name: rdkit
description: Use when working with RDKit for cheminformatics in Python. Covers molecular I/O, property calculation, Lipinski filters, fingerprints, similarity, 3D conformer generation, reactions, fragmentation, substructure search, MCS, stereochemistry, and tautomers.
RDKit
The primary Python library for cheminformatics. Molecular manipulation, descriptors, fingerprints, 3D generation, reactions, and more.
When to Use This Skill
- Reading/writing molecules from SMILES, SDF, MOL, PDB files
- Calculating molecular properties and drug-likeness filters (Ro5, QED)
- Computing and comparing molecular fingerprints (Morgan/ECFP, MACCS, RDKit FP)
- Generating 3D conformers (ETKDG, MMFF, UFF)
- Substructure searching and SMARTS queries
- Maximum Common Substructure (MCS) analysis
- Chemical reactions via SMARTS or RXN files
- Molecular fragmentation (BRICS, RECAP, Murcko scaffolds)
- Stereochemistry assignment and analysis
- Tautomer enumeration and molecule standardization
- Molecular visualization (2D SVG/PNG, similarity maps)
Quick Start
from rdkit import Chem
from rdkit.Chem import AllChem, Descriptors, Draw, rdMolDescriptors
# Load molecule
mol = Chem.MolFromSmiles('CC(=O)Oc1ccccc1C(=O)O') # aspirin
# Basic properties
print(Descriptors.MolWt(mol)) # 180.16
print(Descriptors.MolLogP(mol)) # 1.31
print(rdMolDescriptors.CalcNumHBD(mol)) # 1
print(rdMolDescriptors.CalcNumHBA(mol)) # 4
print(rdMolDescriptors.CalcTPSA(mol)) # 63.6
# Morgan fingerprint (ECFP4-like)
fpgen = AllChem.GetMorganGenerator(radius=2)
fp = fpgen.GetFingerprint(mol)
# 2D image
img = Draw.MolToImage(mol, size=(300, 200))
Router — What to Read
| Task |
Reference |
| SMILES, SDF, MOL, PDB, SMARTS I/O, serialization |
references/io-molecules.md |
| Descriptors, Lipinski Ro5, QED, ADME, drug filters |
references/properties-descriptors.md |
| Morgan, MACCS, RDKit FP, atom pair, similarity, diversity |
references/fingerprints-similarity.md |
| 3D conformers (ETKDG), MMFF/UFF optimization, 3D descriptors |
references/3d-conformers.md |
| Reactions (SMARTS), BRICS, RECAP, Murcko, tautomers, standardization |
references/transformations.md |
| Substructure search (SMARTS), MCS, rings, stereochemistry, pharmacophores |
references/analysis-search.md |
| Visualization: SVG/PNG, highlighting, similarity maps, grids |
references/visualization.md |
Key Modules
| Module |
Import |
Role |
Chem |
from rdkit import Chem |
Core molecule objects, I/O |
AllChem |
from rdkit.Chem import AllChem |
3D, fingerprints, reactions |
Descriptors |
from rdkit.Chem import Descriptors |
200+ 2D descriptors |
rdMolDescriptors |
from rdkit.Chem import rdMolDescriptors |
Fast C++ descriptors |
DataStructs |
from rdkit import DataStructs |
Fingerprint similarity |
Draw |
from rdkit.Chem import Draw |
2D visualization |
rdMolDraw2D |
from rdkit.Chem.Draw import rdMolDraw2D |
SVG/Cairo rendering |
MACCSkeys |
from rdkit.Chem import MACCSkeys |
MACCS fingerprints |
rdFMCS |
from rdkit.Chem import rdFMCS |
Maximum Common Substructure |
BRICS |
from rdkit.Chem import BRICS |
BRICS fragmentation |
Recap |
from rdkit.Chem import Recap |
RECAP fragmentation |
MurckoScaffold |
from rdkit.Chem.Scaffolds import MurckoScaffold |
Scaffold extraction |
rdMolStandardize |
from rdkit.Chem.MolStandardize import rdMolStandardize |
Tautomers, cleanup |
rdChemReactions |
from rdkit.Chem import rdChemReactions |
Reaction handling |
Installation
# conda (recommended)
conda install -c conda-forge rdkit
# pip (official wheel since 2022)
pip install rdkit
# verify
python -c "from rdkit import Chem; print(Chem.MolFromSmiles('c1ccccc1'))"
Related Skills
deepchem — ML models on molecular datasets built on top of RDKitcheminformatics — SMILES notation, file formats, molecular representationsnextflow — Pipeline execution for high-throughput molecular workflows
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