Skill: cheminem/pharmaclaw-chemistry-query (version 2.0.1)

--- 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. --- # 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 ```bash # 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. ```bash python scripts/chain_entry.py --input-json '{"name": "sotorasib", "context": "user"}' ``` Output schema: ```json { "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:** ```bash # 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


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)