Chemistry Rdkit

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)