How do I install the Pharmaclaw Alphafold Agent skill?

Run npx skillmds@latest add dvcrn/pharmaclaw-alphafold-agent in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Pharmaclaw Alphafold Agent safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Pharmaclaw Alphafold Agent?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Pharmaclaw Alphafold Agent free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Pharmaclaw Alphafold Agent?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Pharmaclaw Alphafold Agent by dvcrn

Name: Pharmaclaw Alphafold Agent
Rating: 4.5 (4 reviews)
Author: dvcrn

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.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

PharmaClaw AlphaFold Agent

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

---name: pharmaclaw-alphafold-agentdescription: 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.---# PharmaClaw AlphaFold Agent## OverviewProtein 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```bash# Fetch structure and dock a ligandpython scripts/alphafold_agent.py '{"uniprot": "P01116", "smiles": "CC(=O)Nc1ccc(O)cc1"}'# Structure retrieval onlypython 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```json{ "uniprot": "P01116", "smiles": "CC(=O)Nc1ccc(O)cc1", "fasta": "path/to/sequence.fasta"}```## Output Format```json{ "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## ComplianceUses 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

Frequently asked questions