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An analysis of NMR sensitivity enhancements obtained using non-uniform weighted sampling, and the application to protein NMR

Waudby, CA; Christodoulou, J; (2012) An analysis of NMR sensitivity enhancements obtained using non-uniform weighted sampling, and the application to protein NMR. Journal of Magnetic Resonance , 219 pp. 46-52. 10.1016/j.jmr.2012.04.013. Green open access

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Abstract

Non-uniform weighted sampling (NUWS) is a sampling strategy, related to non-uniform sampling (NUS) in the limit of long acquisition times, in which each indirect increment of a multidimensional spectrum is sampled multiple times according to some weighting function. As the spectrum is fully sampled it can be processed in a conventional manner by the discrete Fourier transform, making the analysis of sensitivity much more straightforward than for NUS data. Previously, 2-3 fold increases in signal-to-noise ratio (SNR) have been reported using NUWS. However, as the sampling schedule acts as a window function, the observed SNR must be compared with uniformly sampled data apodized using the same weighting function. On doing this, we calculate more modest improvements of 10-20% in SNR, and these are verified experimentally for spectra of α-synuclein and YFP. Nevertheless, we prove that NUWS always improves the sensitivity compared with identically processed uniformly sampled data, and when combined with rapid recycling experiments such as the SOFAST-HMQC, NUWS methods have the potential to make a useful and practical contribution to sensitivity-limited measurements.

Type: Article
Title: An analysis of NMR sensitivity enhancements obtained using non-uniform weighted sampling, and the application to protein NMR
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.jmr.2012.04.013
Publisher version: http://dx.doi.org/10.1016/j.jmr.2012.04.013
Language: English
Additional information: Copyright © 2012 Elsevier Inc. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. The published article is available from the journal website at http://dx.doi.org/10.1016/j.jmr.2012.04.013
Keywords: Algorithms, Computer Simulation, Magnetic Resonance Spectroscopy, Models, Chemical, Models, Statistical, Proteins, Sample Size
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Structural and Molecular Biology
URI: https://discovery.ucl.ac.uk/id/eprint/1365841
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