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Pharmaclaw Chemistry Query

面向化学任务的工具集:通过 PubChem、ChEMBL、PubMed 公共 API 检索化合物信息与文献,并用 RDKit 计算分子性质、生成 2D 结构图、指纹与相似性匹配、BRICS 逆合成与多步合成路线规划,另含标准化、扩展描述符、骨架分析、MCS、MMPA、化学空间可视化等高级功能,输出结构化 JSON 与图像文件。

cheminem
cheminem
热度 94.14
最近更新 2026-05-11 17:26:00
分类:数据依赖:代码执行 / 第三方 API / 读写文件应用场景:研究 / 数据处理 / API 集成

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add pharmaclaw-chemistry-query
Metadata
name
pharmaclaw-chemistry-query
description
Chemistry agent skill for PubChem API queries (compound info/properties, structures/SMILES/images, synthesis routes/references) + RDKit cheminformatics (SMILES to molecule props/logP/TPSA, 2D PNG/SVG viz, Morgan fingerprints, retrosynthesis/BRICS disconnects, multi-step synth planning). Use for chemistry tasks involving compounds, molecules, structures, PubChem data, RDKit analysis, SMILES processing, synthesis routes, retrosynthesis, reaction simulation. Triggers on chemistry, compounds, molecules, chemical data/properties, PubChem, RDKit, SMILES, structures, synthesis, reactions, retrosynthesis, synth plan/route.
type
code
dependencies
{"python":">=3.10","python-packages":["rdkit","gradio","pandas","Pillow"],"system":["java (JRE 8+ for OPSIN, optional — only needed for IUPAC name→SMILES conversion)"],"external-apis":["PubChem REST API (public, no key required)","ChEMBL API (public, no key required)","PubMed/NCBI E-utilities (public, no key required)"],"notes":"OPSIN JAR (13.8MB) is auto-downloaded on first use of IUPAC name conversion with pinned SHA-256 checksum verification (d25bc08f...). All other functionality works without Java/OPSIN.\n"}

Chemistry Query Agent v1.4.1

Overview

Full-stack chemistry toolkit combining PubChem data retrieval with RDKit molecule processing, visualization, analysis, retrosynthesis, and synthesis planning. All outputs are structured JSON for easy downstream chaining. Generates PNG/SVG images on demand.

Key capabilities:

  • PubChem compound lookup (info, structure, synthesis refs, similarity search)
  • RDKit molecular properties (MW, logP, TPSA, HBD/HBA, rotatable bonds, aromatic rings)
  • 2D molecule visualization (PNG/SVG)
  • BRICS retrosynthesis with recursive depth control
  • Multi-step synthesis route planning
  • Forward reaction simulation with SMARTS templates
  • Morgan fingerprints and similarity/substructure search
  • 21 named reaction templates (Suzuki, Heck, Grignard, Wittig, Diels-Alder, etc.)

Quick Start

# PubChem compound info
exec python scripts/query_pubchem.py --compound "aspirin" --type info

# Molecular properties from SMILES
exec python scripts/rdkit_mol.py --smiles "CC(=O)Oc1ccccc1C(=O)O" --action props

# Retrosynthesis
exec python scripts/rdkit_mol.py --target "CC(=O)Oc1ccccc1C(=O)O" --action retro --depth 2

# Full chain (name → props + draw + retro)
exec python scripts/chain_entry.py --input-json '{"name": "caffeine", "context": "user"}'

Scripts

scripts/query_pubchem.py

PubChem REST API queries with automatic name→CID resolution and timeout handling.

--compound <name|CID> --type <info|structure|synthesis|similar> [--format smiles|inchi|image|json] [--threshold 80]
  • info: Formula, MW, IUPAC name, InChIKey (JSON)
  • structure: SMILES, InChI, image URL, or full JSON
  • synthesis: Synonyms/references for a compound
  • similar: Similar compounds by 2D fingerprint (top 20)

scripts/rdkit_mol.py

RDKit cheminformatics engine. Resolves names via PubChem automatically.

