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Identification of potential leukocyte antigen-related protein (PTP-LAR) inhibitors through 3D QSAR pharmacophore-based virtual screening and molecular dynamics simulation

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Version 2 2019-10-17, 11:36
Version 1 2019-10-07, 06:25
journal contribution
posted on 2019-10-17, 11:36 authored by Shan Du, Bing Yang, Xin Wang, Wei-Ya Li, Xin-Hua Lu, Zhi-Hui Zheng, Ying Ma, Run-Ling Wang

Owing to its negative regulatory role in insulin signaling, protein tyrosine phosphatase of leukocyte antigen-related protein (PTP-LAR) was widely thought as a potential drug target for diabetes. Now, it was urgent to search for potential LAR inhibitors targeting diabetes. Initially, the pharmacophore models of LAR inhibitors were established with the application of the HypoGen module. The cost analysis, test set validation, as well as Fischer’s test was used to verify the efficiency of pharmacophore model. Then, the best pharmacophore model (Hypo-1-LAR) was applied for the virtual screening of the ZINC database. And 30 compounds met the Lipinski’s rule of five. Among them, 10 compounds with better binding affinity than the known LAR inhibitor (BDBM50296375) were discovered by docking studies. Finally, molecular dynamics simulations and post-analysis experiments (RMSD, RMSF, PCA, DCCM and RIN) were conducted to explore the effect of ligands (ZINC97018474 and Compound 1) on LAR and preliminary understand why ZINC97018474 had better inhibitory activity than Compound 1 (BDBM50296375).

Communicated by Ramaswamy H. Sarma

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 81773569), the Natural Science Foundation of Tianjin (Grant No. 18JCQNJC13700), the Cooperation and Exchange Project of the National Natural Science Foundation of China (Grant No. 81611130090), the Science & Technology Development Fund of Tianjin Education Commission for Higher Education (Grant No. 2017KJ229).

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