Multivariate design and modeling in QSAR

Quantitative structure-activity relationship (QSAR) modeling provides a rational basis for understanding mechanisms of biological performance and how to alter chemical structures to achieve improved performance. However, in the quest for a valid QSAR model, several critical problems must be dealt with in an appropriate manner. Chemometric techniques are relevant in QSAR development and will help the inexperienced QSAR analyst in avoiding trivial mistakes. The chemometric QSAR strategy, applicable both in drug design and environmentally related sciences, highlights some crucial steps that otherwise often are neglected. These steps include how to select the proper data analytical method, how to design the training set, how to describe chemical and biological properties of compounds and analyze these data, and finally how to validate the relevance of an established QSAR model. A discussion of these steps is given, using four illustrative examples.