THE REVIEW OF VIRTUAL SCREENING TECHNIQUES

Abstract

Effective treatments extend lives in the world, and significant efforts are in place to expand the use of life-saving medications in the developing world. This paper gives an overview of drug discovery process and emphasises in the area of virtual screening. Because machine learning is fast becoming a popular mechanism to support activity recognition in drug discovery process and other real-world applications, hence, this review emphasises on machine learning methods used in virtual screening. This includes linear and kernel discriminant analysis, neural network, decision tree, graph kernel machines, and support vector machine.