2020 Fiscal Year Final Research Report
Application of supramolecular graph system to GWAS analyses
| Project/Area Number |
17H01818
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Life / Health / Medical informatics
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| Research Institution | Nagahama Institute of Bio-Science and Technology |
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Principal Investigator |
Shirai Tsuyoshi 長浜バイオ大学, バイオサイエンス学部, 教授 (00262890)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Keywords | 生命分子計算 / 生体超分子構造 / ゲノムワイド相関解析 / 分子間相互作用 |
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| Outline of Final Research Achievements |
The supra-molecular graph system, which contains more than 30,000 molecules (proteins and drugs) and human-diseases as nodes and more than 300,000 interactions (protein-protein, protein-drug, and protein-disease interactions) as edges, has been developed in this study. An application has been also developed to construct the structural models of the disease-related supra-molecules, in which disease-related and drug-target proteins were in complex, and more than 4,500 models were generated. The graph system was applied to GBDT machine learning, and it was demonstrated that the network-paths of disease - efficient drugs could be discriminated with 0.9 accuracy.
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| Free Research Field |
情報生物学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で開発した超分子グラフシステムにより、疾患とそれら疾患の治療薬を分子間相互作用に基づいて解析するためのデータ基盤が構築された。また、このシステムにより疾患関連タンパク質と医薬品ターゲットタンパク質(疾患関連超分子)の構造モデルを構築することで、医薬品の作用を分子構造に基づいて解析することが可能になった。さらに超分子グラフシステムに基づく機械学習により、疾患-有効医薬品の分子経路(パス)が高精度で判別可能であることから、このシステムが医薬品の論理的設計や新規の医薬品ターゲットの発見に応用可能であることが示された。
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