Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets
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 15N- and 13C-edited NOESY-HSQC spectra of human ubiquitin.
KeywordsMultidimensional NMR spectroscopy Fourier transformation Sparse sampling Random sampling NOESY Proteins Ubiquitin
Special thanks are addressed at Maxim Mayzel from Swedish NMR Centre for his help in using MDD package, and at prof. J.C. Hoch from University of Connecticut Health Center for providing access to Rowland NMR Toolkit v.3. This work was supported by grant number: N301 07131/2159, founded by Ministry of Science and Higher Education in years 2006-2009. Research cofinanced by the European Social Fund and State funds under the Integrated Regional Operational Programme, Measure 2.6 “Regional Innovation Strategies and transfer of knowledge”, Mazovian Voivodship project “Mazovian Ph.D. Scholarship”.
- Barna JCJ, Tan SM, Laue ED (1988) Use of CLEAN in conjunction with selective data sampling for 2D NMR experiments. J Magn Reson 78:327–332Google Scholar
- Bodenhausen G, Ernst RR (1981) The accordion experiment, a simple approach to three-dimensional NMR spectroscopy. J Magn Reson 45:367–373Google Scholar
- Bracewell RN (2000) The Fourier transform and its applications. McGraw-Hill Higher Education, New YorkGoogle Scholar
- Goddart TD, Kneller DG (1989–2008) SPARKY 3. University of California, San FranciscoGoogle Scholar
- Hoch JC, Stern AS (1996) NMR data processing. Wiley, New YorkGoogle Scholar
- Press WH, Flannery BP, Teukolsky SA, Vetterling WT (2007) Numerical recipes in C, 3rd edn. Cambridge University Press, CambridgeGoogle Scholar