Optimized angle selection for radial sampled NMR experiments

NASR: an effective approach for simultaneous noise and artifact suppression in NMR spectroscopy

As a powerful tool for biological analysis, especially protein structure and dynamic studies, nuclear magnetic resonance (NMR) spectroscopy suffers from intrinsic low signal to nose ratio (SNR) and long acquisition time required for multidimensional (nD) experiments. Nonuniform sampling (NUS) can effectively speed up the experiment but often introduces artifacts into the spectrum. In addition to the development of highly sensitive hardware and NMR pulse sequences, data postprocessing is a relative simple and cost-effective method to improve the SNR and suppress the artifacts. In this work, we propose an effective approach for simultaneously suppressing noise and artifacts based on the resampling principle. The method is named NASR for short and tested using one-, two-, and three-dimensional (1D, 2D, and 3D) NMR spectra that were acquired using ether conventional or NUS (spiral and random, for 3D) approaches. The results reveal that the NASR is fast and applicable for improving the quality of 1D to nD NMR spectra with all kinds of sampling schemes.

Al NMR: a novel NMR data processing program optimized for sparse sampling

Sparse sampling in biomolecular multidimensional NMR offers increased acquisition speed and resolution and, if appropriate conditions are met, an increase in sensitivity. Sparse sampling of indirectly detected time domains combined with the direct truly multidimensional Fourier transform has elicited particular attention because of the ability to generate a final spectrum amenable to traditional analysis techniques. A number of sparse sampling schemes have been described including radial sampling, random sampling, concentric sampling and variations thereof. A fundamental feature of these sampling schemes is that the resulting time domain data array is not amenable to traditional Fourier transform based processing and phasing correction techniques. In addition, radial sampling approaches offer a number of advantages and capabilities that are also not accessible using standard NMR processing techniques. These include sensitivity enhancement, sub-matrix processing and determination of minimal sets of sampling angles. Here we describe a new software package (Al NMR) that enables these capabilities in the context of a general NMR data processing environment.

Optimized linear prediction for radial sampled multidimensional NMR experiments

Radial sampling in multidimensional NMR experiments offers greatly decreased acquisition times while also providing an avenue for increased sensitivity. Digital resolution remains a concern and depends strongly upon the extent of sampling of individual radial angles. Truncated time domain data leads to spurious peaks (artifacts) upon FT and 2D FT. Linear prediction is commonly employed to improve resolution in Cartesian sampled NMR experiments. Here, we adapt the linear prediction method to radial sampling. Significantly more accurate estimates of linear prediction coefficients are obtained by combining quadrature frequency components from the multiple angle spectra. This approach results in significant improvement in both resolution and removal of spurious peaks as compared to traditional linear prediction methods applied to radial sampled data. The 'averaging linear prediction' (ALP) method is demonstrated as a general tool for resolution improvement in multidimensional radial sampled experiments.

SEnD NMR: sensitivity enhanced n-dimensional NMR

Sparse sampling offers tremendous potential for overcoming the time limitations imposed by traditional Cartesian sampling of indirectly detected dimensions of multidimensional NMR data. However, in many instances sensitivity rather than time remains of foremost importance when collecting data on protein samples. Here we explore how to optimize the collection of radial sampled multidimensional NMR data to achieve maximal signal-to-noise. A method is presented that exploits a rigorous definition of the minimal set of radial sampling angles required to resolve all peaks of interest in combination with a fundamental statistical property of radial sampled data. The approach appears general and can achieve a substantial sensitivity advantage over Cartesian sampling for the same total data acquisition time. Termed Sensitivity Enhanced n-Dimensional or SEnD NMR, the method involves three basic steps. First, data collection is optimized using routines to determine a minimal set of radial sampling angles required to resolve frequencies in the radially sampled chemical shift evolution dimensions. Second, appropriate combinations of experimental parameters (transients and increments) are defined by simple statistical considerations in order to optimize signal-to-noise in single angle frequency domain spectra. Finally, the data is processed with a direct multidimensional Fourier transform and a statistical artifact and noise removal step is employed.

AMORE-HX: a multidimensional optimization of radial enhanced NMR-sampled hydrogen exchange

The Cartesian sampled three-dimensional HNCO experiment is inherently limited in time resolution and sensitivity for the real time measurement of protein hydrogen exchange. This is largely overcome by use of the radial HNCO experiment that employs the use of optimized sampling angles. The significant practical limitation presented by use of three-dimensional data is the large data storage and processing requirements necessary and is largely overcome by taking advantage of the inherent capabilities of the 2D-FT to process selective frequency space without artifact or limitation. Decomposition of angle spectra into positive and negative ridge components provides increased resolution and allows statistical averaging of intensity and therefore increased precision. Strategies for averaging ridge cross sections within and between angle spectra are developed to allow further statistical approaches for increasing the precision of measured hydrogen occupancy. Intensity artifacts potentially introduced by over-pulsing are effectively eliminated by use of the BEST approach.