drug-db-chembl

Query ChEMBL web services for targets, molecules, and bioactivity measurements.

144|21|Updated Jan 8, 2026
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill drug-db-chembl
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: drug-db-chembl
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/drug-db-chembl
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill drug-db-chembl

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill removes the manual effort of assembling curated, provenance-preserving ChEMBL datasets for targets, molecules, and bioactivity measurements.

Core Features & Use Cases

  • Target discovery: Find candidate ChEMBL targets by gene/protein name or resolve targets by UniProt accession.
  • Model-ready bioactivity retrieval: Download bioactivity records with curation filters for potency type, assay type, standardized units, equality relations, and optional pChEMBL constraints.
  • Molecule lookup and chemical search: Retrieve molecule records by ChEMBL ID/InChIKey or search by SMILES using similarity or substructure.
  • Use Case: Generate an EGFR binding-potency dataset (IC50 in nM with equality-only labels and pChEMBL filtering) suitable for QSAR/ML training and quick inspection via CSV export.

Quick Start

Query ChEMBL for EGFR IC50 binding activities filtered to standardized nM values with equality relation and pChEMBL >= 5.0, and save them to a JSON file.

Frequently Asked Questions about drug-db-chembl

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build model-ready bioactivity datasets from ChEMBL for QSAR training?

Retrieve ChEMBL bioactivity data for specific targets by querying ChEMBL web services with filters for potency type, assay type, standardized nM units, and equality relations. You can generate an EGFR IC50 binding dataset with pChEMBL filtering to ensure potency labels are suitable for QSAR and ML training.

What is pChEMBL and when do I need it for drug discovery dataset curation?

pChEMBL is a standardized potency metric computed from nM equality measurements during drug discovery dataset curation. You need it when assembling uniform potency-labeled datasets for QSAR or ML, as it normalizes diverse activity measurements into a single comparable scale for model training.

Can I search ChEMBL molecules by SMILES using similarity or substructure matching?

Search ChEMBL molecules by SMILES using similarity or substructure matching to retrieve molecule records. The Skill queries ChEMBL web services to support chemical lookup by SMILES, ChEMBL ID, or InChIKey for drug discovery dataset building.

How do I find candidate ChEMBL targets by gene name or UniProt accession?

Find candidate ChEMBL targets by querying ChEMBL web services with a gene or protein name, or resolve targets directly by UniProt accession. This retrieves curated target records needed to anchor bioactivity data retrieval for drug discovery datasets.

Does this approach export bioactivity data in JSON and CSV formats for inspection?

The dataset curation approach exports standardized bioactivity tables in both JSON and CSV formats. This enables quick inspection and integration into downstream QSAR or ML pipelines for drug discovery applications.