Computational study of therapeutic targets and ADME-Associated proteins and application in drug design

Abstract

With the exponential growth of genomic data and the rapid development of numerous computational approaches, continuous effort and increasing interest have been directed at drug discovery. The main purpose of my study is computational study of therapeutic targets and ADME-associated proteins on the basis of knowledge providing by three bioinformatics databases (Therapeutic Target Database, Therapeutically Relevant Multiple Pathways database, and ADME-Associated Proteins database), which are developed or updated in this work. After database construction, we do knowledge discovery in drug target search analysis, drug pharmacokinetics and pharmacogenomics studies. Firstly, we study the progress of target exploration by analyzing currently explored targets and generate several useful clues for facilitating new targets searching. Moreover, an Artificial Intelligent (e.g. Support Vector Machines) system is successfully trained to predict potential druggable proteins. Also, we study the feasibility of computational predicting individual variations of drug responses from the polymorphisms of ADME-associated proteins.