Title: A novel approach for identification of possible GSK-3β inhibitors using computational virtual screening analysis of drugs

Authors: Kakarla Naga Madhavi Latha; G. Rama Mohan Babu

Addresses: Department of Computer Science and Engineering, University College of Engineering and Technology, Acharya Nagarjuna University, Nagarjuna Nagar, Guntur – 522510, Andhra Pradesh, India ' Department of Information Technology, R.V.R. & J.C College of Engineering, Chowdavaram, Guntur – 522019, Andhra Pradesh, India

Abstract: GSK-3 has a prominent role in glucose uptake and was investigated using more specific, ATP-competitive GSK-3 inhibitors. This multifunctional kinase apart from the ability to phosphorylate glycogen synthase and regulate glucose metabolism was subsequently found to be a critical component in numerous cellular functions including regulation of different cell signalling, cell division, differentiation, proliferation and growth as well as apoptosis. In this work, we report molecular docking analysis of 2035 approved drugs from DrugBank database based on their potential to bind against type-2 diabetes protein target, GSK-3β. Molecular docking analysis revealed several new classes of drugs reported to exhibit inhibitory properties against GSK-3β. Out of 13 best drugs resulted from the analysis, top three (Venetoclax, Cobicistat and Atorvastatin) were selected based on consensus scoring using six scoring schemes such as MolDock score of Molegro, mcule, Pose&Rank, MTiAutoDock, DockThor and DSX respectively.

Keywords: virtual screening; molecular docking; DrugBank; type-2 diabetes; GSK-3β.

DOI: 10.1504/IJCBDD.2019.103596

International Journal of Computational Biology and Drug Design, 2019 Vol.12 No.4, pp.312 - 331

Received: 11 Jul 2018
Accepted: 25 Sep 2018

Published online: 13 Nov 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article