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 via https://github.com/shamsaraj/ezqsar, and it runs on Linux and MS-Windows.
Highlights
Quantitative Structure Activity Relationship (QSAR) is a difficult computational chemistry approach for beginner scientists and a time consuming one for even more experienced researchers
Some of the features are similar between those packages. They are intended to be used mostly by beginners. They provide a single function that can do the entire job starting with a data set and ends with a complete QSAR model that includes descriptor generation, data processing, modeling, internal and external validity assessment, presentation of a QSAR model with the ability to predict the activities of new structures
It wrapped up QSAR tools in several functions and user can tune several parameters for each one, but ezqsar could be used by advanced users to provide an easy and precise look on the modelability of a data set and prediction of the activity of a test set with estimation of applicability domain
Summary
Quantitative Structure Activity Relationship (QSAR) is a difficult computational chemistry approach for beginner scientists and a time consuming one for even more experienced researchers. Quantitative Structure Activity Relationship (QSAR) is an old but still applicable method for the various branches of chemistry. It attempts to find a model that can predict the biological activity of chemical compounds using their structural features [1]. There are several modules available in commercial tools [2] (SYBYL, MOE and Schrodinger suite) that make QSAR studies simpler than ever
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