manner. AntiFold assigns low probabilities to mutations that disrupt antigen binding, synergizing with protein language model residue probabilities, and demonstrates promise for guiding antibody optimization while retaining structure-related properties. Availability and implementation: AntiFold is freely available under the BSD 3-Clause as a web server (https://opig.stats.ox.ac.uk/webapps/antifold/) and pip-installable package (https://github.com/oxpig/AntiFold).
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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.