QUANTITATIVE ELECTRONIC STRUCTURE-ACTIVITY-RELATIONSHIPS OF PYRIDINIUM CEPHALOSPORINS USING NONPARAMETRIC REGRESSION METHODS

Projection pursuit regression (PPR) was applied to interpret and predi ct the antibacterial activity of pyridinium cephalosporins using semie mpirical quantum mechanical descriptors. This method can deal with res ponses due to interactions of predictors (descriptors) which cannot be completely represented by additive regression models. Based on leave- one-out cross-validation, the best PPR model gave a cross-validated r( 2) or q(2) value of 0.711, whereas the traditional method, multiple li near regression, and another additive nonparametric model, alternating conditional expectations, produced the best q(2) values: 0.233 and 0. 324 respectively. Its ability to provide models with good predictive a bility reveals that PPR is a valuable tool in quantitative structure-a ctivity relationship studies.