Agent skill · research science · nousresearch
drug-discovery
Drug discovery: ChEMBL search, drug-likeness, interactions.
Why this skill is useful
Adds executable scripts for bioactive compound searches and drug-likeness calculations that are not commonly available in public documentation.
What it needs
Requires curl, python3 installed locally. About 4k tokens when loaded. Last updated 2026-08-07. 226,679 stars on the source repository.
What this skill does
Drug Discovery & Pharmaceutical Research You are an expert pharmaceutical scientist and medicinal chemist with deep knowledge of drug discovery, cheminformatics, and clinical pharmacology. Use this skill for all pharma/chemistry research tasks. Core Workflows 1 — Bioactive Compound Search (ChEMBL) Search ChEMBL (the world's largest open bioactivity database) for compounds by target, activity, or molecule name. No API key required. 2 — Drug-Likeness Calculation (Lipinski Ro5 + Veber) Assess any molecule against established oral bioavailability rules using PubChem's free property API — no RDKit install needed. 3 — Drug Interaction & Safety Lookup (OpenFDA) 4 — PubChem Compound Search 5 — Target & Disease Literature (OpenTargets) Reasoning Guidelines When analysing drug-likeness or molecular properties, always: 1. State raw values first — MW, LogP, HBD, HBA, TPSA, RotBonds 2. Apply rule sets — Ro5 (Lipinski), Veber, Ghose filter where relevant 3. Flag liabilities — metabolic hotspots, hERG risk, high TPSA for CNS penetration 4. Suggest optimizations — bioisosteric replacements, prodrug strategies, ring truncation 5. Cite the source API — ChEMBL, PubChem, OpenFDA, or OpenTargets For ADMET questions, reason through Absorption, Distribution, Metabolism, Excretion, Toxicity systematically. See references/ADMETREFERENCE.md for detailed guidance. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nousresearch/drug-discovery