RESEARCH ARTICLE
Development and Validation of a Robust QSAR Model For Piperazine and Keto Piperazine Derivatives as Renin Inhibitors
Jimish R. Patel*, Laxman M. Prajapati
Article Information
Identifiers and Pagination:
Year: 2016Volume: 3
First Page: 1
Last Page: 24
Publisher Id: PHARMSCI-3-1
DOI: 10.2174/1874-844901603010601
Article History:
Received Date: 22/07/2015Revision Received Date: 9/02/2016
Acceptance Date: 17/02/2016
Electronic publication date: 31/03/2016
Collection year: 2016
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
Abstract
Background:
The renin is a key performer in the renin–angiotensin system, and it offers a resource for the beneficial action of hypertension and heart malfunction. The keto piperazine based renin inhibitors have shown greater potential and good biavaibility.
Objective:
To develop a highly efficient QSAR model for 80 piperazines and keto piperazines to predict renin enzyme inhibitory activity.
Methods:
The renin inhibitory activity (IC50) was considered as biological activity. Dragon software, version 5.5 was used for calculation of physicochemical parameters. Sequential MLR (multiple linear regression) is carried out to create quantitative structure–activity relationship models, which were again evaluated in support of statistical significance and analytical capacity by inner and exterior validation.
Results:
The greatest QSAR model was a correlation coefficient (R2) of 0.846, cross-validation correlation coefficient (Q2) of 0.818 and, R2 pred of 0.821. The leave one out cross validation method was used to assess the performance of the chosen model.
Conclusion:
The quantitative structure–activity relationship model suggests that the constitutional descriptors (Sv, nDB, nO) play a vital role in binding of ligands with renin enzyme. The information presented provides important structural insight in designing more potent renin enzyme inhibitors.
