What question did this study set out to answer?

This study aims to assess how pocket shape and depth can predict the druggability of proteins.

May 9, 2026Open Access

Luoshu Pocket Geometry Predicts Protein Druggability: Pocket Shape and Depth as Orthogonal Geometric Signals (v3, n=85)

Key Points

This study aims to assess how pocket shape and depth can predict the druggability of proteins.
Evaluated 85 DUD-E proteins using two geometric signals from the Luoshu framework.
Measured pocket sphericity and depth to generate a composite score for predicting druggability.
Compared results with existing methods like SiteMap and pseudo-fpocket.
Achieved an area under the curve (AUC) of 0.851 for the composite score, outperforming SiteMap by +0.111.
Pocket sphericity alone has an AUC of 0.814; pocket depth contributes to the prediction with an AUC of 0.781.
Ablation studies confirm sphericity is the dominant predictor for druggability.

Abstract

v3 (ablation-validated): Two orthogonal geometric signals from the Luoshu framework predict protein druggability with AUC=0. 851 on 85 DUD-E proteins (perm-p0. 781) while chcₘax adds complementary information (removal: 0. 851->0. 814). Head-to-head vs pseudo-fpocket (same 85 proteins): +0. 103. Method: C-alpha + backbone dihedrals only, <1 second, no ML/MD/ligand data. Transparency: v1 (n=24, AUC=0. 957 proof-of-concept), v2 (n=85, AUC=0. 846 phi-weighted), v3 (n=85, AUC=0. 851 ablation-validated). Includes complete data table (druggabilityᵥ4ₜable. csv, n=85). Extends: doi: 10. 5281/zenodo. 20073888 (v2), doi: 10. 5281/zenodo. 20073303

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