RESEARCH ARTICLE
Ezqsar: An R Package for Developing QSAR Models Directly From Structures
Jamal Shamsara*
Article Information
Identifiers and Pagination:
Year: 2017Volume: 11
First Page: 212
Last Page: 221
Publisher ID: TOMCJ-11-212
DOI: 10.2174/1874104501711010212
Article History:
Received Date: 18/08/2017Revision 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.
Abstract
Background:
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.
Results:
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.
Conclusion:
The R package, ezqsar, is freely available viahttps://github.com/shamsaraj/ezqsar, and it runs on Linux and MS-Windows.
