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matthew-johnson
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drug-discovery

Identify and analyze drug-like compounds using ChEMBL, PubChem, OpenFDA, and OpenTargets APIs.

Updated Apr 20, 2026
Search Tags:#bioinformatics#cheminformatics#drug-discovery#chembl#pharmacology#openfda#lead-optimization
One-click install
npx skills add https://github.com/matthew-johnson/hermes-agent --skill drug-discovery-matthew-johnson
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drug-discovery
Source: https://github.com/matthew-johnson/hermes-agent/tree/main/optional-skills/research/drug-discovery
Command: npx skills add https://github.com/matthew-johnson/hermes-agent --skill drug-discovery-matthew-johnson

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Pharmaceutical researchers need an integrated, open and scriptable workflow to quickly identify bioactive molecules, evaluate drug-likeness, assess interactions, and interpret ADMET, reducing cycle times in lead optimization.

Core Features & Use Cases

  • Bioactive compound search: query ChEMBL targets and fetch top active molecules with pChEMBL filtering.
  • Drug-likeness assessment: compute Ro5, Veber parameters (MW, LogP, HBD/HBA, TPSA, rotatable bonds) and flag liabilities for oral bioavailability.
  • Drug interactions & safety: look up interactions via OpenFDA and surface adverse event signals.
  • Lead optimization guidance: interpret PubChem properties and ADMET profiles to suggest refinements.

Quick Start

Run the provided Python scripts to perform a targeted ChEMBL search and evaluate Ro5/Veber compliance for candidate molecules.

Frequently Asked Questions about drug-discovery

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

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

To assess drug-likeness for lead optimization, compute Rule of Five and Veber parameters including molecular weight, LogP, hydrogen bond donors and acceptors, TPSA, and rotatable bonds to flag potential oral bioavailability liabilities.

Can I check drug interactions and adverse events using OpenFDA?▼

To interpret ADMET profiles during lead optimization, analyze PubChem properties and evaluate absorption, distribution, metabolism, excretion, and toxicity data to suggest structural refinements for candidate molecules.

Do I need API keys to query PubChem and OpenTargets for pharmacology data?▼

The drug discovery workflow focuses on target-based screening and lead optimization, meaning it evaluates drug-like compounds for specific targets rather than performing high-throughput phenotypic screening or virtual library generation.

What is the best way to evaluate oral bioavailability liabilities in medicinal chemistry?▼

After lead optimization, the next step is to export the refined candidate molecules and ADMET profiles to format conversion pipelines or downstream clinical trial preparation tools to generate actionable research reports.

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