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Found 19 Skills
Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.
Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.
Query ChEMBL's bioactive molecules and drug discovery data. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.
Identify drug repurposing candidates using ToolUniverse for target-based, compound-based, and disease-driven strategies. Searches existing drugs for new therapeutic indications by analyzing targets, bioactivity, safety profiles, and literature evidence. Use when exploring drug repurposing opportunities, finding new indications for approved drugs, or when users mention drug repositioning, off-label uses, or therapeutic alternatives.
Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.
Research GPCR receptors, antibody structures, and protein interface analysis using GPCRdb, SAbDab, and PDBePISA. Retrieves receptor families, known ligands (agonists/antagonists/biased), mutations, crystal/cryo-EM structures, antibody CDR annotations, and protein-protein interface geometry. Use when asked about GPCR drug targets, receptor-ligand interactions, antibody structural data, or protein assembly interfaces.
6 pharmaceutical research skills. Trigger: drug discovery, pharmacology, clinical trial design, regulatory filing. Design: end-to-end pipeline from target identification to clinical trials.