Developing a virtual random screening method for cancer drug discovery

2014 Fiscal Year Final Research Report

• Project/Area Number: 24500364
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Bioinformatics/Life informatics
• Research Institution: Tokyo University of Science
• Principal Investigator: OHWADA Hayato 東京理科大学, 理工学部, 教授 (30203954)
• Co-Investigator(Kenkyū-buntansha): AOKI Shin 東京理科大学, 薬学部, 教授 (00222472)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 機械学習 / 創薬

Outline of Final Research Achievements

This study presents a high performance virtual screening method for drug design based on machine learning. In drug discovery with computers, drug designer often use docking software and decide the docking between the compound and the protein with the result of docking software, structure of the compound, and any information of compound. Currently, the performance of docking software is not high. The present method exploits the experiential knowledge of pharmaceutical researchers and allows to screen compounds with high performance based on the result of the docking software and chemical information of compounds. The experiment shows our method have high-accuracy as 98.4 % and excellent ROC curve.

Free Research Field

知能情報学