Quantitative structure-activity relationships (QSAR) are one of the most important methodologies for rational drug design. In QSAR, compounds are represented by chemical structure descriptors, and then statistical models are built to predict biological activities of candidate structures. In this paper, two principal topics in QSAR, variable selection and 3D-QSAR, are picked up and are reviewed in recent trend. The aim of variable selection is to construct a significant QSAR model by selecting important descriptors among from descriptor pool. Until now, many variable selection methods have been developed and proposed. On the other hand, molecular alignment is important factor of 3D-QSAR analysis because appropriate alignment is usually required to construct proper 3D-QSAR models. In addition, we review new QSAR methods using molecular surface properties, alignment independent QSAR methods, and 4D-QSAR methods.
Keywords: QSAR, variable selection, 3D-QSAR, molecular alignment, genetic algorithm, genetic programming
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