| Project/Area Number |
25440032
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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 |
Structural biochemistry
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| Research Institution | Tokyo Metropolitan University |
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Principal Investigator |
Peter Guentert 首都大学東京, 理工学研究科, 教授 (20392110)
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| Co-Investigator(Kenkyū-buntansha) |
Ikeya Teppei 首都大学東京, 理工学研究科, 助教 (30457840)
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| Co-Investigator(Renkei-kenkyūsha) |
Ito Yutaka 首都大学東京, 理工学研究科, 教授 (80261147)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | NMR立体構造計算 / NMR信号自動解析 / NMR 立体構造計算 / CYANA / NOE自動解析 / eNOE / NMR^2 / ベイズ推定 / 蛋白質-リガンド複合体 / In-cell NMR / NMRデータの自動帰属 / 構造計算 / FLYA |
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| Outline of Final Research Achievements |
In-cell NMR has enabled the direct observation of proteins in living cells. We developed the CYANA software specifically for in-cell NMR. The automated chemical shift and NOE assignment algorithms in CYANA were adapted for better handling of in-cell NMR spectra processed with nonlinear sampling techniques.The automated chemical shifts assignment is significantly more robust and efficient than previous methods, and NMR structure calculation algorithm based on Bayesian inference are cornerstones for this. Compared to spectra of purified proteins, in-cell NMR ones typically show a significant number of background signals, low signal-noise ratio, and broadened signals that lead to much higher assignment ambiguity, which makes it difficult and cumbersome to check all possibilities manually. An algorithm can exhaustively search all candidates and determine assignments more quickly and more objectively. The viability of the in-cell CYANA approach was shown by applying it to in-cell NMR data.
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