Fragment and knowledge-based design of selective GSK-3β inhibitors using virtual screening models

Abstract

Glycogen Synthase Kinase 3beta is one of the important targets in the treatment of type II diabetes and Alzheimer's disease. Currently this target is in pursuit for type II diabetes and a few GSK-3beta inhibitors have been now advanced to Phases I and II of clinical trials. The best validated HypoGen model consists of four pharmacophore features; 1) two hydrogen bond acceptors, 2) one hydrogen bond donor and 3) one hydrophobic. This pharmacophore model correlates well with the docking model, one hydrogen bond acceptor is necessary for the H-bond interaction with VAL135, and second hydrogen bond acceptor is important for the H-bond interactions with ARG141 and the hydrophobic feature may be required for the weak H-bond interactions with ASP133. The comparative model was developed from analogue and structure-based models like Catalyst, Glide SP & XP, Gold Fitness & ChemScore and Ligand Fit using multiple linear regression analysis. A virtual library of 10,000 molecules was generated employing fragment and knowledge-based approach and the comparative model was used to predict the activities of these molecules. The H-bond with ARG141 appears to be unique to GSK-3beta and explains the high GSK-3beta selectivity observed for 1H-Quinazolin-4-ones and Benzo[e][1,3]oxazin-4-ones. This understanding of protein-ligand interactions and molecular recognition increases the rapid development of potent and selective inhibitors, and also helps to eliminate the increase in number of false positives and negatives.