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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.

Authors
  • Du, Shan1
  • Yang, Bing2
  • Wang, Xin3
  • Li, Wei-Ya1
  • Lu, Xin-Hua4
  • Zheng, Zhi-Hui4
  • Ma, Ying1
  • Wang, Run-Ling1
  • 1 Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, China. , (China)
  • 2 Department of Cell Biology, School of Basic Medical Science, Tianjin Medical University, Tianjin, China. , (China)
  • 3 Tasly Pharmaceutical Group Co., Ltd, Tianjin, China. , (China)
  • 4 Key Laboratory for New Drug Screening Technology of Shijiazhuang City, New Drug Research & Development Center of North China Pharmaceutical Group Corporation, National Microbial Medicine Engineering & Research Center, Hebei Industry Microbial Metabolic Engineering & Technology Research Center, Shijiazhuang, Hebei, China. , (China)
Type
Published Article
Journal
Journal of biomolecular structure & dynamics
Publication Date
Sep 01, 2020
Volume
38
Issue
14
Pages
4232–4245
Identifiers
DOI: 10.1080/07391102.2019.1676825
PMID: 31588870
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

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.

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