--smiles <SMILES> --action <props|draw|fingerprint|similarity|substruct|xyz|react|retro|plan>
Action Description Key Args
props MW, logP, TPSA, HBD, HBA, rotB, aromRings --smiles
draw 2D PNG/SVG (300×300) --smiles --output file.png --format png|svg
retro BRICS recursive retrosynthesis --target <SMILES|name> --depth N
plan Multi-step retro route --target <SMILES|name> --steps N
react Forward reaction via SMARTS --reactants "smi1 smi2" --smarts "<SMARTS>"
fingerprint Morgan fingerprint bitvector --smiles --radius 2
similarity Tanimoto similarity scoring --query_smiles --target_smiles "smi1,smi2"
substruct Substructure matching --query_smiles --target_smiles "smi1,smi2"
xyz 3D coordinates (MMFF optimized) --smiles

scripts/chain_entry.py

Standard agent chain interface. Accepts {"smiles": "...", "context": "..."} or {"name": "...", "context": "..."}. Returns unified JSON with props, visualization, and retrosynthesis.

python scripts/chain_entry.py --input-json '{"name": "sotorasib", "context": "user"}'

Output schema:

{
  "agent": "chemistry-query",
  "version": "1.4.0",
  "smiles": "<canonical>",
  "status": "success|error",
  "report": {"props": {...}, "draw": {...}, "retro": {...}},
  "risks": [],
  "viz": ["path/to/image.png"],
  "recommend_next": ["pharmacology", "toxicology"],
  "confidence": 0.95,
  "warnings": [],
  "timestamp": "ISO8601"
}

scripts/templates.json

21 named reaction templates with SMARTS, expected yields, conditions, and references. Includes: Suzuki, Heck, Buchwald-Hartwig, Grignard, Wittig, Diels-Alder, Click, Sonogashira, Negishi, and more.

Chaining

  1. Name → Full Profile: chain_entry.py with {"name": "ibuprofen"} → props + draw + retro
  2. Chemistry → Pharmacology: Output feeds directly into pharma-pharmacology-agent
  3. Retro + Viz: Get precursors, then draw each one
  4. Suzuki Test: --action react --reactants "c1ccccc1Br c1ccccc1B(O)O" --smarts "[c:1][Br:2].[c:3][B]([c:4])(O)O>>[c:1][c:3]"

Tested With

All features verified end-to-end with RDKit 2024.03+:

Molecule SMILES Tests Passed
Caffeine CN1C=NC2=C1C(=O)N(C(=O)N2C)C info, structure, props, draw, retro, plan, chain
Aspirin CC(=O)Oc1ccccc1C(=O)O info, structure, props, draw, retro, plan, chain
Sotorasib PubChem name lookup info, structure, props, draw, retro, chain
Ibuprofen PubChem name lookup info, structure, props, chain
Invalid SMILES XXXINVALID Graceful JSON error
Empty input {} Graceful JSON error

Resources

  • references/api_endpoints.md — PubChem API endpoint reference and rate limits
  • scripts/rdkit_reaction.py — Legacy reaction module
  • scripts/chembl_query.py, scripts/pubmed_search.py, scripts/admet_predict.py — Additional query modules

scripts/advanced_chem.py

Advanced cheminformatics engine with 6 Tier 1 capabilities.

