Combining DFT and QSAR result for predicting the biological activity of the phenylsuccinimide derivatives


ABSTRACT:

Study 3D-QSAR is applied to a set of 57 molecules based on N-phenylsuccinimides using the principal component analysis (PCA) method, the multiple linear regression method (MLR) and the artificial neural network (ANN). The predicted values of activities are in good agreement with the experimental results. The artificial neural network (ANN) techniques, considering the relevant descriptors obtained from the MLR, showed a correlation coefficient of 0,9 with an 8-20-1 ANN model which is a good result. As a result of quantitative structure-activity relationships, we found that the model proposed in this study is constituted of major descriptors used to describe these molecules. The obtained results suggested that proposed combination of several calculated parameters could be useful in predicting biological activity of N-phenylsuccinimides derivatives.

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For more details PDF Link: http://www.jocpr.com/articles/combining-dft-and-qsar-result-for-predicting-the-biological-activity-of-the-phenylsuccinimide-derivatives.pdf

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