On the physical interpretation of QSAR models.
Multidimensional quantitative structure-activity models (QSAR) developed using molecular structure descriptors and regression analysis techniques have found wide utility and acceptance. However, it is often difficult to extract a physical interpretation of such models because of the types of descriptors involved and the multidimensional nature of the model. The work described here illustrates a method of model interpretation that employs partial least squares (PLS) analysis. Structure-activity relationship information is derived from the positions of specific sets of structures in the PLS score plots and the weights for each variable in the PLS components. Using these data, information regarding major structure-activity trends, trend exceptions, and unique or outlying observations is easily obtained. Examples of this methodology are illustrated using QSAR equations developed for the inhibition of quinolone-resistant bacterial DNA gyrase and human topoisomerase-II inhibition by a series of quinolone antibacterial agents.
D001426:Bacterial Proteins / Q000037:antagonists & inhibitors; D024881:Drug Resistance, Bacterial; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000494:pharmacology; D006801:Humans; D020128:Inhibitory Concentration 50; D016018:Least-Squares Analysis; D008956:Models, Chemical; D008958:Models, Molecular; D021281:Quantitative Structure-Activity Relationship; D015363:Quinolones / Q000737:chemistry* / Q000494:pharmacology; D059005:Topoisomerase II Inhibitors
D001426:Bacterial Proteins; D004791:Enzyme Inhibitors; D015363:Quinolones; D059005:Topoisomerase II Inhibitors