Ezqsar: An R Package for Developing QSAR Models Directly From Structures
Identifiers and Pagination:Year: 2017
First Page: 212
Last Page: 221
Publisher ID: TOMCJ-11-212
Article History:Received Date: 18/08/2017
Revision Received Date: 01/11/2017
Acceptance Date: 12/11/2017
Electronic publication date: 30/11/2017
Collection year: 2017
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4. 0 International Public License (CC-BY 4. 0), a copy of which is available at: https://creativecommons. org/licenses/by/4. 0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Quantitative Structure Activity Relationship (QSAR) is a difficult computational chemistry approach for beginner scientists and a time consuming one for even more experienced researchers.
Method and Materials:
Ezqsar which is introduced here addresses both the issues. It considers important steps to have a reliable QSAR model. Besides calculation of descriptors using CDK library, highly correlated descriptors are removed, a provided data set is divided to train and test sets, descriptors are selected by a statistical method, statistical parameter for the model are presented and applicability domain is investigated.
Finally, the model can be applied to predict the activities for an extra set of molecules for a purpose of either lead optimization or virtual screening. The performance is demonstrated by an example.
The R package, ezqsar, is freely available viahttps://github.com/shamsaraj/ezqsar, and it runs on Linux and MS-Windows.