Parameter Estimation of Multidimensional NMR Signals based on High-Resolution Subband Analysis of 2D NMR Projections
Paper in proceeding, 2009

NMR spectroscopy is a powerful technique used in protein research for comprehensive functional characterizations, e.g. structure determination at atomic resolution. Due to the molecular size (typically>1000 atoms), proteinNMR spectra contain a large number of signal frequencies. Resolving these requires high-dimensional spectroscopy. However, when the number of frequency exceeds three, conventional approaches start to demand unrealistic long experiment time, and the data analysis becomes challenging. In this paper we explore a combination of novel methods: Data from 5D NMR experiments are recorded as a series of 2D projections, which are then subjected to 2D subband filters and 2D LS-ESPRIT for estimation of signal parameters. Based on the relations established between 5D NMR signals and their 2D counterparts, projection spectroscopy allows to extract highly similar information as what would be found in conventional 5D NMR experiments; however, while the latter would require months of experiment time, the recording of all necessary projections can be accomplished within 1-2 days. Preliminary results show the efficiency of the method with respect to accuracy and resolution of the parameter estimates as compared with conventional methods.

multidimensional NMR

2D subband

projection spectroscopy

2D ESPRIT

frequency estimation

protein structures.

Author

Irene Yu-Hua Gu

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Martin Billeter

University of Gothenburg

Mohammad Reza Sharafy

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Vahid Anhari Sorkhabi

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Jonas Fredriksson

University of Gothenburg

Doroteya Staykova

University of Gothenburg

IEEE International Conf. Acoustics, Speech and Signal Processing (ICASSP 2009)

497-500

Subject Categories

Biochemistry and Molecular Biology

Chemical Engineering

Signal Processing

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Created

10/7/2017