Article ID Journal Published Year Pages File Type
7563175 Chemometrics and Intelligent Laboratory Systems 2015 7 Pages PDF
Abstract
Chalcones and their derivatives possess a wide range of significant pharmacological activities; among the most important ones is their anticancer activity. For this reason we performed a Quantitative Structure-Activity Relationships (QSAR) study of their anticancer activity against MCF-7 human breast cancer cell lines. In this work, several descriptor options were tested on the dataset containing 93 molecular structures, using ERM (Enhanced Replacement Method). The best models were found using merely two dimensional descriptors. The two dimensional descriptor pool was further expanded using several nonlinear transformations, which resulted in an optimal five molecular descriptor model that showed very good predictive ability. Thus, ERM was capable of finding a simple to interpret and understand model that nonetheless addresses nonlinearities between the descriptors and the activity. Furthermore, the acquired model is very straightforward to use since it does not require the optimization of chemical structures for the calculation of three dimensional descriptors.
Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
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