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smiles-validation

Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.

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Files included (2)

  • SKILL.md2.0 KB
  • scripts/validate.py8.8 KB

SKILL.md (original)

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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

ScriptPurposeKey Outputs
validate.pySMILES validation, comparison, and modification checkingJSON report with validity, similarity, scaffold match, modification verification

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