Non-uniform sampling in biomolecular magic angle spinning solid state nuclear magnetic resonance

Nuclear magnetic resonance (NMR) is a commonly used method in many fields of chemistry. It aids in the understanding of molecular structure, interactions and dynamics. These properties require the acquisition of correlations between NMR-active spins via magic-angle spinning (MAS) solid-state NMR of immiscible materials. Such correlations are detected through multi-dimensional experiments that are conducted by uniformly sampling a time grid. It is common and simple to collect data that way, for the processing power cost is fairly low owing to the simple algorithm of fast Fourier transform (FFT). In recent years, and in line with increasing computational power, different time inversion processing algorithms such as entropy reconstruction enabled the use of non-uniform sampling (NUS) as an alternative sampling scheme. The use of NUS improves signal-to-noise while shortening two-dimensional experiments 2-4 fold and three-dimensional experiments even further. The big improvement is gained mainly through choosing a proper sampling schedule, thus acquiring less noise and enabling the acquisition of broader spectral widths at no expense of experiment time.

We will show our recent efforts to adapt NUS techniques for the study of two-dimensional spectra of Li-ATP and the filamentous bacteriophage IKe. We compare different schedules, sampling coverages, acquisition times and dwell times, and report on the best scheme to enhance the signals, keep an acceptable dynamic range and reduce artifacts.

Future work will focus on applying the best NUS schedules derived from the analysis above in order to study structure and dynamics in various forms of bacteriophage viruses including filamentous and spherical phage. Optimizing NUS assures that such spectra will be achieved during much shorter experimental times yet with consistent spectral information.

References:

Mobli and J. C. Hoch, “Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR,” Prog. Nucl. Magn. Reson. Spectrosc., vol. 83, pp. 21–41, 2014