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Lacuna: Cryptic Binding Pocket Discovery via Conformational Ensemble Analysis

Authors: Moore, Clayton W.;

Lacuna: Cryptic Binding Pocket Discovery via Conformational Ensemble Analysis

Abstract

Lacuna discovers cryptic binding pockets in proteins by generating a conformational ensemble, detecting pockets per conformer, clustering across the ensemble, and ranking by a continuous crypticity score. Evaluated on 22 cryptic-pocket apo/holo pairs (7/22, 32% under a size-robust Jaccard-or-centroid criterion; 59% under the legacy size-gameable recall metric). Uses an Anisotropic Network Model backend on CPU (~1-8 s/protein).

If you use Lacuna in your research, please cite it as below.

Keywords

protein-structure, cryptic-pockets, conformational-ensemble, drug-discovery, computational-biology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average