Chapter 2 - QSAR: Descriptor calculations, model generation, validation and their application

Abstract

QSAR (Quantitative Structure Activity Relationships) modeling has been an old age technique for the development of relationships between physicochemical properties of the chemical substances and their biological activities to obtain a reliable mathematical and statistical model for the prediction of the activities of new chemical entities. The fundamental principle underlying the QSAR is that the variation in structural properties is responsible for the variations in biological activities of the congeneric molecules. In the classical QSAR studies, dependent variables including affinities of the ligands to their binding sites, inhibition constants, rate constants, and other biological end points have been correlated with atomic, group or molecular properties such as lipophilicity, polarizability, electronic and steric properties (Hansch analysis) or with certain structural features (Free-Wilson analysis). QSAR certainly decreases the number of compounds to be synthesized by facilitating the selection of the most promising candidates. This chapter provides an overview of the different QSAR approaches employed within the current drug discovery process to construct predictive structure–activity relationships and also discusses the limitations that are fundamental to these approaches.