medchem

Topics in the source

• Medchem
• Overview
• When to Use This Skill
• Installation
• Core Capabilities
• 1. Medicinal Chemistry Rules
• 2. Structural Alert Filters
• 3. Functional API for High-Level Operations

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. 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 Calculating molecular complexity metrics Apply established drug-likeness rules to molecules using the medchem.rules module. Available Rules: Rule of Five (Lipinski) Rule of Oprea Rule of CNS Rule of leadlike (soft and strict) Rule of three Rule of Reos Rule of drug Rule of Veber Golden triangle PAINS filters Single Rule Application: Multiple Rules with RuleFilters: Result Format: Results are returned as dictionaries with pass/fail status and detailed information for each rule. Detect potentially proble

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