Agent skill · research science · aiskillstore
medchem
Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.
Why this skill is useful
Adds executable scripts for applying complex medicinal chemistry rules and filters that enhance compound prioritization workflows.
What it needs
Requires medchem installed locally. About 5k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
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 Calculating molecular complexity metrics Installation Core Capabilities 1. Medicinal Chemistry Rules 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. 2. Structural Alert Filters Detect potentially problematic structural patterns using the medchem.structural module. Available Filters: 1. Common Alerts - General structural alerts derived from ChEMBL curation and literature 2. NIBR Filters - Novartis Institutes for BioMedical Research filter set 3. Lilly Demerits - Eli Lilly's demerit-based system (275 rules, molecules rejected at >100 demerits) Common Alerts: NIBR Filters: Lilly Demerits: 3. Functional API for High-Level Operations The medchem.functional module provides convenient functions for common workflows. Quick Filtering: 4. Chemical Groups Detection Identify specific chemical groups and functional groups using medchem.groups. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/medchem--b5ef1b