Using Voronoi Grid and SVM Linear Regression in Drug Discovery

In this paper we propose a new method for generating an informative QSAR model (called VSVR-QSAR) using Voronoi grid and support vector machines regression. The procedure enables researchers to understand the physicochemical meaning of the steric and electrostatics measurements and the inclusion of those measurements as latent variables in the generated QSAR model. The procedure proved to be comparable or better than the classical QSAR, as well as conventional 3D-QSAR procedures