pharmaclaw-alphafold-agent
Compliant AlphaFold Agent for protein structure retrieval, ESMFold prediction, binding site detection, and RDKit ligand docking. Fetches public PDB/AlphaFold DB structures, predicts folds via ESMFold (HuggingFace), identifies binding pockets, and performs basic molecular docking. Chains from Chemistry Query (receives SMILES for docking) and feeds into IP Expansion and Catalyst Design. Triggers on alphafold, fold, PDB, docking, structure, protein, binding site, pocket, UniProt, KRAS, target.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/cheminem/pharmaclaw-alphafold-agentWhat This Skill Does
The pharmaclaw-alphafold-agent is a sophisticated module within the OpenClaw framework designed to streamline protein-ligand interactions for drug discovery. By integrating RCSB PDB structure retrieval with ESMFold-based sequence modeling, it serves as a central hub for structural biology tasks. The agent automates the process of finding existing experimental structures from the AlphaFold DB or RCSB, and when data is missing, it dynamically triggers ESMFold via HuggingFace to predict the protein fold. Furthermore, it includes specialized routines for binding site identification and RDKit-based ligand docking, allowing users to assess binding affinities and molecular positioning efficiently.
Installation
To integrate this skill into your environment, use the OpenClaw command-line interface. Run the following command in your terminal: clawhub install openclaw/skills/skills/cheminem/pharmaclaw-alphafold-agent Ensure that you have an active Python environment with sufficient resources, as ESMFold prediction can be computationally intensive for larger protein sequences.
Use Cases
- Target Validation: Quickly retrieve structural data for a known protein target using its UniProt ID.
- In-Silico Screening: Dock small molecules (SMILES) into candidate binding pockets to generate initial binding affinity scores for lead optimization.
- Novel Protein Analysis: Generate 3D structural models from FASTA sequences for proteins that have not yet been solved through X-ray crystallography or Cryo-EM.
- Pipeline Integration: Feed structural data into IP Expansion or Catalyst Design agents for integrated drug development workflows.
Example Prompts
- "Find the structure for UniProt P01116 and dock the molecule CC(=O)Nc1ccc(O)cc1 into its primary binding pocket."
- "Perform an ESMFold prediction for the sequence provided in sequence_data.fasta and identify any accessible binding sites."
- "Is there a publicly available AlphaFold structure for target KRAS? If so, retrieve it and perform a standard docking analysis with my input SMILES."
Tips & Limitations
This tool is optimized for rapid screening rather than high-fidelity physics-based simulations. While it offers a powerful workflow for early-stage discovery, note that the docking results are based on RDKit conformer scoring, which is a simplification compared to tools like AutoDock Vina. Users should treat affinity scores as relative rankings rather than absolute thermodynamic values. Always verify the PDB source, and for complex protein targets, consider refining the binding site detection using specialized standalone tools if the current pocket identification lacks required granularity.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-cheminem-pharmaclaw-alphafold-agent": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, file-read, file-write, external-api, code-execution
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