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Computational and Mathematical Methods in Medicine
Volume 2017 (2017), Article ID 4245613, 13 pages
https://doi.org/10.1155/2017/4245613
Research Article

Computational Insight into Protein Tyrosine Phosphatase 1B Inhibition: A Case Study of the Combined Ligand- and Structure-Based Approach

1Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, China
2Faculty of Pharmaceutical Sciences, Toho University, Miyama 2-2-1, Funabashi, Chiba 274-8510, Japan

Correspondence should be addressed to Jian Wang; moc.liame@gnawnaij and Maosheng Cheng; ten.362@gnehcsm

Received 23 August 2017; Accepted 26 September 2017; Published 26 December 2017

Academic Editor: Tingjun Hou

Copyright © 2017 Xiangyu Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Protein tyrosine phosphatase 1B (PTP1B) is an attractive target for treating cancer, obesity, and type 2 diabetes. In our work, the way of combined ligand- and structure-based approach was applied to analyze the characteristics of PTP1B enzyme and its interaction with competitive inhibitors. Firstly, the pharmacophore model of PTP1B inhibitors was built based on the common feature of sixteen compounds. It was found that the pharmacophore model consisted of five chemical features: one aromatic ring (R) region, two hydrophobic (H) groups, and two hydrogen bond acceptors (A). To further elucidate the binding modes of these inhibitors with PTP1B active sites, four docking programs (AutoDock 4.0, AutoDock Vina 1.0, standard precision (SP) Glide 9.7, and extra precision (XP) Glide 9.7) were used. The characteristics of the active sites were then described by the conformations of the docking results. In conclusion, a combination of various pharmacophore features and the integration information of structure activity relationship (SAR) can be used to design novel potent PTP1B inhibitors.