Quantitative structure-activity relationships (QSARs) of N-terminus fragments of NK1 tachykinin antagonists: a comparison of classical QSARs and three-dimensional QSARs from similarity matrices.

Abstract

The ability of three-dimensional quantitative structure-activity relationships (QSARs) derived from classical QSAR descriptors and similarity indices to rationalize the activity of 28 N-terminus fragments of tachykinin NK1 receptor antagonists was examined. Two different types of analyses, partial least squares and multiple regression, were performed in order to check the robustness of each derived model. The models derived using classical QSAR descriptors lacked accurate quantitative and predictive abilities to describe the nature of the receptor-inhibitor interaction. However models derived using 3D QSAR descriptors based on similarity indices were both robust and significantly predictive. The best model was obtained through the statistical analysis of molecular field similarity indices (n = 28, r2 = 0.846, r(cv)2 = 0.737, s = 0.987, PRESS = 7.102) suggesting that electronic and size-related properties are the most relevant in explaining the affinity data of the training set. The overall quality and predictive ability of the models applied to the test set appear to be very high, since the predicted affinities of three test compounds agree with the experimentally determined affinities obtained subsequently within the experimental error of the binding data.