Covariance NMR in higher dimensions: application to 4D NOESY spectroscopy of proteins

Elucidation of high-resolution protein structures by NMR spectroscopy requires a large number of distance constraints that are derived from nuclear Overhauser effects between protons (NOEs). Due to the high level of spectral overlap encountered in 2D NMR spectra of proteins, the measurement of high quality distance constraints requires higher dimensional NMR experiments. Although four-dimensional Fourier transform (FT) NMR experiments can provide the necessary kind of spectral information, the associated measurement times are often prohibitively long. Covariance NMR spectroscopy yields 2D spectra that exhibit along the indirect frequency dimension the same high resolution as along the direct dimension using minimal measurement time. The generalization of covariance NMR to 4D NMR spectroscopy presented here exploits the inherent symmetry of certain 4D NMR experiments and utilizes the trace metric between donor planes for the construction of a high-resolution spectral covariance matrix. The approach is demonstrated for a 4D (13)C-edited NOESY experiment of ubiquitin. The 4D covariance spectrum narrows the line-widths of peaks strongly broadened in the FT spectrum due to the necessarily short number of increments collected, and it resolves otherwise overlapped cross peaks allowing for an increase in the number of NOE assignments to be made from a given dataset. At the same time there is no significant decrease in the positive predictive value of observing a peak as compared to the corresponding 4D Fourier transform spectrum. These properties make the 4D covariance method a potentially valuable tool for the structure determination of larger proteins and for high-throughput applications in structural biology.