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drug-discovery

Query ChEMBL targets and extract bioactive compounds with pChEMBL metrics for drug discovery.

Updated Apr 19, 2026
Search Tags:#pubchem#drug-discovery#chembl#opentargets#openfda#lead-optimization
One-click install
npx skills add https://github.com/gqf2008/hermez-ai --skill drug-discovery-gqf2008
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drug-discovery
Source: https://github.com/gqf2008/hermez-ai/tree/main/skills/research/drug-discovery
Command: npx skills add https://github.com/gqf2008/hermez-ai --skill drug-discovery-gqf2008

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Pharmaceutical research teams often juggle multiple data sources to identify bioactive compounds, assess drug-likeness, and predict safety implications. This skill consolidates these tasks into a single, repeatable workflow to accelerate medicinal chemistry decisions.

Core Features & Use Cases

  • Bioactive Compound Search (ChEMBL): discover compounds by target, activity, or molecule name.
  • Molecule Property & Drug-Likeness checks: retrieve MW, LogP, HBD/HBA, TPSA, pChEMBL, and QED-like metrics to guide lead optimization.
  • Safety & Interaction lookups: access OpenFDA interactions and OpenTargets disease associations to evaluate risk.
  • Open data integration: leverage PubChem for tools-free property lookups and OpenTargets for target-disease context to inform experimental planning.
  • Use Case: imagine optimizing a lead against EGFR with focus on Lipinski Ro5 and Veber rules while checking potential adverse events.

Quick Start

Ask the AI to search for a target like EGFR and retrieve top bioactive ChEMBL compounds with pChEMBL thresholds and key property metrics for lead selection.

Frequently Asked Questions about drug-discovery

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

FAQPage Schema
How do I retrieve bioactive compounds from ChEMBL for drug discovery?▼

The skill queries ChEMBL targets and extracts high-pChemBL actives to retrieve bioactive compounds for drug discovery. It identifies molecules by target, activity, or name to support target-based discovery and lead optimization.

Can I check drug-likeness properties like Lipinski Ro5 and Veber rules using PubChem?▼

Yes, you can check drug-likeness using PubChem and ChEMBL data. The workflow retrieves MW, LogP, HBD/HBA, TPSA, pChEMBL, and QED-like metrics to evaluate Lipinski Ro5 and Veber rules for lead optimization.

How do I assess drug safety and adverse events during lead optimization?▼

Assess drug safety during lead optimization by accessing OpenFDA interactions and OpenTargets disease associations. This evaluates potential adverse events and risks to inform experimental planning and safety screening.

Do I need API keys or authentication to query OpenTargets and OpenFDA?▼

No, you do not need API keys or authentication to query OpenTargets and OpenFDA. The workflow requires only free public APIs with YAML frontmatter metadata, optional references, scripts, and assets to fetch targets, activities, and properties.

What is the best way to find target-disease associations for experimental planning?▼

The best way to find target-disease associations is leveraging OpenTargets data integration. It fetches target-disease context to inform experimental planning and assess safety implications alongside ChEMBL bioactivity data.

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