Tropical diseases-related protein-protein interaction analysis by using exhaustive docking
| Project/Area Number |
16K00388
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Life / Health / Medical informatics
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
Matsuzaki Yuri 東京工業大学, リーダーシップ教育院, 特任准教授 (30572888)
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| Co-Investigator(Kenkyū-buntansha) |
内古閑 伸之 明治大学, 総合数理学部, 助教 (20397483)
黒川 裕美子 国立遺伝学研究所, 新分野創造センター, 特任研究員 (10381633)
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| Research Collaborator |
Shimu Yaku KU Leuven
Marutan Jurietto Lyon University 1
Renei Giyomu Lyon University 1
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | タンパク質間相互作用 / タンパク質ドッキング / タンパク質間相互作用ネットワーク / 並列計算 |
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| Outline of Final Research Achievements |
We have developed a computational method of protein-protein interaction (PPI) prediction by using interaction profile analysis of rigid-docking decoys. By combining originially developed interaction fingerprint representation of docking decoys and an extended machine learning (extra-trees) method, we have successfully improved prediction performance of conventional docking based prediction methods. We applied this PPI prediction method on predicting i) PPIs of Trypanosoma cruzi and ii) interactions of dengue virus and human proteins and obtained in total 67 novel PPI candidates. Two candidate pairs of high prediction score were tested by immunoprecipitation experiments and one was confirmed to have affinity. We have also conducted comparison analysis of virus-human and human-human protein interactions in terms of interaction fingerprints of docking decoy set.
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| Academic Significance and Societal Importance of the Research Achievements |
熱帯病を引き起こす寄生生物やウイルスに関する基礎的な生物学研究は，経済的な問題からあまり進んでおらず，多くのPPI 情報が既に知られているヒトとは異なり，新規PPI 発見やPPI ネットワークの理解が創薬におけるターゲットタンパク質の選択に有用な情報となる．PPI 予測は困難な問題である一方，現時点で15万件をこえるタンパク質立体構造データが公開データベース（PDB）に蓄積されている．従来のPPI ネットワーク予測研究では十分には活用されてこなかったこれらのデータを活用することで，未知PPI の発見や，ウイルス-宿主間PPI の特徴の発見などの結果を得ることが期待できる．
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Report
(4 results)
Research Products
(21 results)
