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How to design a binder against a target protein with RFdiffusion

Diffuse a binder against a target chain, using hotspot residues to aim it at the right surface.

Short answer: Set up the repo and the SE3nv environment as in the installation section; then run ./scripts/run_inference.py 'contigmap.contigs=[B1-100/0 100-100]' inference.output_prefix=test_outputs/binder_test inference.num_designs=10 with your target as chain B; Aim the binder at the interface with hotspot residues, specified as 'ppi.hotspot_res=[A30,A33,A34]'. All steps.

platform. Diffusion is computationally intensive, so a large uncropped target makes runs very slow.

Who it is forA team looking for de novo binders to a receptor or antigen.

The problemBinder campaigns are slow and the model will otherwise bind the wrong patch.

The outcomeA set of candidate binder backbones aimed at the interface you chose.

What you need first

  • A clone of the repo plus the model weights downloaded into its models folder
  • Anaconda or Miniconda, and NVIDIA's SE(3)-Transformer installed from the env folder
  • An NVIDIA GPU; the provided environment file targets CUDA 11.1 and may need adapting
  • Docker as an alternative to the conda setup, using the provided docker/Dockerfile

Steps

  1. Set up the repo and the SE3nv environment as in the installation section
  2. Run ./scripts/run_inference.py 'contigmap.contigs=[B1-100/0 100-100]' inference.output_prefix=test_outputs/binder_test inference.num_designs=10 with your target as chain B
  3. Aim the binder at the interface with hotspot residues, specified as 'ppi.hotspot_res=[A30,A33,A34]'
  4. For more diverse topologies try the beta model with inference.ckpt_override_path=models/Complex_beta_ckpt.pt, and see ./examples/design_ppi.sh

Prompt for your agent

With RosettaCommons/RFdiffusion, design 10 binders to residues 1-100 of chain B in <my target pdb> with hotspot residues <my hotspots>, and explain how to pick the hotspots from the structure.

Caveat. The beta model generates more topologies but the README says it has not been extensively experimentally validated.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for RosettaCommons/RFdiffusion and "Design a binder against a target protein"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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