Media & StreamingDocumentedScanned

refua

Refua is used in drug discovery to computationally fold and score biomolecular complexes (e.g.

Share:

Installation

npx clawhub@latest install refua

View the full skill documentation and source below.

Documentation

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 “unified Complex API” 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