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JamesFincher
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drug-discovery

Screen candidate molecules for drug-likeness and retrieve bioactivity and safety data from public APIs.

Updated May 4, 2026
Search Tags:#bioinformatics#drug discovery#medicinal chemistry#cheminformatics#ADMET#target validation#safety signals
One-click install
npx skills add https://github.com/JamesFincher/gengar --skill drug-discovery-jamesfincher
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drug-discovery
Source: https://github.com/JamesFincher/gengar/tree/main/optional-skills/research/drug-discovery
Command: npx skills add https://github.com/JamesFincher/gengar --skill drug-discovery-jamesfincher

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Drug discovery teams need fast, practical help evaluating chemical matter (bioactivity evidence, drug-likeness, and safety signals) before committing to deeper wet-lab work or clinical review.

Core Features & Use Cases

  • Bioactive compound search (ChEMBL): Find targets and retrieve top active compounds with potency-focused filters to support hypothesis generation and lead selection.
  • Drug-likeness and oral bioavailability checks (PubChem-based): Compute and interpret Lipinski Ro5 and Veber rules from readily available molecular properties to flag likely absorption issues early.
  • Safety and interaction signals (OpenFDA): Look up reported drug-drug interactions and adverse event patterns to inform risk-aware prioritization and readout planning.
  • Target–disease context (OpenTargets): Connect gene/target names to associated diseases to strengthen translational relevance for your lead series.

Quick Start

Use the drug-discovery skill to assess whether a candidate molecule meets Lipinski Ro5 and Veber oral bioavailability rules and to retrieve supporting bioactivity and safety context by asking for “Ro5/Veber screening, ChEMBL bioactivity lookup, and OpenFDA interaction/adverse-event summaries for aspirin.”

Frequently Asked Questions about drug-discovery

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

FAQPage Schema
How do I check Lipinski Ro5 and Veber rules for oral bioavailability of candidate molecules?▼

To check Lipinski Ro5 and Veber rules for oral bioavailability, the skill computes molecular properties from PubChem data and flags likely absorption issues early. It evaluates candidate molecules against standard drug-likeness criteria to support early ADMET reasoning.

Can I retrieve bioactivity evidence and active compounds from ChEMBL for target validation?▼

Yes, you can retrieve bioactivity evidence from ChEMBL by searching for specific targets. The skill queries ChEMBL endpoints to retrieve top active compounds with potency-focused filters, directly supporting target validation and lead selection workflows.

How do I look up drug-drug interactions and adverse event patterns using OpenFDA?▼

To look up drug-drug interactions and adverse event patterns using OpenFDA, the skill queries public OpenFDA endpoints for reported safety signals. It retrieves interaction context and adverse event summaries to inform risk-aware prioritization of candidate molecules.

Do I need curl and python3 to run bioinformatics and cheminformatics analysis with this skill?▼

Yes, you need curl and python3 installed for command-line execution to run bioinformatics and cheminformatics analysis. The skill requires these tools to interpret structured output from public APIs like ChEMBL, PubChem, OpenFDA, and OpenTargets.

What is the best way to connect gene targets to associated diseases for translational relevance?▼

The best way to connect gene targets to associated diseases for translational relevance is using the OpenTargets API integration. The skill queries OpenTargets endpoints to map target names to disease associations, strengthening target-to-disease translation for lead series.

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