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SettingsResearch demo · not for clinical or commercial use
Corollary
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  2. Protein Design
  3. RFDiffusion

Protein Design · Baker Lab / Institute for Protein Design

RFDiffusion

De novo backbone generation by denoising diffusion — the binder-design workhorse.

Academic and non-commercial use onlyAcademic tier only. Commercial users are routed to BindCraft + ProteinMPNN for binder design.Non-commercial (BSD-derived)
Availability
Ready
Typical latency
7.0min
Credits per run
~3,360
Compute tier
C · Heavy

5–30min

Runs on Managed GPU endpoint

Runs on managed compute. Availability and startup time depend on current capacity.

Run this model

RFDiffusion

Required. The contig map refers to this structure's chains.

Needs target structure (pdb)

About this model

RFDiffusion generates protein backbones from noise, optionally conditioned on a target for binder design, a motif to scaffold, or a symmetry group. Experimentally validated against a wide range of targets. The standard first step of the design pipeline, followed by ProteinMPNN for sequences.

Standardized I/O contract

Every model in the Hub speaks the same contract, which is what lets the Router and the agent call any of them without special-casing.

Inputs

  • target_pdbtextarea · required

    Target structure (PDB)

  • contigstext

    Contig map

  • diffusion_stepsnumber

    Diffusion steps

Outputs

  • pdbstructure

    All-atom coordinates in PDB format, viewable and downloadable.

Specification

Hardware
2× A100
GPU memory
40 GB
Version
1.1.0
Licence
Non-commercial (BSD-derived)
Backend
ReadyManaged GPU endpoint
MCP server
mcp-protein-server

Tasks

backbone generationbinder design

Chains well with

  • ProteinMPNNInverse folding: given a backbone, design sequences that actually fold onto it.
  • ESMFoldSingle-sequence folding in seconds — no MSA, no waiting.
  • Boltz-2Structure and binding affinity in one pass, approaching FEP accuracy 1000× faster.

Source

  • Repository
diffusionbinder-designde-novoacademicflagship