Discovery of GSK3β Inhibitors through In Silico Prediction-and-Experiment Cycling Strategy, and Biological Evaluation

Abstract

Direct inhibitors of glycogen synthase kinase 3β (GSK3β) have been investigated and reported for the past 20 years. In the search for novel scaffold inhibitors, 3000 compounds were selected through structure-based virtual screening (SBVS), and then high-throughput enzyme screening was performed. Among the active hit compounds, pyrazolo [1,5-a]pyrimidin-7-amine derivatives showed strong inhibitory potencies on the GSK3β enzyme and markedly activated Wnt signaling. The result of the molecular dynamics (MD) simulation, enhanced by the upper-wall restraint, was used as an advanced structural query for the SBVS. In this study, strong inhibitors designed to inhibit the GSK3β enzyme were discovered through SBVS. Our study provides structural insights into the binding mode of the inhibitors for further lead optimization.

Poly(N-acryloylglycine-acrylamide) Hydrogel Mimics the Cellular Microenvironment and Promotes Neurite Growth with Protection from Oxidative Stress

“…As per our obtained results, the reference molecule TMU formed six hydrogen bonds. The selective inhibitor SB415286 interacted by forming five hydrogen bonds at one conformation, while in another conformation it formed three hydrogen bonds and potent inhibitor SB216763 formed two hydrogen bonds at the ATP pocket with almost similar binding energies from −6.9 to 8 kcal mol –1 at inhibitor constants of K i = 7.48 to 1.37 μM along with hydrophobic interacting residues, as provided in Table S1 and Figure . Furthermore, we observed that NAG (G) and its polymeric units (dimer and trimer) established the protein–ligand interactions with ATP pockets of GSK3β with a higher binding energy at nanomolar (nM) concentrations compared to the available inhibitors at micromolar (μM) concentrations.…”

Discovery of GABA Aminotransferase Inhibitors via Molecular Docking, Molecular Dynamic Simulation, and Biological Evaluation

“…The Search 3D Database protocol in Discovery Studio was utilized to create a pharmacophore model of the vigabatrin and GABA-AT complex, and the generated pharmacophore model hit compounds from a large database were filtered, such as the 530,000 compounds in the Korea Chemical Bank (KCB). The KCB database is an indexed multi-conformer database constructed using the Build 3D Database protocol in Discover Studio [34]. The screened 50 compounds were further analyzed by preliminary biological studies.…”

Discovery of Potential GSK-3β Allosteric Modulators for Alzheimer’s Disease

“…In another study using machine learning, ruboxistaurin was identified as a GSK-3β inhibitor with IC50 = 97.3 nM [4]. Pyrazolo [1,5-a]pyrimidin-7-amine derivatives were identified using pharmacophore models, docking, and molecular dynamics from ~ 530k compound's database [18]. Nevertheless, none of these studies identified novel scaffolds nor targeted allosteric binding sitesother than the orthosteric/active one.…”