Boosting Protein Dynamics Studies Using Quantitative Nonuniform Sampling NMR Spectroscopy
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- Yoh Matsuki
- Institute for Protein Research, Osaka University, Osaka, Japan,
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- Tsuyoshi Konuma
- Bioorganic Research Institute, Suntory Foundation for Life Sciences, Osaka, Japan
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- Toshimichi Fujiwara
- Institute for Protein Research, Osaka University, Osaka, Japan,
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- Kenji Sugase
- Bioorganic Research Institute, Suntory Foundation for Life Sciences, Osaka, Japan
書誌事項
- 公開日
- 2011-11-01
- 資源種別
- journal article
- DOI
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- 10.1021/jp2081116
- 公開者
- American Chemical Society (ACS)
この論文をさがす
説明
NMR spectroscopy is uniquely suited to study protein dynamics over a wide range of time scales at atomic resolution. However, existing NMR relaxation methods require highly serial, lengthy data collection, ultimately limiting their application to short-lived samples, such as proteins in living cells. In recent years, the utility of nonuniform sampling (NUS) NMR methodologies has been increasingly recognized, but their application has been rare in relaxation measurements where highly accurate spectral quantification is demanded. Recently, Matsuki et al. developed a new NUS-processing method, SIFT (Spectroscopy by Integration of Frequency and Time domain information), which is highly robust and faithful in reproducing signals. In this work, we demonstrate the gains that are possible with more aggressive use of frequency domain information than was employed previously. This improvement is crucial for SIFT to be used in accelerating relaxation measurements while preserving full analytical accuracy. By taking the KIX domain of mouse CREB-binding protein (CBP) as an example, we demonstrate that this quantitative NUS processing method enables total 10-fold expedition of the R(2) relaxation dispersion measurements. The advanced SIFT processing should be equally useful for other NMR relaxation measurements.
収録刊行物
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- The Journal of Physical Chemistry B
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The Journal of Physical Chemistry B 115 (46), 13740-13745, 2011-11-01
American Chemical Society (ACS)
