Abstract
NMR relaxation dispersion experiments play a central role in exploring molecular motion over an important range of timescales, and are an example of a broader class of multidimensional NMR experiments that probe important biomolecules. However, resolving the spectral features of these experiments using the Fourier transform requires sampling the full Nyquist grid of data, making these experiments very costly in time. Practitioners often reduce the experiment time by omitting 1D experiments in the indirectly observed dimensions, and reconstructing the spectra using one of a variety of post-processing algorithms. In prior work, we described a fast, Fourier-based reconstruction method using iterated maps according to the Difference Map algorithm of Veit Elser (DiffMap). Here we describe coDiffMap, a new reconstruction method that is based on DiffMap, but which exploits the strong correlations between 2D data slices in a pseudo-3D experiment. We apply coDiffMap to reconstruct dispersion curves from an \(R_2\) relaxation dispersion experiment, and demonstrate that the method provides fast reconstructions and accurate relaxation curves down to very low numbers of sparsely-sampled data points.
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Acknowledgements
We thank G. Manley for acquiring the IGPS data set. We thank D. Cui, G. Manley, and S. Elrington for helpful discussions. J.P. Loria acknowledges the support of the NSF through Grant No. MCB-1615415, and the NIH through Grant No. GM112781. R. Blum, J. Rovny, and S. Barrett acknowledge the support of the NSF through Grant No. DMR-1610313 and Grant No. DMR-1310274. R. Blum is an NSF fellow and this material is based upon work supported by the NSF GRFP under Grant No. DGE-1122492.
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Rovny, J., Blum, R.L., Loria, J.P. et al. Accelerating 2D NMR relaxation dispersion experiments using iterated maps. J Biomol NMR 73, 561–576 (2019). https://doi.org/10.1007/s10858-019-00263-3
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DOI: https://doi.org/10.1007/s10858-019-00263-3