ProteinMPNN
Baker Lab / IPD (University of Washington)
Inverse folding model: generates amino acid sequences predicted to fold into a target 3D backbone structure. Standard component of all modern protein design pipelines.
Best For
Standard sequence design step after RFdiffusion; generates candidate sequences for any backbone
License
Open Source (check repo)
Strengths
- +Production-ready
- +~1 second per design
- +Widely adopted in industry
Limitations
- −Backbone must be provided
- −Not antibody-specific (use AntiFold for CDRs)
R&D Pipeline Coverage
Related Tools
RFdiffusion
Baker Lab / IPD (University of Washington)
Diffusion-based generative model for de novo protein backbone design. Generates novel protein structures conditioned on binding targets, symmetry, or functional sites.
LigandMPNN
Baker Lab / IPD (University of Washington)
Extension of ProteinMPNN that conditions sequence design on bound ligands, small molecules, metals, and nucleotides.
AntiFold
OPIG (Oxford)
Antibody-specific inverse folding model fine-tuned from ESM-IF1. Designs sequences predicted to maintain structural fold given an antibody backbone.
More in Generative Design
RFdiffusion
Baker Lab / IPD (University of Washington)
Diffusion-based generative model for de novo protein backbone design. Generates novel protein structures conditioned on binding targets, symmetry, or functional sites.
RFdiffusion2
Baker Lab / IPD (University of Washington)
Successor to RFdiffusion using flow matching. Designs enzymes directly from active site geometry (theozyme) specifications.
LigandMPNN
Baker Lab / IPD (University of Washington)
Extension of ProteinMPNN that conditions sequence design on bound ligands, small molecules, metals, and nucleotides.
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