Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets

被引:74
作者
Stanek, Jan [1 ]
Kozminski, Wiktor [1 ]
机构
[1] Univ Warsaw, Fac Chem, PL-02093 Warsaw, Poland
关键词
Multidimensional NMR spectroscopy; Fourier transformation; Sparse sampling; Random sampling; NOESY; Proteins; Ubiquitin; FILTER DIAGONALIZATION METHOD; COUPLED EVOLUTION PERIODS; MULTIDIMENSIONAL NMR; REDUCED-DIMENSIONALITY; MAXIMUM-ENTROPY; TIME-DOMAIN; SPECTRAL RECONSTRUCTION; FAST ACQUISITION; RESOLUTION; SPECTROSCOPY;
D O I
10.1007/s10858-010-9411-2
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Spectra obtained by application of multidimensional Fourier Transformation (MFT) to sparsely sampled nD NMR signals are usually corrupted due to missing data. In the present paper this phenomenon is investigated on simulations and experiments. An effective iterative algorithm for artifact suppression for sparse on-grid NMR data sets is discussed in detail. It includes automated peak recognition based on statistical methods. The results enable one to study NMR spectra of high dynamic range of peak intensities preserving benefits of random sampling, namely the superior resolution in indirectly measured dimensions. Experimental examples include 3D (15)N- and (13)C-edited NOESY-HSQC spectra of human ubiquitin.
引用
收藏
页码:65 / 77
页数:13
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