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name: pharmaclaw-cheminformatics description: Advanced cheminformatics agent for 3D molecular analysis, pharmacophore mapping, format conversion, RECAP fragmentation, and stereoisomer enumeration. The "senior cheminformatician" upgrade to Chemistry Query. Use for 3D conformer generation/ensembles (ETKDG + MMFF/UFF), pharmacophore feature extraction and fingerprints, molecular format conversion (SMILES/SDF/MOL/InChI/PDB/XYZ), RECAP retrosynthetic fragmentation for library design, stereoisomer enumeration (R/S, E/Z), and cheminformatics profiling. Chains from chemistry-query (receives SMILES) and feeds into pharmacology, catalyst-design, ip-expansion. Triggers on conformer, 3D structure, pharmacophore, SDF, MOL file, format conversion, RECAP, fragmentation, stereoisomer, chirality, enantiomer, cheminformatics, library design, building blocks, docking prep.

Cheminformatics Agent v1.0.0

Overview

Advanced cheminformatics toolkit for 3D molecular analysis and drug development workflows. Extends Chemistry Query (which handles 2D lookup/properties/visualization) with predictive and structural capabilities that require 3D reasoning.

Chemistry Query = "What is this molecule?" (2D, lookup, descriptors) Cheminformatics = "What can this molecule become?" (3D, conformers, pharmacophores, fragments, stereoisomers)

Scripts

scripts/conformer_gen.py

3D conformer ensemble generation using ETKDG with MMFF/UFF optimization.

--smiles <SMILES> --action <generate|ensemble|best> [--num_confs N] [--optimize mmff|uff|none] [--energy_window F] [--prune_rms F] [--output file.sdf]

Action	Description
generate	Generate N conformers with energies and RMSD matrix
ensemble	Same as generate + write SDF file
best	Find lowest-energy conformer with 3D coordinates

python scripts/conformer_gen.py --smiles "CC(=O)Oc1ccccc1C(=O)O" --action generate --num_confs 20
python scripts/conformer_gen.py --smiles "CCO" --action best --output best.sdf
python scripts/conformer_gen.py --smiles "c1ccccc1" --action ensemble --num_confs 50 --output benzene_confs.sdf

Output includes: conformer energies (kcal/mol), relative energies, convergence status, RMSD matrix (top 20), SDF file.

scripts/format_converter.py

Convert between molecular file formats.

--smiles <SMILES> | --input <file> --to <format> [--output file] [--batch] [--name label]

Supported formats: smiles, sdf, mol, inchi, inchikey, pdb, xyz

python scripts/format_converter.py --smiles "CCO" --to sdf --output ethanol.sdf
python scripts/format_converter.py --smiles "CCO" --to inchi
python scripts/format_converter.py --input mols.sdf --to smiles --batch
python scripts/format_converter.py --smiles "CCO" --to pdb --output ethanol.pdb

Batch mode reads multi-molecule SDF files. All 3D formats auto-generate and optimize conformers.

scripts/pharmacophore.py

Pharmacophore feature extraction, fingerprints, and comparison.

--smiles <SMILES> --action <features|fingerprint|compare|map> [--target_smiles "smi1,smi2"] [--output file.png]

Action	Description
features	Extract 3D pharmacophoric features (HBD, HBA, aromatic, hydrophobic, ionizable) with coordinates
fingerprint	Generate Gobbi 2D pharmacophore fingerprint
compare	Pairwise pharmacophore similarity (Tanimoto) across multiple molecules
map	Generate color-coded pharmacophore PNG (green=donor, red=acceptor, yellow=aromatic, blue=hydrophobic)

python scripts/pharmacophore.py --smiles "CC(=O)Oc1ccccc1C(=O)O" --action features
python scripts/pharmacophore.py --smiles "CC(=O)Oc1ccccc1C(=O)O" --action map --output pharm.png
python scripts/pharmacophore.py --target_smiles "CCO,CC(=O)O,c1ccccc1" --action compare

scripts/recap_fragment.py

RECAP (Retrosynthetic Combinatorial Analysis Procedure) fragmentation at synthetically accessible bonds (amide, ester, amine, urea, ether, olefin, sulfonamide, etc.).

--smiles <SMILES> --action <fragment|leaves|tree|common_fragments> [--target_smiles "smi1,smi2"] [--max_depth N]

Action	Description
fragment	All RECAP fragments with metadata
leaves	Terminal building blocks only (for library design)
tree	Hierarchical decomposition tree
common_fragments	Shared fragments across multiple molecules (common scaffolds)

python scripts/recap_fragment.py --smiles "CC(=O)Nc1ccc(O)cc1" --action fragment
python scripts/recap_fragment.py --smiles "CC(=O)Nc1ccc(O)cc1" --action leaves
python scripts/recap_fragment.py --target_smiles "CC(=O)Nc1ccc(O)cc1,CC(=O)Nc1ccccc1" --action common_fragments

Use case: Leaf fragments → building blocks for combinatorial library enumeration. Common fragments across a compound series → shared pharmacophoric scaffolds.

scripts/stereoisomers.py

Stereoisomer enumeration and analysis (chiral centers R/S, double bond E/Z).

--smiles <SMILES> --action <enumerate|analyze|compare> [--max_isomers N] [--only_unassigned]

Action	Description
enumerate	Generate all stereoisomers with configurations
analyze	Count chiral centers and stereo bonds without enumerating
compare	Compare properties across all stereoisomers (drug dev relevance)

python scripts/stereoisomers.py --smiles "C(F)(Cl)Br" --action enumerate
python scripts/stereoisomers.py --smiles "CC=CC" --action analyze
python scripts/stereoisomers.py --smiles "OC(F)(Cl)Br" --action compare

Drug relevance: FDA requires characterization of each stereoisomer for chiral drug candidates. Flags meso forms and provides R/S assignments.

scripts/chain_entry.py

Standard agent chain interface. Runs all 5 modules on a SMILES input.

python scripts/chain_entry.py --input-json '{"smiles": "CC(=O)Nc1ccc(O)cc1", "context": "user"}'
python scripts/chain_entry.py --input-json '{"smiles": "CCO", "actions": ["conformers", "pharmacophore"]}'

Input JSON fields:

• smiles (required): Input SMILES
• context: Chain context string
• actions: Array to run subset — ["conformers", "pharmacophore", "recap", "stereoisomers", "formats"]
• output_dir: Directory for SDF/PNG output files

Output schema:

{
  "agent": "cheminformatics",
  "version": "1.0.0",
  "smiles": "<canonical>",
  "status": "success|error",
  "report": {
    "conformers": {...},
    "pharmacophore": {...},
    "recap": {...},
    "stereoisomers": {...},
    "formats": {...}
  },
  "risks": [],
  "warnings": [],
  "viz": ["path/to/file.sdf", "path/to/pharmacophore_map.png"],
  "recommend_next": ["pharmacology", "catalyst-design", "ip-expansion"],
  "confidence": 0.9,
  "timestamp": "ISO8601"
}

Chaining

From	To	What passes
Chemistry Query →	Cheminformatics	SMILES + basic properties
Cheminformatics →	Pharmacology	SMILES + pharmacophore profile for ADME context
Cheminformatics →	Catalyst Design	3D conformer data for catalyst selection
Cheminformatics →	IP Expansion	Stereoisomers as patentable variants
Cheminformatics →	Toxicology	Fragment analysis for structural alerts

Dependencies

• Python ≥ 3.10
• rdkit-pypi
• Pillow (for pharmacophore map PNG)
• numpy