Individual skill
medchem
Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.
cli-tool/components/skills/scientific/medchem/SKILL.md
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- Last checked
- Nov 4, 2026
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- License
- MIT
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# Medchem
## Overview
Medchem is a Python library for molecular filtering and prioritization in drug discovery workflows. Apply hundreds of well-established and novel molecular filters, structural alerts, and medicinal chemistry rules to efficiently triage and prioritize compound libraries at scale. Rules and filters are context-specific—use as guidelines combined with domain expertise.
## When to Use This Skill
This skill should be used when:
- Applying drug-likeness rules (Lipinski, Veber, etc.) to compound libraries
- Filtering molecules by structural alerts or PAINS patterns
- Prioritizing compounds for lead optimization
- Assessing compound quality and medicinal chemistry properties
- Detecting reactive or problematic functional groups