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Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs
RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291263/ https://www.ncbi.nlm.nih.gov/pubmed/27193998 http://dx.doi.org/10.1093/nar/gkw438 |
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author | Krepl, Miroslav Cléry, Antoine Blatter, Markus Allain, Frederic H.T. Sponer, Jiri |
author_facet | Krepl, Miroslav Cléry, Antoine Blatter, Markus Allain, Frederic H.T. Sponer, Jiri |
author_sort | Krepl, Miroslav |
collection | PubMed |
description | RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM–RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein–RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein–RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for ‘MD-adapted structure ensemble’ as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein–RNA complexes. |
format | Online Article Text |
id | pubmed-5291263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-52912632017-02-10 Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs Krepl, Miroslav Cléry, Antoine Blatter, Markus Allain, Frederic H.T. Sponer, Jiri Nucleic Acids Res Structural Biology RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM–RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein–RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein–RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for ‘MD-adapted structure ensemble’ as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein–RNA complexes. Oxford University Press 2016-07-27 2016-05-18 /pmc/articles/PMC5291263/ /pubmed/27193998 http://dx.doi.org/10.1093/nar/gkw438 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Structural Biology Krepl, Miroslav Cléry, Antoine Blatter, Markus Allain, Frederic H.T. Sponer, Jiri Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs |
title | Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs |
title_full | Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs |
title_fullStr | Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs |
title_full_unstemmed | Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs |
title_short | Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs |
title_sort | synergy between nmr measurements and md simulations of protein/rna complexes: application to the rrms, the most common rna recognition motifs |
topic | Structural Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291263/ https://www.ncbi.nlm.nih.gov/pubmed/27193998 http://dx.doi.org/10.1093/nar/gkw438 |
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