Identification of the potential dual inhibitor of protein tyrosine phosphatase sigma and leukocyte common antigen-related phosphatase by virtual screen, molecular dynamic simulations and post-analysis

Abstract

Owing to their inhibitory role in regulating oligodendrocyte differentiation and apoptosis, protein tyrosine phosphatase sigma (PTPσ) and leukocyte common antigen-related phosphatase (LAR) play a crucial potential role in treating spinal cord injury (SCI) disease. In this research, the computer aided drug design (CADD) methods were applied to discover the potential dual-target drug involving virtual screen, molecular docking and molecular dynamic simulation. Initially, the top 20 compounds with higher docking score than the positive controls (ZINC13749892, ZINC14516161) were virtually screened out from NCI and ZINC databases, and then were submitted in ADMET to predict their drug properties. Among these potential compounds, ZINC72417086 showed a higher docking score and satisfied Lipinski’s rule of five. In addition, the post-analysis demonstrated that when ZINC72417086 bound to PTPσ and LAR, it could stable proteins conformations and destroy the residues interactions between P-loop and other loop regions in active pocket. Meanwhile, residue ARG1595 and ARG1528 could play a crucial role in in the inhibition of PTPσ and LAR, respectively. This research offered a novel approach for rapid discovery of dual-target leads compounds to treat SCI.

Communicated by Ramaswamy H. Sarma

Keywords:

• PTPσ
• LAR
• SCI
• CADD
• Virtual screening
• ADMET
• MD simulations

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

National Natural Science Foundation of China [grant number 81773569], Natural Science Foundation of Tianjin [grant number: 18JCQNJC13700], Cooperation and Exchange Project of the National Natural Science Foundation of China [grant number 81611130090], and Science & Technology Development Fund of Tianjin Education Commission for Higher Education [grant number 2017KJ229].