--action <standardize|descriptors|scaffold|mcs|mmpa|chemspace> --smiles <SMILES> [options]
Action Description Key Args
standardize Salt stripping, charge normalization, tautomer enumeration --smiles
descriptors 217+ molecular descriptors (RDKit full set), QED, SA Score, Lipinski/Veber rules --smiles --descriptor_set all|druglike|physical|topological
scaffold Murcko scaffold extraction, generic scaffolds, diversity analysis, R-group decomposition --smiles or --target_smiles "smi1,smi2,..." --rgroup_core <SMARTS>
mcs Maximum Common Substructure across 2+ molecules --target_smiles "smi1,smi2,..."
mmpa Matched Molecular Pair Analysis — find single-point transformations --target_smiles "smi1,smi2,..."
chemspace Chemical space visualization (PCA/t-SNE/UMAP scatter plot PNG) --target_smiles "smi1,smi2,..." --method pca|tsne|umap --output plot.png

Examples:

# Standardize a salt form
python scripts/advanced_chem.py --action standardize --smiles "[Na+].CC(=O)[O-]"

# Full descriptors (217+)
python scripts/advanced_chem.py --action descriptors --smiles "CC(=O)Oc1ccccc1C(=O)O" --descriptor_set all

# Scaffold diversity of a set
python scripts/advanced_chem.py --action scaffold --target_smiles "CC(=O)Oc1ccccc1C(=O)O,CN1C=NC2=C1C(=O)N(C(=O)N2C)C,CC(C)Cc1ccc(cc1)C(C)C(=O)O"

# MCS of aspirin and salicylic acid
python scripts/advanced_chem.py --action mcs --target_smiles "CC(=O)Oc1ccccc1C(=O)O,c1ccccc1C(=O)O"

# Matched molecular pairs
python scripts/advanced_chem.py --action mmpa --target_smiles "c1ccc(CC(=O)O)cc1,c1ccc(CCC(=O)O)cc1"

# Chemical space PCA plot
python scripts/advanced_chem.py --action chemspace --target_smiles "CC(=O)Oc1ccccc1C(=O)O,CN1C=NC2=C1C(=O)N(C(=O)N2C)C,c1ccccc1" --method pca --output space.png

Changelog

v2.0.0 (2026-02-28)

  • NEW: advanced_chem.py with 6 Tier 1 cheminformatics capabilities
    • Molecular Standardization & Tautomer Enumeration (salt stripping, charge normalization, canonical tautomers)
    • Extended Descriptors (217+ RDKit descriptors, QED, SA Score, Lipinski, Veber)
    • Scaffold Analysis (Murcko, generic scaffolds, diversity ratio, R-group decomposition)
    • Maximum Common Substructure (rdFMCS with coverage per molecule)
    • Matched Molecular Pair Analysis (rdMMPA fragmentation, transformation detection)
    • Chemical Space Visualization (PCA/t-SNE/UMAP with matplotlib scatter plots)
  • Dependencies: scikit-learn, matplotlib (added)

v1.4.1 (2026-02-25)

  • Security hardening: input sanitization for all subprocess calls (SMILES, compound names, output paths)
  • Added _sanitize_input() — length limits, null-byte rejection for all user inputs
  • Added _sanitize_output_path() — prevents path traversal, restricts extensions, blocks arbitrary file writes
  • Added shell metacharacter rejection in resolve_target()
  • Added SMILES validation via RDKit in chem_ui.py before subprocess calls
  • Added compound input validation in query_pubchem.py (length/null-byte checks)
  • Added timeout to resolve_target() PubChem subprocess call
  • Addresses VirusTotal "suspicious" classification for argument injection vectors

v1.4.0 (2026-02-14)

  • Fixed PubChem SMILES/InChI endpoint (property/CanonicalSMILES/TXT)
  • Fixed chain_entry.py HTML entity corruption
  • Fixed brics_retro to handle BRICSDecompose string output correctly
  • Added request timeouts (15s) to all PubChem calls
  • Graceful error handling for invalid SMILES and empty input
  • Updated chain output version and schema
  • Comprehensive end-to-end testing

v1.3.0

  • RDKit props NoneType fixes, invalid SMILES graceful errors
  • React fix: ReactionFromSmarts import
  • Name resolution via PubChem for all RDKit actions

v1.2.0

  • BRICS retrosynthesis + 21 reaction templates library
  • Multi-step synthesis planning