Modelling and targeting mitochondrial protein tyrosine phosphatase 1: a computational approach.

Autor: Ragunathan, Venkataraghavan, Chithra, K., Shivanika, C., Sudharsan, Meenambiga Setti
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Zdroj: In Silico Pharmacology; 1/17/2022, Vol. 10 Issue 1, p1-30, 30p
Abstrakt: The present research scintillates on the homology modelling of rat mitochondrial protein tyrosine phosphatase 1 (PTPMT1) and targeting its activity using flavonoids through a computational docking approach. PTPMT1 is a dual-specificity phosphatase responsible for protein phosphorylation and plays a vital role in the metabolism of cardiolipin biosynthesis, insulin regulation, etc. The inhibition of PTPMT1 has also shown enhanced insulin levels. The three-dimensional structure of the protein is not yet known. The homology modelling was performed using SWISS-MODEL and Geno3D webservers to compare the efficiencies. The PROCHECK for protein modelled using SWISS-MODEL showed 91.6% of amino acids in the most favoured region, 0.7% residues in the disallowed region that was found to be significant compared to the model built using Geno3D. 210 common flavonoids were docked in the modelled protein using the AutoDock 4.2.6 along with a control drug alexidine dihydrochloride. Our results show promising candidates that bind protein tyrosine phosphatase 1, including, prunin (− 8.66 kcal/mol); oroxindin (− 8.56 kcal/mol); luteolin 7-rutinoside (− 8.47 kcal/mol); 3(2H)-isoflavenes (− 8.36 kcal/mol); nicotiflorin (− 8.29 kcal/mol), ranked top in the docking experiments. We predicted the pharmacokinetic and Lipinski properties of the top ten compounds with the lowest binding energies. To further validate the stability of the modelled protein and docked complexes molecular dynamics simulations were performed using Desmond, Schrodinger for 150 ns in conjunction with MM-GBSA. Thus, flavonoids could act as potential inhibitors of PTPMT1, and further, in-vitro and in-vivo studies are essential to complete the drug development process. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index