drug-discovery

Retrieve bioactivity and drug-likeness data from ChEMBL, PubChem, and OpenFDA APIs.

19|4|Updated Apr 22, 2026
One-click install
npx skills add https://github.com/carterwayneskhizeine/hermes-agent-windows-R --skill drug-discovery-carterwayneskhizeine
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drug-discovery
Source: https://github.com/carterwayneskhizeine/hermes-agent-windows-R/tree/main/optional-skills/research/drug-discovery
Command: npx skills add https://github.com/carterwayneskhizeine/hermes-agent-windows-R --skill drug-discovery-carterwayneskhizeine

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you research drug discovery candidates by quickly pulling bioactivity data, estimating drug-likeness, and summarizing interaction and safety signals from public sources.

Core Features & Use Cases

  • Bioactive compound and target search (ChEMBL): Find targets, retrieve top active molecules, and inspect molecule-level properties.
  • Drug-likeness screening (PubChem + rule sets): Compute practical property summaries and apply Lipinski Ro5 and Veber oral bioavailability checks.
  • Interaction and safety lookups (OpenFDA): Retrieve label-reported drug–drug interactions and adverse event mentions to support early risk triage.
  • ADMET-style reasoning support: Use the provided ADMET reference to interpret absorption, distribution, metabolism, excretion, and toxicity themes during lead optimization discussions.
  • Use Case: When you have a lead molecule name or an EGFR target concept, you can fetch candidate bioactivity context from ChEMBL, run Ro5/Veber-style assessments from PubChem, and then query OpenFDA for interaction/safety signals relevant to your compound or drug candidate.

Quick Start

Use the drug-discovery skill to evaluate a compound's oral-likeness by running it for the molecule name you are investigating (e.g., 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 drug-likeness using Lipinski Ro5 and Veber rules for a compound?▼

Check drug-likeness by retrieving molecular properties from PubChem and applying Lipinski Ro5 and Veber oral bioavailability rules via bundled Python scripts to compute property thresholds.

How do I retrieve bioactivity data for drug discovery targets from ChEMBL?▼

Retrieve bioactivity data by querying the ChEMBL API to find targets, fetch top active molecules, and inspect molecule-level properties for medicinal chemistry workflows.

Can I use OpenFDA to look up drug interactions and adverse events for early ADMET triage?▼

Use OpenFDA to query label-reported drug interactions and adverse event mentions, providing safety summaries that support early ADMET risk triage for drug candidates.

What is the best way to evaluate a lead molecule's oral bioavailability before lead optimization?▼

Evaluate oral bioavailability by pulling molecular properties from PubChem and running rule-based drug-likeness screenings using Lipinski Ro5 and Veber parameters against computed thresholds.

Do I need Python to compute molecular property thresholds for cheminformatics screening?▼

Python is optional but supported through bundled helper scripts that compute and report property thresholds, while core data retrieval relies on executing curl-backed API calls.

Are there limitations to using public chemical APIs for early drug discovery workflows?▼

Limitations include dependency on public API availability for ChEMBL, PubChem, and OpenFDA, meaning data retrieval requires network access and rule-based screening serves only early triage rather than definitive ADMET conclusions.