chembl-queryQuery ChEMBL database for bioactivity data on drug-like compounds. Use this skill when: (1) Finding compounds active against a protein target (target-based s...
Install via ClawdBot CLI:
clawdbot install hollyya/chembl-queryGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://www.ebi.ac.uk/chembl/api/data`Audited Apr 16, 2026 · audit v1.0
Generated May 11, 2026
A pharmaceutical company identifies a novel protein target for a disease. Using the ChEMBL query skill, researchers search for known compounds active against the target to assess druggability and prioritize hits for further screening.
A biotech startup investigating repurposing opportunities for an existing drug uses the molecule-based search to retrieve the full bioactivity profile, including all targets and activity values, to identify off-target effects or additional indications.
An academic research group studying diabetes queries ChEMBL for all drugs or compounds associated with the disease. They filter by clinical phase to identify approved drugs and those in late-stage development for systematic review.
A medicinal chemist searching for analogs of a promising hit compound uses the target-based search with a given protein target and potency threshold (e.g., IC50 ≤ 100 nM) to find structurally diverse compounds with high activity.
Offer target-based and molecule-based ChEMBL queries as part of a bioinformatics platform subscription for biotechs. Revenue from monthly/annual subscriptions and per-query fees.
Automate generation of repurposing opportunity reports for specific diseases using indication queries. Sell reports to pharma companies or research institutions.
Wrap the ChEMBL query skill into a larger API that also includes other databases (e.g., PubChem, DrugBank). Charge per API call or offer tiered plans based on usage volume.
💬 Integration Tip
Integrate as a Python module in your drug discovery pipeline. For large-scale queries, consider caching results and using bulk retrieval to avoid rate limits.
Scored May 11, 2026
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