drug-discovery

Automate bioactivity compound search, oral bioavailability assessment, and drug interaction lookup via ChEMBL, PubChem, and OpenFDA APIs.

Updated May 9, 2026
One-click install
npx skills add https://github.com/robertbr123/Linket-Agent --skill drug-discovery-robertbr123
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: drug-discovery
Source: https://github.com/robertbr123/Linket-Agent/tree/main/optional-skills/research/drug-discovery
Command: npx skills add https://github.com/robertbr123/Linket-Agent --skill drug-discovery-robertbr123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires curl, python3, and includes scripts (resource) and references (resource) components.

What problem does it solve?

The drug-discovery skill streamlines pharmaceutical research by automating workflows such as compound searching, drug-likeness assessment, and interaction lookup, saving time and resources in drug discovery workflows.

Core Features & Use Cases

  • Bioactive Compound Search: Search for compounds in ChEMBL, the world's largest open bioactivity database.
  • Drug-Likeness Calculation: Evaluate oral bioavailability using Lipinski's Rule of Five and Veber's Oral Bioavailability Rules.
  • Drug Interaction & Safety Lookup: Lookup drug-drug interactions via OpenFDA and interpret ADMET profiles.
  • Use Case: For medicinal chemists and pharmacologists, this skill helps in analyzing molecules, optimizing leads, and understanding drug safety.

Quick Start

Run 'search compound EGFR' to search for bioactive compounds targeted at EGFR.

Frequently Asked Questions about drug-discovery

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

FAQPage Schema
How do I search for bioactive compounds in ChEMBL for drug discovery?

To search for bioactive compounds in ChEMBL, run a compound search command like 'search compound EGFR' to query the database. This automates bioactivity compound research by integrating directly with ChEMBL API endpoints to retrieve targeted molecules.

How do I calculate oral bioavailability using Lipinski's Rule of Five?

You can calculate oral bioavailability by evaluating drug-likeness using Lipinski's Rule of Five and Veber's Oral Bioavailability Rules. The skill automates these calculations to assess molecular properties and determine if compounds are suitable for oral administration.

How do I check drug-drug interactions via OpenFDA for ADMET analysis?

To check drug-drug interactions via OpenFDA, use the drug interaction safety lookup feature to query the OpenFDA API. This retrieves interaction data and helps interpret ADMET profiles for understanding drug safety in pharmaceutical research workflows.

Do I need python3 and curl to automate pharmacology research workflows?

Yes, you need python3 and curl installed to automate pharmacology research workflows. These dependencies are required to execute the scripts that integrate with ChEMBL, PubChem, and OpenFDA APIs for compound searching and safety analysis.

What's the best way to evaluate drug-likeness for lead optimization?

The best way to evaluate drug-likeness for lead optimization is to assess oral bioavailability using Lipinski's Rule of Five and Veber's rules. This automated approach helps medicinal chemists analyze molecules and optimize leads efficiently.