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refua

Refua is used in drug discovery to computationally fold and score biomolecular

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Skill: Refua

Summary

Refua is used in drug discovery to computationally fold and score biomolecular complexes (e.g., protein–ligand/protein–protein) and optionally profile ADMET, helping prioritize which molecules to synthesize and test first in a drug discovery pipeline.

This skill runs and connects to the refua-mcp MCP server, which exposes Refua’s ā€œunified Complex APIā€ as MCP tools for:

  • Boltz2 complex folding (+ optional affinity evaluation)
  • BoltzGen design workflows
  • Optional ADMET profiling (when installed)

Clawdbot supports MCP natively, so the only requirement is running this MCP server and calling its tools. (github.com)

Installation & assets (operator steps)

1) Install Refua + refua-mcp

Install Refua (CPU or CUDA), then install the MCP server package: (github.com)

  • GPU support:
    • pip install refua[cuda]
  • CPU-only:
    • pip install refua
  • MCP server:
    • pip install refua-mcp

2) Optional: enable ADMET

ADMET tool support is optional and requires an extra: (github.com)

  • pip install refua[admet]

3) Download model/assets

Boltz2 and BoltzGen require model/molecule assets. Refua can download them automatically: (github.com)

  • python -c "from refua import download_assets; download_assets()"

Default asset locations + overrides: (github.com)

  • Boltz2 uses ~/.boltz by default
    • Override via tool option boltz.cache_dir if needed
  • BoltzGen uses a bundled HF artifact by default
    • Override via tool option boltzgen.mol_dir if needed

Running the MCP server

Start the server using the module entrypoint: (github.com)

python3 -m refua_mcp.server