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Table 1 Performance of various strategies to match ligand-binding pockets assessed with the area under the ROC curve (AUC). Three types of algorithms are evaluated, direct methods based on the local alignment between a pair of pockets, indirect techniques employing structure-based virtual screening to detect chemically similar binding sites, and meta-predictors combining a direct and an indirect algorithm. Direct approaches are benchmarked on APoc and TOUGH-M1 datasets, whereas indirect methods and meta-predictors are assessed against the TOUGH-M1 dataset only

From: Comparative assessment of strategies to identify similar ligand-binding pockets in proteins

Algorithm

Type

Dataset

APoc

TOUGH-M1

APoc

direct

0.82

0.65

SiteEngine

direct

0.60

0.66

G-LoSA

direct

0.77

0.69

Vina

indirect

–

0.55

rDock

indirect

–

0.67

APoc + Vina

meta

–

0.67

APoc + rDock

meta

–

0.70

SiteEngine + Vina

meta

–

0.66

SiteEngine + rDock

meta

–

0.76

G-LoSA + Vina

meta

–

0.66

G-LoSA + rDock

meta

–

0.77