Development of NMR drug discovery pipeline using database

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K06970
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Structural biochemistry
• Research Institution: Osaka University
• Principal Investigator: Kobayashi Naohiro 大阪大学, たんぱく質研究所, 特任准教授(常勤) (80272160)
• Co-Investigator(Kenkyū-buntansha): 児嶋 長次郎 横浜国立大学, 大学院工学研究院, 教授 (50333563)
• Co-Investigator(Renkei-kenkyūsha): HIROAKI Hidekazu 名古屋大学, 創薬科学研究科, 教授 (10336589) ; MOTONO Chie 産業技術総合研究所, 創薬分子プロファイリング研究センター, 主任研究員 (80415752)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 核磁気共鳴法 / データベース / 自動解析

Outline of Final Research Achievements

The three-dimensional structure encoded in the genome sequence experimentally determined is about 10% of the total, and recently there are tendencies for cases of drug discovery research using a structure prediction model. In this research project, we have constructed a drug discovery support database that links a model structure database that can be a target of nuclear magnetic resonance (NMR) research, which is lined to several external life science databases such as BMRB, a database of NMR experiment data. In the period from FY2016 to FY2017, utilizing a database, we designed an automatic analysis pipeline based on deep learning, and determined the NMR signal assignments and the solution tertiary structure required for drug discovery research using about 25% of NMR data sets. The new technology has sucessfully shortened automatic NMR analysis to about half a day.

Free Research Field

核磁気共鳴分光学