QSPR study of maximum absorption wavelength of various flavones by multivariate image analysis and principal components-least squares support vector machine

Abstract

A novel quantitative structure-property relationships (QSPR) model has been developed for the maximum absorption wavelength (λmax) of 69 flavones. Modeling of λmax of these compounds as a function of the bidimensional images as descriptors was established by chemometrics methods. The resulted descriptors were subjected to principal component analysis (PCA) and the most significant principal components (PCs) were extracted. Multivariate image analysis applied to QSPR modeling was done by means of principal component-least squares support vector machine (PC-LSSVM) method. This model was applied for the prediction of the λmax of flavones, which were not in the modeling procedure with low standard errors and high correlation coefficient. The resulted model showed high prediction ability with root mean square error of prediction of 0.3815 for PC-LSSVM.