AntiFold
OPIG (Oxford)
Antibody-specific inverse folding model fine-tuned from ESM-IF1. Designs sequences predicted to maintain structural fold given an antibody backbone.
Best For
CDR sequence optimization for known antibody scaffolds
License
Open Source (BSD 3-Clause)
Strengths
- +Antibody-specific (outperforms ESM-IF1 on CDRs)
- +Web server available
- +BSD license
Limitations
- −Backbone must be provided
- −CDR-H3 diversity limited
R&D Pipeline Coverage
Related Tools
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Luo et al. (NeurIPS 2022)
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Inverse folding model: generates amino acid sequences predicted to fold into a target 3D backbone structure. Standard component of all modern protein design pipelines.
ESM-IF1
Meta AI (FAIR)
Structure-conditioned inverse folding model: given a protein backbone, predicts sequences likely to fold into it. General-purpose (not antibody-specific).
More in Antibody Design
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RFdiffusion fine-tuned for de novo antibody design. Generates VHHs, scFvs, and full antibodies targeting user-specified epitopes. Experimentally validated with cryo-EM.
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Suite for predicting 3D structures of antibodies (ABodyBuilder), nanobodies (NanoBodyBuilder2), and TCRs (TCRBuilder2) from sequence.
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