A Review on Computational Methods in Developing Quantitative Structure-Activity Relationship (QSAR)

Virtual filtering and screening of combinatorial libraries have recently gained attention as methods complementing the high-throughput screening and combinatorial chemistry. These chemoinformatic techniques rely heavily on quantitative structure-activity relationship (QSAR) analysis, a field with established methodology and successful history. In this review, we discuss the computational methods for building QSAR models. The review starts with general introduction and theories of QSAR and identifying the general scheme of a QSAR model. Following, the review focus on the methodologies in constructing three main components of QSAR model, namely the methods for describing the molecular structure of compounds, for selection of informative descriptors and for activity prediction. The review present both the well established methods as well as techniques introduced into the QSAR domain.