Quantitative structure-property relationship study of inhibitory of dihydropyridine by quantum chemical descriptors and ODC-PLS

A quantitative structure–property relationship (QSPR) study is suggested for the prediction of toxicity (IGC50) of dihydropyridine (DHP). Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc .One of the challenges in the field of quantitative structure-activity relationship (QSAR) analysis is the correct classification of a chemical compound to an appropriate model for the prediction of activity. Orthogonal descriptor correction (ODC) methods have been proposed as a way of preprocessing data prior to performing partial least squares (PLS) regression [1]. The purpose is generally not to improve the prediction but to remove variation in X that is uncorrelated with Y in order to simplify both the structure and interpretation of the resulting PLS regression model. The useful information regarding the structure– activity relationship analysis should be retained. The generalized cross-validation method was employed to select the ridge parameter and the number of ODC components. The proposed methodology has been tested in PLS modeling for QSAR studies of dihydropyridine (DHP) inhibitors. A comparison in the modeling power of PLS is made between non-processed data set, It has been demonstrated that data preprocessing using ridge estimated ODC could improve PLS regression models by reducing both model complexity and prediction errors. The analysis of the dihydropyridine (DHP) inhibitor data provides some insight in the effect of molecular structure on the activity of anti-inflammatory agents.