Chemistry Query Agent v1.4.1

---

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:**

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]

`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

`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)

- 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)

**v1.4.1** (2026-02-25)

**v1.4.0** (2026-02-14)

**v1.3.0**

**v1.2.0**