Media & StreamingDocumentedScanned
refua
Refua is used in drug discovery to computationally fold and score biomolecular complexes (e.g.
Share:
Installation
npx clawhub@latest install refuaView 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()"
- Boltz2 uses
~/.boltzby default
boltz.cache_dir if needed
- BoltzGen uses a bundled HF artifact by default
boltzgen.mol_dir if needed
Running the MCP server
Start the server using the module entrypoint: ([github.com]())python3 -m refua_mcp.server