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Structure‐Based Virtual Screening of Glycogen Synthase Kinase 3β Inhibitors: Analysis of Scoring Functions Applied to Large True Actives and Decoy Sets
Author(s) -
Osolodkin Dmitry I.,
Palyulin Vladimir A.,
Zefirov Nikolay S.
Publication year - 2011
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2011.01159.x
Subject(s) - decoy , virtual screening , gsk 3 , receiver operating characteristic , computational biology , glycogen synthase , computer science , kinase , chemistry , biology , biochemistry , machine learning , enzyme , receptor , drug discovery
Comparative assessment of nine different scoring functions (OpenEye and Tripos implementation) applied to structure‐based virtual screening based on rigid docking of the pregenerated conformations library of glycogen synthase kinase 3β (GSK‐3β) inhibitors has been carried out. The functions studied belong to the following types: Gaussian (Chemgauss3, Shapegauss), empirical (Chemscore, OEChemscore, Piecewise Linear Potential, Screenscore), force field‐based (D_score and G_score), and potential of mean force (PMF_score). Overall enrichment of the large true inhibitors set against the set of true non‐inhibitors, Directory of Useful Decoys (DUD), cyclin‐dependent kinase 2 subset, and NCI Diversity Set was evaluated by means of ROC (receiver operating characteristic) method. According to this analysis, scoring function Chemscore leads to the best enrichment of the inhibitors whereas the best early enrichment of the actives may be obtained with the help of Chemgauss3 function as estimated by BEDROC (Boltzmann‐enhanced discrimination of ROC) metrics.