Skill UI

Datamol wraps RDKit with Pythonic APIs tailored for drug discovery, offering SMILES/SELFIES/InChI parsing, standardization, descriptor and fingerprint calculation, clustering, 3D conformer workflows, and parallel/cloud-aware batch I/O while returning native rdkit.Chem.Mol objects.

Molfeat is a Python toolkit that converts SMILES/RDKit molecules into embeddings via 100+ calculators, transformers, and pretrained models for QSAR, screening, similarity search, and deep learning pipelines.

RDKit delivers a Python-based cheminformatics toolkit for parsing SMILES/SDF, computing descriptors, generating 2D/3D coordinates, fingerprinting, searching substructures, managing reactions, and visualizing molecules, ideal for drug discovery and computational chemistry workflows.

Pythonic wrapper around RDKit for drug discovery workflows: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel batch processing. Returns native RDKit Mol objects.

Unified Python library with 100+ molecular featurizers and pretrained embeddings. Converts SMILES or RDKit molecules into ML-ready numerical features for QSAR modeling, virtual screening, similarity search, and deep learning.

Python cheminformatics toolkit for fine-grained molecular control: SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D coordinate generation, similarity, reactions, and visualization.