E-pharmacophore-based virtual screening to identify GSK-3β inhibitors

Abstract

Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer's disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50 ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.

Energy-Optimized Pharmacophore Coupled Virtual Screening in the Discovery of Quorum Sensing Inhibitors of LasR Protein of <em>Pseudomonas aeruginosa</em>

“…Protein structure obtained from the PDB was not suitable in its native state for molecular docking [14] . Therefore, the protein structure was optimized with Schrödinger's Protein Preparation Wizard for proper bond orders, the addition of hydrogen atoms and missing residues, correction of formal charges to the hetero groups, and generation of tautomer/ionization states at physiologic pH (7.0) [34] . The water molecules present in most crystal protein structure [35] .…”

“…The 'pose-viewer' files of these three docked complexes were then used for e-pharmacophore modeling with Phase module [51] where a default set of six chemical features: hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic (H), negative ionizable (N), positive ionizable (P), and aromatic ring (R) were employed [48] . For precise matching, pharmacophoric sites with fitness score lower than -0.5 were rejected [34,52] . In this study, the generated three different e-pharmacophores were merged together to generate a common epharmacophore model.…”

“…The common e-pharmacophore model was then screened against the internal library. The incurred results were then assessed with EF, ROC value, BEDROC (α=20) metrics, RIE, and GH score which are often used to standardize the VS protocol [34,59] . The following equations were used to calculate the EF and GH score:…”

“…E-pharmacophores are generated by optimized energies from interactions mapped onto the atom center [34] . The generation of multiple hypotheses is required to identify the best pharmacophore model that is able to render a potential outcome [78] .…”

Classifying druggability on potential binding sites of glycogen synthase kinase-3?: an in-silico assessment

“…Structurally, GSK-3 is a two-domain kinase fold comprising a β-strand domain and an α-helix domain. The residues forming the ATP-binding site (pocket 1) are seated deep between the interface of the α-helix and β-strand domains surrounded by a hinge region and a glycine-rich loop, which is often referred to as "P-loop" [22][23][24][25] . The substrate binding site (pocket 2) is surrounded by the C-loop and the activation loop.…”