Computer aided drug design: Drug target directed in silico approaches

Abstract

In modern drug discovery practices, drug leads are screened / designed against a pre-selected drug target. As a prerequisite step, target identification becomes increasingly important and receives more and more attentions from researchers. This work begins with the development of the Therapeutic Target Database (TTD), which provides a comprehensive information source of known therapeutic targets and serves as a basis for the development of other in silico tools. With this database, statistical learning approaches are explored in genome scale drug target discovery and virtual screening technologies are investigated in the rapid analysis of the mechanisms of action of active ingredients from medicinal plants. Our experiments showed that the support vector machine algorithm, a novel statistical learning approach, may be useful in the prediction of drug-target like proteins in human genome and an extended docking algorithm, INVDOCK, may facilitate the rapid analysis of the therapeutic mechanisms of effective herbal medicines.