NMR Backbone Assignment of Large Proteins by Using 13Cα‐Only Triple‐Resonance Experiments |
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Authors: | Dr Qingtao Wei Dr Jiajing Chen Dr Juan Mi Dr Jiahai Zhang Prof Ke Ruan Prof Jihui Wu |
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Institution: | Hefei National Laboratory for Physical Sciences at Microscale, Collaborative Innovation Center of Chemistry for Life Sciences, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, P.R. China |
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Abstract: | Nuclear magnetic resonance (NMR) is a powerful tool to interrogate protein structure and dynamics residue by residue. However, the prerequisite chemical‐shift assignment remains a bottleneck for large proteins due to the fast relaxation and the frequency degeneracy of the 13Cα nuclei. Herein, we present a covariance NMR strategy to assign the backbone chemical shifts by using only HN(CO)CA and HNCA spectra that has a high sensitivity even for large proteins. By using the peak linear correlation coefficient (LCC), which is a sensitive probe even for tiny chemical‐shift displacements, we correctly identify the fidelity of approximately 92 % cross‐peaks in the covariance spectrum, which is thus a significant improvement on the approach developed by Snyder and Brüschweiler (66 %) and the use of spectral derivatives (50 %). Thus, we calculate the 4D covariance spectrum from HN(CO)CA and HNCA experiments, in which cross‐peaks with LCCs above a universal threshold are considered as true correlations. This 4D covariance spectrum enables the sequential assignment of a 42 kDa maltose binding protein (MBP), in which about 95 % residues are successfully assigned with a high accuracy of 98 %. Our LCC approach, therefore, paves the way for a residue‐by‐residue study of the backbone structure and dynamics of large proteins. |
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Keywords: | backbone assignment covariance NMR isotope labeling NMR spectroscopy proteins |
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