Pharmacophore modelling, docking and molecular dynamic simulation studies in the discovery of potential human renin inhibitors
- PMID: 35932508
- DOI: 10.1016/j.jmgm.2022.108272
Pharmacophore modelling, docking and molecular dynamic simulation studies in the discovery of potential human renin inhibitors
Abstract
Hypertension is the main cause of human death and the Renin- Angiotensin- Aldosterone System (RAAS) has a key role in the control of human blood pressure. In this research a multi-step virtual screening strategy was applied in order to find new potential renin inhibitors. The crystal structure of renin-aliskiren complex was explored and receptor-ligand pharmacophore model was developed and validated using pharmit. ZINC database was screened by pharmacophore model and Lipinski's rule of five. Thereafter, the retrieved hits were docked in the active site of renin by using Vina. ADME parameters and toxicity of the filtered compounds were approximated using in silico methods and the selected compounds were subjected to high performance docking in order to improve the accuracy of screening. The non-bond interactions of the hit molecules with renin were explored and the compounds with the highest affinity and appropriate interactions were selected. In the last step, molecular dynamic simulation studies were performed on the complex of renin with aliskiren and three top-ranked structures including ZINC6085004, ZINC426421106, and ZINC5481346. RMSD, RMSF, Rg and number of hydrogen bonds were calculated. The binding free energy was calculated using the MM/PBSA method. The result of MD simulation indicated the stable binding of ZINC426421106 and ZINC5481346 with the active site of renin. According to this in-silico study these two compounds are drug-like, nontoxic, and have a high potential for inhibiting renin and could serve as appropriate lead molecules for the development of renin inhibitors as antihypertensive agents.
Keywords: Docking; Inhibitor; Molecular dynamic simulation; Pharmacophore modelling; Renin.
Copyright © 2022. Published by Elsevier Inc.
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