NMR Backbone Assignment of Large Proteins by Using C-13(alpha)-Only Triple-Resonance Experiments

作者：Wei, Qingtao; Chen, Jiajing; Mi, Juan; Zhang, Jiahai; Ruan, Ke^*; Wu, Jihui^*

来源：Chemistry - A European Journal, 2016, 22(28): 9556-9564.

DOI：10.1002/chem.201601871

• backbone assignment
• covariance NMR
• isotope labeling
• NMR spectroscopy
• proteins

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 C-13(alpha) 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 Bruschweiler (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.

• 出版日期2016-7-4
• 单位中国科学技术大学