Published August 18, 2026
| Version v1.0.1
Software
Open
Lacuna: Cryptic Binding Pocket Discovery via Conformational Ensemble Analysis
Authors/Creators
Description
Lacuna discovers cryptic binding pockets in proteins by generating a conformational ensemble, detecting pockets per conformer, clustering across the ensemble, and ranking the resulting sites with a learned model. On CryptoBench's designated test fold (n=178) it recovers 66.3% of known cryptic sites in its top 5 with the protein-language-model ranker, under a size-robust Jaccard criterion, against 63.5% for P2Rank, 61.8% for IF-SitePred and 43.8% for fpocket. The difference from P2Rank is not statistically separable. Runs on CPU with an Anisotropic Network Model backend.
Notes
Files
mooreneural/lacuna-v1.0.1.zip
Files
(21.4 MB)
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md5:1b31cad249fbadb5a274189820c45934
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Additional details
Related works
- Is supplement to
- Software: https://github.com/mooreneural/lacuna/tree/v1.0.1 (URL)
Software
- Repository URL
- https://github.com/mooreneural/lacuna