Optimization of Multidimensional Nuclear Magnetic Resonance Spectroscopy, for Resolution and Sensitivity, Through Application of Radial Sampling

The high probability of degenerate frequencies in NMR spectra of complex biopolymers such as proteins presented a great barrier to detailed analysis. The combination of multidimensional NMR spectroscopy and high magnetic field strengths has overcome the resulting resonance assignment problem for proteins less than 50 kDa. However, as protein size increases the sampling and sensitivity limited regimes become apparent. As a consequence, the orthogonal linear sampling requirements of conventional multidimensional NMR spectroscopy, combined with increased signal averaging require a longer acquisition time than is feasible. To overcome these limitations, radial sampling of the indirect dimensions of multidimensional experiments is utilized. It is demonstrated here, that through optimization of radial sampling acquisition parameters, it is possible to escape the linear sequential sampling requirements of Cartesian sampling, which allows for the collection of a high resolution spectrum in reduced acquisition time. Further, by exploiting a fundamental statistical advantage of radial sampling, it is possible to obtain a signal-to-noise advantage, over the traditional methodology. The approach is generalized by developing an all inclusive NMR data processing package and associated programs to optimize radial sampling acquisition parameters. An example, which utilizes the resolution and sensitivity advantages, to collect a novel application of a high resolution four-dimensional 13C, 15N edited NOESY is presented in support.