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pcl-chemistry-querypcl 化学查询

Agent Skill

pcl-chemistry-query 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

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请帮我安装这个 Agent Skill:pcl-chemistry-query(pcl 化学查询)
来源仓库:https://github.com/cheminempharmaclaw/pcl-chemistry-query
安装命令:
openclaw skills install pcl-chemistry-query
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openclaw skills install pcl-chemistry-query

简介

pcl-chemistry-query 基于 PubChem 与 RDKit 提供化合物查询与化学信息学分析。

  • 适用于科研、制药领域查询物质属性、结构或合成路径。
  • 支持 SMILES 解析、图像生成与物化性质预测。
  • 结果来源于公开数据库,准确性依赖原始数据来源。
  • 可用于初步筛选,但实验验证仍为必要步骤。

SKILL.md

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
system
external-apis
notes
>

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>
ActionDescriptionKey Args
propsMW, logP, TPSA, HBD, HBA, rotB, aromRings--smiles
draw2D PNG/SVG (300×300)`--smiles --output file.png --format png\svg`
retroBRICS recursive retrosynthesis`--target <SMILES\name> --depth N`
planMulti-step retro route`--target <SMILES\name> --steps N`
reactForward reaction via SMARTS--reactants "smi1 smi2" --smarts "<SMARTS>"
fingerprintMorgan fingerprint bitvector--smiles --radius 2
similarityTanimoto similarity scoring--query_smiles --target_smiles "smi1,smi2"
substructSubstructure matching--query_smiles --target_smiles "smi1,smi2"
xyz3D 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+:

MoleculeSMILESTests Passed
CaffeineCN1C=NC2=C1C(=O)N(C(=O)N2C)Cinfo, structure, props, draw, retro, plan, chain
AspirinCC(=O)Oc1ccccc1C(=O)Oinfo, structure, props, draw, retro, plan, chain
SotorasibPubChem name lookupinfo, structure, props, draw, retro, chain
IbuprofenPubChem name lookupinfo, structure, props, chain
Invalid SMILESXXXINVALIDGraceful 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]
ActionDescriptionKey Args
standardizeSalt stripping, charge normalization, tautomer enumeration--smiles
descriptors217+ molecular descriptors (RDKit full set), QED, SA Score, Lipinski/Veber rules`--smiles --descriptor_set all\druglike\physical\topological`
scaffoldMurcko scaffold extraction, generic scaffolds, diversity analysis, R-group decomposition--smiles or --target_smiles "smi1,smi2,..." --rgroup_core <SMARTS>
mcsMaximum Common Substructure across 2+ molecules--target_smiles "smi1,smi2,..."
mmpaMatched Molecular Pair Analysis — find single-point transformations--target_smiles "smi1,smi2,..."
chemspaceChemical 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

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