synthetic-sciences SMILES Validation
Overview
LLMs frequently generate invalid SMILES or produce molecules that don't match their stated reasoning. This skill provides strict validation, structural comparison, and modification verification.
Key checks:
- Parse validation: RDKit sanitization, valence checking, parenthesis/bracket balance
- Structural comparison: Tanimoto similarity, scaffold preservation, MCS analysis
- Modification verification: Confirm claimed structural changes exist in the actual molecule
- Classification: Categorize changes as optimization (>0.6 similarity), significant modification (0.4-0.6), or de novo design (<0.4)
When to Use This Skill
- After molecule generation: Validate every SMILES before reporting results
- Optimization verification: Confirm proposed modifications match the actual structure
- Batch validation: Check a library of generated molecules for validity
- Quality control: Ensure reproducibility of molecular designs
Installation
pip install rdkit-pypi
Core Workflows
1. Validate a Single SMILES
python scripts/validate.py --smiles "c1ccccc1"
2. Compare Original vs Modified
python scripts/validate.py --original "c1ccccc1" --proposed "c1ccc(O)cc1" --check-modification "Added hydroxyl group"
3. Batch Validation
python scripts/validate.py --input generated_molecules.csv --output validation_report.json
Script Reference
| Script | Purpose | Key Outputs |
|---|---|---|
validate.py |
SMILES validation, comparison, and modification checking | JSON report with validity, similarity, scaffold match, modification verification |