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Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives, a new class of alpha-glucosidase inhibitors

Authors
Bharatham, KavithaBharatham, NagakumarPark, Ki HunLee, Keun Woo
Issue Date
Jun-2008
Publisher
ELSEVIER SCIENCE INC
Keywords
alpha-glucosidase; GOLD molecular docking; MD simulation; pharmacophore model development; sulfonamide chalcone derivatives; ligplot
Citation
JOURNAL OF MOLECULAR GRAPHICS & MODELLING, v.26, no.8, pp.1202 - 1212
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Volume
26
Number
8
Start Page
1202
End Page
1212
URI
https://scholarworks.bwise.kr/gnu/handle/sw.gnu/27395
DOI
10.1016/j.jmgm.2007.11.002
ISSN
1093-3263
Abstract
Sulfonamide chalcone derivatives are a new class of non-saccharide compounds that effectively inhibit glucosidases which are the major targets in the treatment of Type 2 diabetes and HIV infection. Our aim is to explore their binding mode of interaction at the active site by comparing with the sugar derivatives and to develop a pharmacophore model which would represent the critical features responsible for a-glucosidase inhibitory activity. The homology modeled structure of Saccharomyces cerevisiae alpha-glucosidase was built and used for molecular docking of non-sugar/sugar derivatives. The validated docking results projected the crucial role of NH group in the binding of sugar/non-sugar derivatives to the active site. Ligplot analyses revealed that Tyr71, and Phe177 form hydrophobic interactions with sugar/non-sugar derivatives by holding the terminal glycosidic ring mimics. Molecular dynamic (MD) simulation studies were performed for protein alone and with chalcone derivative to prove its binding mechanism as shown by docking/Ligplot results. It would also help to substantiate the homology modeled structure stability. With the knowledge of the crucial interactions between ligand and protein from docking and MD simulation studies, features for pharmacophore model development were chosen. The CATALYST/HipHop was used to generate a five featured pharmacophore model with a training set of five non-sugar derivatives. As validation. all the crucial features of the model were perfectly mapped onto the 3D structures of the sugar derivatives as well as the newly tested non-sugar derivatives. Thus, it can be useful in virtual screening for finding new non-sugar derivatives as a-glucosidase inhibitors. (C) 2007 Elsevier Inc. All rights reserved.
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