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Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics

[Image: see text] Molecular dynamics (MD) simulations for RNA tetramers r(AAAA), r(CAAU), r(GACC), and r(UUUU) are benchmarked against (1)H–(1)H NOESY distances and (3)J scalar couplings to test effects of RNA torsion parametrizations. Four different starting structures were used for r(AAAA), r(CAAU...

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Autores principales: Condon, David E., Kennedy, Scott D., Mort, Brendan C., Kierzek, Ryszard, Yildirim, Ilyas, Turner, Douglas H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2015
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4463549/
https://www.ncbi.nlm.nih.gov/pubmed/26082675
http://dx.doi.org/10.1021/ct501025q
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author Condon, David E.
Kennedy, Scott D.
Mort, Brendan C.
Kierzek, Ryszard
Yildirim, Ilyas
Turner, Douglas H.
author_facet Condon, David E.
Kennedy, Scott D.
Mort, Brendan C.
Kierzek, Ryszard
Yildirim, Ilyas
Turner, Douglas H.
author_sort Condon, David E.
collection PubMed
description [Image: see text] Molecular dynamics (MD) simulations for RNA tetramers r(AAAA), r(CAAU), r(GACC), and r(UUUU) are benchmarked against (1)H–(1)H NOESY distances and (3)J scalar couplings to test effects of RNA torsion parametrizations. Four different starting structures were used for r(AAAA), r(CAAU), and r(GACC), while five starting structures were used for r(UUUU). On the basis of X-ray structures, criteria are reported for quantifying stacking. The force fields, AMBER ff99, parmbsc0, parm99χ_Yil, ff10, and parmTor, all predict experimentally unobserved stacks and intercalations, e.g., base 1 stacked between bases 3 and 4, and incorrect χ, ϵ, and sugar pucker populations. The intercalated structures are particularly stable, often lasting several microseconds. Parmbsc0, parm99χ_Yil, and ff10 give similar agreement with NMR, but the best agreement is only 46%. Experimentally unobserved intercalations typically are associated with reduced solvent accessible surface area along with amino and hydroxyl hydrogen bonds to phosphate nonbridging oxygens. Results from an extensive set of MD simulations suggest that recent force field parametrizations improve predictions, but further improvements are necessary to provide reasonable agreement with NMR. In particular, intramolecular stacking and hydrogen bonding interactions may not be well balanced with the TIP3P water model. NMR data and the scoring method presented here provide rigorous benchmarks for future changes in force fields and MD methods.
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spelling pubmed-44635492015-06-14 Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics Condon, David E. Kennedy, Scott D. Mort, Brendan C. Kierzek, Ryszard Yildirim, Ilyas Turner, Douglas H. J Chem Theory Comput [Image: see text] Molecular dynamics (MD) simulations for RNA tetramers r(AAAA), r(CAAU), r(GACC), and r(UUUU) are benchmarked against (1)H–(1)H NOESY distances and (3)J scalar couplings to test effects of RNA torsion parametrizations. Four different starting structures were used for r(AAAA), r(CAAU), and r(GACC), while five starting structures were used for r(UUUU). On the basis of X-ray structures, criteria are reported for quantifying stacking. The force fields, AMBER ff99, parmbsc0, parm99χ_Yil, ff10, and parmTor, all predict experimentally unobserved stacks and intercalations, e.g., base 1 stacked between bases 3 and 4, and incorrect χ, ϵ, and sugar pucker populations. The intercalated structures are particularly stable, often lasting several microseconds. Parmbsc0, parm99χ_Yil, and ff10 give similar agreement with NMR, but the best agreement is only 46%. Experimentally unobserved intercalations typically are associated with reduced solvent accessible surface area along with amino and hydroxyl hydrogen bonds to phosphate nonbridging oxygens. Results from an extensive set of MD simulations suggest that recent force field parametrizations improve predictions, but further improvements are necessary to provide reasonable agreement with NMR. In particular, intramolecular stacking and hydrogen bonding interactions may not be well balanced with the TIP3P water model. NMR data and the scoring method presented here provide rigorous benchmarks for future changes in force fields and MD methods. American Chemical Society 2015-04-16 2015-06-09 /pmc/articles/PMC4463549/ /pubmed/26082675 http://dx.doi.org/10.1021/ct501025q Text en Copyright © 2015 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Condon, David E.
Kennedy, Scott D.
Mort, Brendan C.
Kierzek, Ryszard
Yildirim, Ilyas
Turner, Douglas H.
Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics
title Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics
title_full Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics
title_fullStr Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics
title_full_unstemmed Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics
title_short Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics
title_sort stacking in rna: nmr of four tetramers benchmark molecular dynamics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4463549/
https://www.ncbi.nlm.nih.gov/pubmed/26082675
http://dx.doi.org/10.1021/ct501025q
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