📦 Pharmaclaw Alphafold Agent — 技能工具

v1.0.0

Compliant AlphaFold Agent for protein structure retrieval, ESMFold prediction, binding site detection, and RDKit ligand docking. Fetches public PDB/AlphaFold...

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by @cheminem (Cheminem)·MIT-0

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License

MIT-0

最后更新

2026/3/11

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OpenClaw

安全

high confidence

The skill's code, instructions, and external calls are consistent with a lightweight, proof‑of‑concept AlphaFold/ESMFold + RDKit agent; it does not ask for credentials or hidden endpoints, though several capabilities are mocked and the script has bugs and is not production-grade.

安全有层次，运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发，无需署名。

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运行时依赖

无特殊依赖

版本

latestv1.0.02026/3/11

pharmaclaw-alphafold-agent v1.0.0 - Initial release of a compliant AlphaFold agent for protein structure retrieval, ESMFold prediction, binding pocket detection, and basic RDKit ligand docking. - Supports fetching public PDB/AlphaFold DB structures, predicting 3D folds, detecting pockets, and docking ligands using SMILES input. - Integrates into multi-step pipelines with clear input/output JSON formats and chain connectivity. - Operates fully on open-source/commercially permissible resources; does not require proprietary servers. - Includes limitations for docking (RDKit scoring) and binding site detection refinement.

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安装命令

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官方npx clawhub@latest install pharmaclaw-alphafold-agent

🇨🇳 镜像加速npx clawhub@latest install pharmaclaw-alphafold-agent --registry https://cn.longxiaskill.com

技能文档

Overview

Protein structure retrieval and ligand docking agent for the PharmaClaw drug discovery pipeline. Fetches experimental structures from RCSB PDB and predicted structures from AlphaFold DB, detects binding sites, and performs conformer-based docking with RDKit.

Quick Start

# Fetch structure and dock a ligand
python scripts/alphafold_agent.py '{"uniprot": "P01116", "smiles": "CC(=O)Nc1ccc(O)cc1"}'# Structure retrieval only
python scripts/alphafold_agent.py '{"uniprot": "P01116"}'

Capabilities

Feature	Method	Source
Structure Fetch	RCSB Search API + AlphaFold DB	Public PDB files
Fold Prediction	ESMFold via HuggingFace	Sequence → 3D structure
Binding Sites	Pocket detection	Residue-level pockets
Ligand Docking	RDKit conformer generation	SMILES → affinity score

Decision Tree

UniProt ID provided? → Fetch from RCSB PDB / AlphaFold DB
FASTA sequence provided? → Predict fold via ESMFold
SMILES provided? → Dock ligand into detected binding pocket
No structure found? → Fall back to ESMFold prediction

Input Format

{
  "uniprot": "P01116",
  "smiles": "CC(=O)Nc1ccc(O)cc1",
  "fasta": "path/to/sequence.fasta"
}

Output Format

{
  "pdb": "1abc.pdb",
  "sites": [{"res": "G12", "pocket_vol": 150}],
  "docking": {"affinity": -15.2, "viz": "docked.png"},
  "compliance": "Public AlphaFold 2 DB/ESMFold (commercial OK)"
}

Chain Integration

Receives from: Chemistry Query (SMILES for docking), Literature (target proteins)
Feeds into: IP Expansion (novel binding modes), Catalyst Design (structure-guided synthesis)

Dependencies

rdkit-pypi — Conformer generation and molecular descriptors
biopython — PDB parsing and FASTA sequence handling
requests — API calls to RCSB and AlphaFold DB

Compliance

Uses only publicly available protein structures (RCSB PDB, AlphaFold DB) and open-source prediction (ESMFold). All data sources are commercially permissible. No proprietary AlphaFold 3 server calls.

Scripts

scripts/alphafold_agent.py — Main agent: fetch, predict, detect sites, dock

Limitations

Docking uses RDKit conformer scoring (not full physics-based docking like Vina)
ESMFold prediction requires significant compute for large proteins
Binding site detection is simplified; production use should integrate fpocket or P2Rank

数据来源：ClawHub ↗ · 中文优化：龙虾技能库