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medchem

Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.

backend/cli/skills/chemistry/medchem/SKILL.md

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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