Issue 59, 2020, Issue in Progress

Investigation of angiotensin-I-converting enzyme (ACE) inhibitory tri-peptides: a combination of 3D-QSAR and molecular docking simulations

Abstract

Angiotensin-I-converting enzyme (ACE) is a key enzyme in the regulation of peripheral blood pressure and electrolyte homeostasis. Therefore, ACE is considered as a promising target for treatment of hypertension. In the present work, in order to investigate the binding interactions between ACE and tri-peptides, three-dimensional quantitative structure–activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were developed. Three different alignment methods (template ligand-based, docking-based, and common scaffold-based) were employed to construct reliable 3D-QSAR models. Statistical parameters derived from the QSAR models indicated that the template ligand-based CoMFA (Rcv2 = 0.761, Rpred2 = 0.6257) and CoMSIA (Rcv2 = 0.757, Rpred2 = 0.6969) models were better than the other alignment-based models. In addition, molecular docking studies were carried out to predict the binding modes of the peptides to ACE. The peptide–enzyme interactions were consistent with the derived 3D contour maps. Overall, the insights gained from this study would offer theoretical references for understanding the mechanism of action of tri-peptides when binding to ACE and aid in the design of more potent tri-peptides.

Graphical abstract: Investigation of angiotensin-I-converting enzyme (ACE) inhibitory tri-peptides: a combination of 3D-QSAR and molecular docking simulations

Supplementary files

Article information

Article type
Paper
Submitted
10 Jun 2020
Accepted
24 Sep 2020
First published
30 Sep 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 35811-35819

Investigation of angiotensin-I-converting enzyme (ACE) inhibitory tri-peptides: a combination of 3D-QSAR and molecular docking simulations

F. Wang and B. Zhou, RSC Adv., 2020, 10, 35811 DOI: 10.1039/D0RA05119E

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