cheminformatics

## What I do - Apply computational methods to chemical data analysis - Design and search chemical databases - Predict molecular properties and reactivity - Perform molecular similarity analysis - Develop quantitative structure-activity relationships (QSAR) - Visualize and analyze chemical structures ## When to use me - When searching chemical databases - When predicting molecular properties - When building QSAR/QSPR models - When analyzing molecular similarity - When virtual screening compounds - When managing chemical data ## Key Concepts ### Molecular Descriptors **Constitutional Descriptors** - Molecular weight - Atom counts (C, H, O, N, etc.) - Number of rings - LogP (lipophilicity) **Topological Descriptors** - Wiener index - Balaban index - Connectivity indices - Hydrogen bond donors/acceptors ```python # Example: Simple molecular fingerprint def morgan_fingerprint(molecule, radius=2): """Generate Morgan/ECFP fingerprint.""" # Simplified representation return { 'features': extract_substructures(molecule, radius), 'bit_vector': encode_as_bits(features), 'similarity': lambda other: tanimoto_coefficient(features, other) } ``` ### Chemical File Formats - SMILES: String representation - SDF: Structure-data file - MOL: MOL file format - PDB: 3D structure - InChI: IUPAC identifier ### Similarity Metrics - Tanimoto coefficient (Jaccard) - Dice similarity - Cosine similarity - Euclidean distance