medchem
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
npx skills add K-Dense-AI/scientific-agent-skills --skill medchem --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Medchem ## Overview Medchem is a Python library from [datamol-io](https://github.com/datamol-io/medchem) for molecular filtering and prioritization in drug discovery. Apply literature-derived drug-likeness rules, named alert catalogs, complexity thresholds, chemical-group detection, and a custom query language to triage compound libraries at scale. Filters are context-specific guidelines — combine with domain expertise and target knowledge. **Version note:** Examples target **medchem 2.0.5** (PyPI stable, Nov 2024). Requires **Python ≥3.9**. Depends on **datamol** and **RDKit** (installed automatically). `RuleFilters` and structural filter classes return **pandas DataFrames**. Lilly demerits require optional native binaries (`mamba install lilly-medchem-rules`). ## When to Use This Skill This skill should be used when: - Applying drug-likeness rules (Lipinski, Veber, CNS, lead-like) to compound libraries - Filtering molecules by structural alerts, PAINS, or NIBR screening-deck rules - Prioritizing compounds for hit-to-lead or lead optimization - Calculating complexity metrics against ZINC-derived thresholds - Detecting functional groups or named substructure catalogs - Building m
- Overview
- When to Use This Skill
- Installation
- Core Capabilities
- 1. Medicinal Chemistry Rules
- 2. Structural Alert Filters
- 3. Named Catalog Filters (PAINS, Brenk, etc.)
- 4. Functional API
- 5. Chemical Groups
- 6. Molecular Complexity
- 7. Scaffold Constraints
- 8. Medchem Query Language
- Workflow Patterns
- Pattern 1: Initial Triage of a Compound Library
uv pip install medchem datamol mamba install -c conda-forge lilly-medchem-rules uv run python scripts/filter_molecules.py input.csv \
What does the medchem skill do?
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill medchem --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.