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Mini-Reviews in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1389-5575
ISSN (Online): 1875-5607

Computation as a Tool for Glycogen Phosphorylase Inhibitor Design

Author(s): Joseph M. Hayes and Demetres D. Leonidas

Volume 10, Issue 12, 2010

Page: [1156 - 1174] Pages: 19

DOI: 10.2174/1389557511009011156

Price: $65

Abstract

Glycogen phosphorylase is an important therapeutic target for the potential treatment of type 2 diabetes. The importance of computation in the search for potent, selective and drug-like glycogen phosphorylase inhibitors which may eventually lead to antihyperglycemic drugs is now firmly established. Acting solo or more effectively in combination with experiment in a multidisciplinary approach to structure based drug design, current day modeling methods are an effective means of reducing the time and money spent on costly experimental procedures. Glycogen phosphorylase is an allosteric protein with five different ligand binding sites, hence offering multiple opportunities for modulation of enzyme activity. However, the binding sites have their own individual characteristics, so that different modeling approaches may be more effective for each. This review is focused on advances in the modeling and design of new inhibitors of the enzyme aimed towards providing the reader with some useful hints towards more successful computer-aided inhibitor (drug) design targeting glycogen phosphorylase.

Keywords: Docking, free energy perturbation (FEP), glycogen phosphorylase, modeling, MM-GBSA, pharmacophore, QM/MM, QSAR, Glycogen Phosphorylase Inhibitor Design, type 2 diabetes, antihyperglycemic drugs, losteric protein, computer-aided inhibitor, insulin resis-tance, hypoglyce-mia, Glycogenolysis, hepatic glucose production, glucose-1-phosphate, GP-inhibitor, struc-ture-based drug design, GP BINDING SITES, Catalytic Site, pyri-doxal-5'-phosphate (PLP), D-glucose, His377, N-Acetyl-D-glucopyranosylamine, Asp283 sidechain carboxylate, UDP-glucose, 2-deoxy-glucose-6-P, glycerophosphate, allosteric inhibi-tors, GlaxoSmithKline series of anthranilimide, Allosteric activators, Monod-Wyman-Changeux model, arginine residues, W1807, naph-thalene group, caffeine, RMGPb inhibition, Phe285, Tyr613, Purines, (flavin mono-nucleotide), (flavin-adenine dinucleotide), CP320626, Glycogen Storage Site, cyclodextrins, cyclooligosaccharides, -1,4-linked 6, 7, or 8 D-glucopyranosyl units, triterpene class of GPIs, oleanic acid GPIs, benzoyl-urea derivative, HLGPa polypeptide chain, PDB complex, quantum-mechanics polarised ligand docking, electrostatic poten-tials, single point energy, (3D-)pharmacophore, Desmond program, tautomeric forms of the ligands, local similarity index, multiple protein structure, NHCON-HCO moieties, HypoGen module, 3D pharmacophore model, benzamide derivatives, glucose-sensitive insulin release, adequate absorption, distribution, metabolism, QikProp, Lipinski's rule of five, thiazolidine-2,4-diones, matched molecular pair analysis


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