Principal Properties for Aromatic Substituents. A Multivariate Approach for Design in QSAR

A set of a hundred aromatic substituents were multivariately characterized by nine descriptor variables taken from the literature. From the 9*100 data set were calculated four principal properties for the aromatic substituents as the four first dimensions in a principal components analysis, PCA. The first three principal properties were used to develop a strategy for selecting substituents from eight subgroups according to a factorial design.