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Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data

NMR is a unique methodology for obtaining information about the conformational dynamics of proteins in heterogeneous biomolecular systems. In various NMR methods, such as transferred cross-saturation, relaxation dispersion, and paramagnetic relaxation enhancement experiments, fast determination of t...

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Autores principales: Ueda, Takumi, Yoshiura, Chie, Matsumoto, Masahiko, Kofuku, Yutaka, Okude, Junya, Kondo, Keita, Shiraishi, Yutaro, Takeuchi, Koh, Shimada, Ichio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4432090/
https://www.ncbi.nlm.nih.gov/pubmed/25677224
http://dx.doi.org/10.1007/s10858-015-9908-9
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author Ueda, Takumi
Yoshiura, Chie
Matsumoto, Masahiko
Kofuku, Yutaka
Okude, Junya
Kondo, Keita
Shiraishi, Yutaro
Takeuchi, Koh
Shimada, Ichio
author_facet Ueda, Takumi
Yoshiura, Chie
Matsumoto, Masahiko
Kofuku, Yutaka
Okude, Junya
Kondo, Keita
Shiraishi, Yutaro
Takeuchi, Koh
Shimada, Ichio
author_sort Ueda, Takumi
collection PubMed
description NMR is a unique methodology for obtaining information about the conformational dynamics of proteins in heterogeneous biomolecular systems. In various NMR methods, such as transferred cross-saturation, relaxation dispersion, and paramagnetic relaxation enhancement experiments, fast determination of the signal intensity ratios in the NMR spectra with high accuracy is required for analyses of targets with low yields and stabilities. However, conventional methods for the reconstruction of spectra from undersampled time-domain data, such as linear prediction, spectroscopy with integration of frequency and time domain, and analysis of Fourier, and compressed sensing were not effective for the accurate determination of the signal intensity ratios of the crowded two-dimensional spectra of proteins. Here, we developed an NMR spectra reconstruction method, “conservation of experimental data in analysis of Fourier” (Co-ANAFOR), to reconstruct the crowded spectra from the undersampled time-domain data. The number of sampling points required for the transferred cross-saturation experiments between membrane proteins, photosystem I and cytochrome b (6) f, and their ligand, plastocyanin, with Co-ANAFOR was half of that needed for linear prediction, and the peak height reduction ratios of the spectra reconstructed from truncated time-domain data by Co-ANAFOR were more accurate than those reconstructed from non-uniformly sampled data by compressed sensing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10858-015-9908-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-44320902015-05-19 Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data Ueda, Takumi Yoshiura, Chie Matsumoto, Masahiko Kofuku, Yutaka Okude, Junya Kondo, Keita Shiraishi, Yutaro Takeuchi, Koh Shimada, Ichio J Biomol NMR Article NMR is a unique methodology for obtaining information about the conformational dynamics of proteins in heterogeneous biomolecular systems. In various NMR methods, such as transferred cross-saturation, relaxation dispersion, and paramagnetic relaxation enhancement experiments, fast determination of the signal intensity ratios in the NMR spectra with high accuracy is required for analyses of targets with low yields and stabilities. However, conventional methods for the reconstruction of spectra from undersampled time-domain data, such as linear prediction, spectroscopy with integration of frequency and time domain, and analysis of Fourier, and compressed sensing were not effective for the accurate determination of the signal intensity ratios of the crowded two-dimensional spectra of proteins. Here, we developed an NMR spectra reconstruction method, “conservation of experimental data in analysis of Fourier” (Co-ANAFOR), to reconstruct the crowded spectra from the undersampled time-domain data. The number of sampling points required for the transferred cross-saturation experiments between membrane proteins, photosystem I and cytochrome b (6) f, and their ligand, plastocyanin, with Co-ANAFOR was half of that needed for linear prediction, and the peak height reduction ratios of the spectra reconstructed from truncated time-domain data by Co-ANAFOR were more accurate than those reconstructed from non-uniformly sampled data by compressed sensing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10858-015-9908-9) contains supplementary material, which is available to authorized users. Springer Netherlands 2015-02-13 2015 /pmc/articles/PMC4432090/ /pubmed/25677224 http://dx.doi.org/10.1007/s10858-015-9908-9 Text en © The Author(s) 2015 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Ueda, Takumi
Yoshiura, Chie
Matsumoto, Masahiko
Kofuku, Yutaka
Okude, Junya
Kondo, Keita
Shiraishi, Yutaro
Takeuchi, Koh
Shimada, Ichio
Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data
title Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data
title_full Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data
title_fullStr Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data
title_full_unstemmed Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data
title_short Development of a method for reconstruction of crowded NMR spectra from undersampled time-domain data
title_sort development of a method for reconstruction of crowded nmr spectra from undersampled time-domain data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4432090/
https://www.ncbi.nlm.nih.gov/pubmed/25677224
http://dx.doi.org/10.1007/s10858-015-9908-9
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