rdkit

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Cheminformatics with RDKit. Use for molecular analysis, drug-likeness, fingerprints, and similarity.

omar-A-hassan By omar-A-hassan schedule Updated 2/20/2026

name: rdkit description: "Cheminformatics with RDKit. Use for molecular analysis, drug-likeness, fingerprints, and similarity."

RDKit — Cheminformatics

When to Use

  • Analyzing molecules from SMILES strings
  • Computing physicochemical properties (MW, LogP, TPSA, etc.)
  • Drug-likeness assessment (Lipinski, Veber, etc.)
  • Molecular similarity (Tanimoto with Morgan fingerprints)
  • Molecular fingerprint generation

Available Tools

  • analyze_molecule(smiles) — Full property profile
  • lipinski_filter(smiles) — Rule of Five check
  • molecular_similarity(smiles1, smiles2) — Tanimoto similarity

SMILES Reference

SMILES (Simplified Molecular Input Line Entry System) is a line notation for molecular structures:

  • CC(=O)OC1=CC=CC=C1C(=O)O — Aspirin
  • CC(C)CC1=CC=C(C=C1)C(C)C(=O)O — Ibuprofen
  • CN1C=NC2=C1C(=O)N(C(=O)N2C)C — Caffeine

Drug-Likeness Rules

  • Lipinski's Rule of Five: MW≤500, LogP≤5, HBD≤5, HBA≤10 (≤1 violation)
  • Veber: RotBonds≤10, TPSA≤140
  • Lead-like: MW 250-350, LogP -1 to 3, RotBonds≤7

Similarity Interpretation

  • Tanimoto > 0.85 — Very similar, likely same scaffold
  • Tanimoto 0.7-0.85 — Similar, may share target activity
  • Tanimoto 0.4-0.7 — Moderate, may share pharmacophore features
  • Tanimoto < 0.4 — Dissimilar
Install via CLI
npx skills add https://github.com/omar-A-hassan/medsci-agent --skill rdkit
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