Development of fully-automated system for NMR structural analysis of higher molecular weight proteins
Project/Area Number |
17H03641
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Research Category |
Grant-in-Aid for Scientific Research (B)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Structural biochemistry
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Research Institution | Yokohama National University |
Principal Investigator |
KOJIMA Chojiro 横浜国立大学, 大学院工学研究院, 教授 (50333563)
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Project Period (FY) |
2017-04-01 – 2020-03-31
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Project Status |
Completed (Fiscal Year 2019)
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Budget Amount *help |
¥17,420,000 (Direct Cost: ¥13,400,000、Indirect Cost: ¥4,020,000)
Fiscal Year 2019: ¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2018: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
Fiscal Year 2017: ¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
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Keywords | NMR / 蛋白質 / 立体構造 |
Outline of Final Research Achievements |
In this research, we have developed a system for determining the NMR structure of higher molecular weight proteins by making use of 950 MHz NMR equipment and fully automated structure calculation software. Specifically, the utilizitation of fully automated NMR structural determination system MagRO, amino acid selective labeling technology, and methyl group-selective deuterium labeling has enabled the structural analysis of protein-protein and protein-drug complexes.
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Academic Significance and Societal Importance of the Research Achievements |
NMRによる蛋白質の立体構造決定は専門性が高く、今まで専門家以外の研究者が利用することが難しかった。本研究では、大阪大学蛋白質研究所で整備されている世界最高感度のNMR装置、小林直宏博士(現理化学研究所)が開発した全自動NMR自動構造計算ソフト、独自開発の安定同位体標識技術などを用いることで、高分子量蛋白質にNMR構造解析が適用可能であることを示した。今後は蛋白質のNMR構造解析の汎用化が進むと考えられる。
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Report
(4 results)
Research Products
(27 results)
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[Journal Article] Structural characterization of the N-terminal kinase-interacting domain of an Hsp90-cochaperone Cdc37 by CD and solution NMR spectroscopy.2019
Author(s)
Ihama, F., Yamamoto, M., Kojima, C., Fujiwara, T., Matsuzaki, K., Miyata, Y., Hoshino, M.
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Journal Title
Biochim. Biophys. Acta-Proteins Proteom.
Volume: 1867
Issue: 9
Pages: 813-820
DOI
Related Report
Peer Reviewed
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[Journal Article] Noise peak filtering in multi-dimensional NMR spectra using convolutional neural networks2018
Author(s)
Kobayashi, N., Hattori, Y., Nagata, T., Shinya, S., Guentert, P., Kojima, C., Fujiwara, T.
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Journal Title
Bioinformatics
Volume: 34
Issue: 24
Pages: 4300-4301
DOI
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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