Site-Specific 13C Chemical Shift Anisotropy Measurements in a Uniformly 15N,13C-Labeled Microcrystalline Protein by 3D Magic-Angle Spinning NMR Spectroscopy
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- 作者：Benjamin J. Wylie ; W. Trent Franks ; Daniel T. Graesser ; and Chad M. Rienstra
- 刊名：Journal of the American Chemical Society
- 出版年：2005
- 出版时间：August 31, 2005
- 年：2005
- 卷：127
- 期：34
- 页码：11946 - 11947
- 全文大小：57K
- 年卷期：v.127,no.34(August 31, 2005)
- ISSN：1520-5126
文摘
In this Communication, we introduce a 3D magic-angle spinning recoupling experiment that correlates chemical shift anisotropy (CSA) powder line shapes with two dimensions of site-resolved isotropic chemical shifts. The principal tensor elements from 127 ROCSA line shapes are reported, constraining 102 unique backbone and side-chain 13C sites in a microcrystalline protein (the 56 residue 
1 immunoglobulin binding domain of protein G). The tensor elements, determined by fitting to numerical simulations, agree well with quantum chemical predictions. The experiments, therefore, validate calculations of CSAs in a protein of known structure. The data will be useful for the development of side-chain CSA quantum calculations and will aid in the design and interpretation of solution NMR experiments that utilize CSA-dipole cross-correlation to constrain torsion angles or to enhance resolution and sensitivity (such as in TROSY). Furthermore, the methodology described here will enable databases of CSA data to be generated with higher efficiency, for purposes of direct protein structure refinement.
1 immunoglobulin binding domain of protein G). The tensor elements, determined by fitting to numerical simulations, agree well with quantum chemical predictions. The experiments, therefore, validate calculations of CSAs in a protein of known structure. The data will be useful for the development of side-chain CSA quantum calculations and will aid in the design and interpretation of solution NMR experiments that utilize CSA-dipole cross-correlation to constrain torsion angles or to enhance resolution and sensitivity (such as in TROSY). Furthermore, the methodology described here will enable databases of CSA data to be generated with higher efficiency, for purposes of direct protein structure refinement.