Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm

A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows...

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Detalles Bibliográficos
Autores principales: Kosiński, Krzysztof, Stanek, Jan, Górka, Michał J., Żerko, Szymon, Koźmiński, Wiktor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5504137/
https://www.ncbi.nlm.nih.gov/pubmed/28243768
http://dx.doi.org/10.1007/s10858-017-0095-8
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author Kosiński, Krzysztof
Stanek, Jan
Górka, Michał J.
Żerko, Szymon
Koźmiński, Wiktor
author_facet Kosiński, Krzysztof
Stanek, Jan
Górka, Michał J.
Żerko, Szymon
Koźmiński, Wiktor
author_sort Kosiński, Krzysztof
collection PubMed
description A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH.
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spelling pubmed-55041372017-07-25 Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm Kosiński, Krzysztof Stanek, Jan Górka, Michał J. Żerko, Szymon Koźmiński, Wiktor J Biomol NMR Article A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH. Springer Netherlands 2017-02-28 2017 /pmc/articles/PMC5504137/ /pubmed/28243768 http://dx.doi.org/10.1007/s10858-017-0095-8 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Kosiński, Krzysztof
Stanek, Jan
Górka, Michał J.
Żerko, Szymon
Koźmiński, Wiktor
Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
title Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
title_full Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
title_fullStr Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
title_full_unstemmed Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
title_short Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
title_sort reconstruction of non-uniformly sampled five-dimensional nmr spectra by signal separation algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5504137/
https://www.ncbi.nlm.nih.gov/pubmed/28243768
http://dx.doi.org/10.1007/s10858-017-0095-8
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