4.25 - Chemometrics for QSAR Modeling

Chemometrics plays a fundamental role in quantitative structure-activity relationships (QSARs) and quantitative structure-property relationships (QSPRs) methods, which aim at empirically linking the molecular structure of chemicals to experimentally-measurable properties. In fact, chemometrics statistics and chemoinformatics are the basic tools for finding meaningful mathematical relationships between the molecular structure and biological, physico-chemical, toxicological and environmental properties of chemicals. The key elements of QSAR/QSPR are molecular descriptors, which are numerical indices encoding information related to the structure of chemicals and are used as independent variables in the subsequent modeling, thus connecting the QSAR approaches to the multivariate and chemometric world. In this article, historical and novel QSAR modeling approaches are presented. After describing the historical background of QSAR and the classical approaches, molecular descriptors are illustrated, with state-of-the-art as well as novel description methodologies. Additionally, the key principles of QSAR are introduced, along with specific elements of the QSAR modeling workflow, e.g., variable reduction and selection, similarity-based approaches, validation, the definition of applicability domain and consensus modeling.