Agent skill

chemistry-rdkit

Computational chemistry with RDKit for molecular analysis, descriptors, fingerprints, and substructure search. Use when working with SMILES, drug discovery, or cheminformatics tasks.

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Forks 1,262

Install this agent skill to your Project

npx add-skill https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/chemistry-rdkit

Metadata

Additional technical details for this skill

author
researchclaw
version
1.0
category
domain
priority
4
references
adapted from K-Dense-AI/claude-scientific-skills
trigger keywords
molecule,SMILES,chemical,drug,rdkit,fingerprint,molecular,compound,reaction,cheminformatics
applicable stages
9,10,12

SKILL.md

RDKit Cheminformatics Best Practice

Molecular I/O

  1. Create molecules from SMILES: mol = Chem.MolFromSmiles('CCO')
  2. Always check for None: MolFromSmiles returns None on invalid input
  3. Convert to canonical SMILES: Chem.MolToSmiles(mol)
  4. Read SDF files: suppl = Chem.SDMolSupplier('file.sdf')
  5. Read SMILES files: suppl = Chem.SmilesMolSupplier('file.smi')
  6. Write molecules: writer = Chem.SDWriter('output.sdf')

Molecular Descriptors

  1. Molecular weight: Descriptors.MolWt(mol)
  2. LogP (lipophilicity): Descriptors.MolLogP(mol)
  3. TPSA (polar surface area): Descriptors.TPSA(mol)
  4. H-bond donors/acceptors: Descriptors.NumHDonors(mol), Descriptors.NumHAcceptors(mol)
  5. Rotatable bonds: Descriptors.NumRotatableBonds(mol)
  6. Lipinski Rule of 5: MW <= 500, LogP <= 5, HBD <= 5, HBA <= 10

Fingerprints and Similarity

  1. Morgan (circular) fingerprints: AllChem.GetMorganFingerprintAsBitVect(mol, radius=2, nBits=2048)
  2. RDKit fingerprints: Chem.RDKFingerprint(mol)
  3. MACCS keys: MACCSkeys.GenMACCSKeys(mol)
  4. Tanimoto similarity: DataStructs.TanimotoSimilarity(fp1, fp2)
  5. Use radius=2 (ECFP4 equivalent) as default for most applications
  6. For virtual screening, Tanimoto > 0.7 suggests structural similarity

Substructure Search

  1. SMARTS patterns: pattern = Chem.MolFromSmarts('[OH]')
  2. Check match: mol.HasSubstructMatch(pattern)
  3. Get all matches: mol.GetSubstructMatches(pattern)
  4. Common SMARTS: [#6](=O)[OH] (carboxylic acid), [NH2] (primary amine)
  5. Filter compound libraries by functional group presence

Property Calculation Patterns

  1. Batch processing: iterate over SDMolSupplier, skip None entries
  2. Use Chem.Descriptors.descList for all available descriptors
  3. For ADMET filtering, calculate Lipinski, Veber, and PAINS filters
  4. Generate 3D coordinates: AllChem.EmbedMolecule(mol, AllChem.ETKDG())
  5. Minimize energy: AllChem.MMFFOptimizeMolecule(mol)

Common Pitfalls

  1. Always sanitize molecules (default behavior) — disable only when needed
  2. Add hydrogens explicitly for 3D work: Chem.AddHs(mol)
  3. Handle stereochemistry: use Chem.AssignStereochemistry(mol)
  4. Large SDF files: use ForwardSDMolSupplier for memory efficiency
  5. Kekulization errors usually indicate invalid SMILES input

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