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RFdiffusion

Generative diffusion for de novo protein backbone design

What's new

RFdiffusion3 (open-sourced 2025) is an all-atom foundation model ~10× faster than RFdiffusion2, now distributed via the Rosetta Foundry.

RFdiffusion brought denoising diffusion to protein design, generating novel backbones for binders, symmetric oligomers, motif scaffolds and enzyme active sites. Designs are typically paired with ProteinMPNN for sequence design and a structure predictor for validation.

The lineage

  • RFdiffusion — backbone generation conditioned on motifs, symmetry and target hotspots.
  • RFdiffusion2 — improved enzyme and all-atom design.
  • RFdiffusion3 — a unified all-atom foundation model, ~10× faster, covering protein–protein, protein–DNA, protein–small-molecule binding and enzyme design.

Related tools

Liftoff.bio illustration — cat ai models
Open source

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ProteinMPNN

Fast, robust inverse folding — sequences for a target backbone

Python libraryCommand lineModel weights
Liftoff.bio illustration — post structure models
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BindCraft

One-shot de novo binder design with AlphaFold2 backpropagation

Python libraryCommand line
Liftoff.bio illustration — cat ai models
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BoltzGen

Toward universal binder design across modalities

Python libraryCommand lineModel weights