Adaptive least-squares method applied to structure-activity correlation of hypotensive N-alkyl-N''-cyano-N'-pyridylguanidines

Abstract
A method using an adaptive least-squares (ALS) technique was developed for the discrimination of ordered categorical data. The method (ALS method) has the advantages of simultaneously considering any number of classes and of producing a single discriminant function which can place patterns in several classes. The ALS method was compared with linear discriminant analysis (LDA) in application to the problem of discriminating 3-class hypotensive therapeutic indices of 76 N-alkyl-N"-cyano-N''-pyridylguanidines using 9 descriptor variables. With the full data set and in the 5 leave-out runs, the ALS method was superior and more stable in recognition and prediction. The structure-activity relationship is discussed on the basis of discriminant functions formulated.