Medchem Filters
Skill ActiveMedicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering. Part of the AlterLab Academic Skills suite.
To efficiently filter and prioritize chemical compounds in drug discovery workflows by applying established medicinal chemistry rules, structural alerts, and complexity metrics.
Features
- Apply drug-likeness rules (Lipinski, Veber, CNS)
- Filter by structural alerts (PAINS, NIBR, Lilly Demerits)
- Calculate molecular complexity
- Detect specific chemical groups
- Command-line interface for batch processing
Use Cases
- Screening large compound libraries for drug-like properties
- Prioritizing hits during lead optimization
- Identifying potentially problematic substructures
- Assessing synthetic accessibility and complexity
Non-Goals
- Performing molecular dynamics simulations
- Designing novel molecular structures
- Predicting biological activity beyond property filters
- Replacing experimental validation
Workflow
- Load molecular data from input file (SMILES, SDF, CSV).
- Apply selected filters (rules, alerts, complexity, constraints).
- Combine results and generate an output file.
- Optionally generate a summary report of filtering statistics.
Trust
- info:Issues Attention2 issues were opened in the last 90 days, and 0 were closed. While there are open issues, the total volume is low and doesn't indicate a severe maintenance issue.
Execution
- warning:Pinned dependenciesWhile dependencies are listed, there is no lockfile present (e.g., `requirements.txt` or `uv.lock`) to ensure pinned versions, posing a risk for reproducibility.
Installation
npx skills add AlterLab-IEU/AlterLab-Academic-SkillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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