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medchem

8.7

by davila7

189Favorites
286Upvotes
0Downvotes

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

cheminformatics

8.7

Rating

0

Installs

Data & Analytics

Category

Quick Review

Excellent skill for medicinal chemistry filtering with comprehensive coverage of drug-likeness rules, structural alerts, and compound prioritization workflows. The description accurately represents capabilities, and the skill provides detailed, production-ready code examples across all major use cases (Lipinski/Veber rules, PAINS filters, structural alerts, complexity metrics). Structure is very clear with logical organization from basic to advanced patterns, appropriate use of referenced files for detailed catalogs, and practical workflow examples. The skill offers significant value by consolidating complex cheminformatics operations that would otherwise require extensive manual implementation and domain expertise. Minor limitation: while novel in aggregation, the underlying algorithms are established medicinal chemistry filters rather than cutting-edge methods, though this is appropriate for the domain where validated, interpretable rules are preferred.

LLM Signals

Description coverage9
Task knowledge10
Structure9
Novelty8

GitHub Signals

18,073
1,635
132
71
Last commit 0 days ago

Publisher

davila7

davila7

Skill Author

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davila7

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