medchem
CommunityFilter compounds with drug-likeness rules.
Education & Research#drug discovery#medicinal chemistry#cheminformatics#drug likeness#structural alerts#compound filtering
AuthorRowtion
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps medicinal chemists and drug discovery scientists efficiently filter and prioritize chemical compounds by applying a wide range of established drug-likeness rules, structural alerts, and complexity metrics.
Core Features & Use Cases
- Drug-Likeness Rules: Apply filters like Lipinski's Rule of Five, Veber's rules, and others to assess oral bioavailability potential.
- Structural Alerts: Detect problematic substructures (PAINS, NIBR, Lilly demerits) that can lead to assay interference or toxicity.
- Use Case: When evaluating a new library of potential drug candidates, use this Skill to quickly identify compounds that are most likely to be "drug-like" and avoid those with known liabilities.
Quick Start
Apply the Rule of Five and common structural alerts to a list of molecules.
Dependency Matrix
Required Modules
medchemdatamolrdkit-pypipandastqdm
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: medchem Download link: https://github.com/Rowtion/Bioclaw/archive/main.zip#medchem Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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