RFdiffusion vs BindCraft
RFdiffusion: Diffusion model for de novo protein backbone design and binder design. BindCraft: One-shot de novo binder design pipeline with AF2 hallucination.
Facts below come from each project's own website, repository and paper. We don't publish benchmark claims here; see the papers for evaluations. Shared tags: design.
| Field | RFdiffusion | BindCraft |
|---|---|---|
| Task | Backbone generation, binder design, motif scaffolding | Binder design |
| Modalities | Protein (binders, symmetric assemblies) | Protein binders |
| MSA required | — | — |
| Open weights | Yes | Uses AlphaFold2 weights |
| GPU need | — | Large GPU memory needed |
| License | BSD-3-Clause | MIT |
| Pricing | Open source | Open source |
| Released | 2022-12-10 | 2024-09-29 |
| Paper | Link | Link |
| GitHub | GitHub | GitHub |
| GitHub stars | 3,090 | 1,249 |
| Interface | Package, Docker, Colab | Colab |
Specs come from each project's README, paper or official page · RFdiffusion README · RFdiffusion paper · BindCraft README · BindCraft paper. “—” means we couldn't verify it.
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