Attempts in unifying biological molecular data via graph methods

2015 Fiscal Year Final Research Report

• Project/Area Number: 25280109
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Life / Health / Medical informatics
• Research Institution: Nagahama Institute of Bio-Science and Technology
• Principal Investigator: Shirai Tsuyoshi 長浜バイオ大学, バイオサイエンス学部, 教授 (00262890)
• Co-Investigator(Kenkyū-buntansha): OOYAMA TAKUJI 山梨大学, 医学工学総合研究部, 准教授 (60423133) ; MAYANAGI KOUTA 九州大学, 生体防御医学研究所, 助教 (50418571)
• Co-Investigator(Renkei-kenkyūsha): ISHINO YOSHIZUMI 九州大学, 農学研究科, 教授 (30346837)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 生体生命情報学 / 分子機械 / 高分子構造・物性 / アルゴリズム / 生体超分子構造

Outline of Final Research Achievements

The biological data are hierarchical, and graph is one of the best data structures for presenting and unifying various biological data from molecules to phylogeny. In this study, multidisciplinary approach was taken to device the methods in comparing biological graphs. The graph-matching method for small molecules had successfully related structures and functions of naturally occurring drugs. The method for comparing phylogenetic trees was used to identify orthologous gene clusters in complex trees. The graph-based supramolecular modeling method had generated 3,197 human protein complex models, and the models revealed disease-related SNVs on the molecular interface for more than 10 disease. The model for EndoMS-PCNA-DNA complex, which specifically cleave mismatched DNA, was verified experimentally by single-particle EM method, and the graph-generated model was shown to be consistent with the experimental structure. The results indicated the usefulness of the graph-based methods.

Free Research Field

構造情報生物学