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Molecular Dynamics-Assisted Optimization of Protein NMR Relaxation Analysis
[Image: see text] NMR relaxation analysis of the mobile residues in globular proteins is sensitive to the form of the experimentally fitted internal autocorrelation function, which is used to represent that motion. Different order parameter representations can precisely fit the same set of (15)N R(1...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009080/ https://www.ncbi.nlm.nih.gov/pubmed/35245056 http://dx.doi.org/10.1021/acs.jctc.1c01165 |
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author | Anderson, Janet S. Hernández, Griselda LeMaster, David M. |
author_facet | Anderson, Janet S. Hernández, Griselda LeMaster, David M. |
author_sort | Anderson, Janet S. |
collection | PubMed |
description | [Image: see text] NMR relaxation analysis of the mobile residues in globular proteins is sensitive to the form of the experimentally fitted internal autocorrelation function, which is used to represent that motion. Different order parameter representations can precisely fit the same set of (15)N R(1), R(2), and heteronuclear NOE measurements while yielding significantly divergent predictions of the underlying autocorrelation functions, indicating the insufficiency of these experimental relaxation data for assessing which order parameter representation provides the most physically realistic predictions. Molecular dynamics simulations offer an unparalleled capability for discriminating among different order parameter representations to assess which representation can most accurately model a wide range of physically realistic autocorrelation functions. Six currently utilized AMBER and CHARMM force fields were applied to calculate autocorrelation functions for the backbone H–N bond vectors of ubiquitin as an operational test set. An optimized time constant-constrained triexponential (TCCT) representation was shown to markedly outperform the widely used (S(f)(2),τ(s),S(2)) extended Lipari–Szabo representation and the more closely related (S(f)(2),S(H)(2), S(N)(2)) Larmor frequency-selective representation. Optimization of the TCCT representation at both 600 and 900 MHz (1)H converged to the same parameterization. The higher magnetic field yielded systematically larger deviations in the back-prediction of the autocorrelation functions for the mobile amides, indicating little added benefit from multiple field measurements in analyzing amides that lack slower (∼ms) exchange line-broadening effects. Experimental (15)N relaxation data efficiently distinguished among the different force fields with regard to their prediction of ubiquitin backbone conformational dynamics in the ps–ns time frame. While the earlier AMBER 99SB and CHARMM27 force fields underestimate the scale of backbone dynamics, which occur in this time frame, AMBER 14SB provided the most consistent predictions for the well-averaged highly mobile C-terminal residues of ubiquitin. |
format | Online Article Text |
id | pubmed-9009080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-90090802022-04-14 Molecular Dynamics-Assisted Optimization of Protein NMR Relaxation Analysis Anderson, Janet S. Hernández, Griselda LeMaster, David M. J Chem Theory Comput [Image: see text] NMR relaxation analysis of the mobile residues in globular proteins is sensitive to the form of the experimentally fitted internal autocorrelation function, which is used to represent that motion. Different order parameter representations can precisely fit the same set of (15)N R(1), R(2), and heteronuclear NOE measurements while yielding significantly divergent predictions of the underlying autocorrelation functions, indicating the insufficiency of these experimental relaxation data for assessing which order parameter representation provides the most physically realistic predictions. Molecular dynamics simulations offer an unparalleled capability for discriminating among different order parameter representations to assess which representation can most accurately model a wide range of physically realistic autocorrelation functions. Six currently utilized AMBER and CHARMM force fields were applied to calculate autocorrelation functions for the backbone H–N bond vectors of ubiquitin as an operational test set. An optimized time constant-constrained triexponential (TCCT) representation was shown to markedly outperform the widely used (S(f)(2),τ(s),S(2)) extended Lipari–Szabo representation and the more closely related (S(f)(2),S(H)(2), S(N)(2)) Larmor frequency-selective representation. Optimization of the TCCT representation at both 600 and 900 MHz (1)H converged to the same parameterization. The higher magnetic field yielded systematically larger deviations in the back-prediction of the autocorrelation functions for the mobile amides, indicating little added benefit from multiple field measurements in analyzing amides that lack slower (∼ms) exchange line-broadening effects. Experimental (15)N relaxation data efficiently distinguished among the different force fields with regard to their prediction of ubiquitin backbone conformational dynamics in the ps–ns time frame. While the earlier AMBER 99SB and CHARMM27 force fields underestimate the scale of backbone dynamics, which occur in this time frame, AMBER 14SB provided the most consistent predictions for the well-averaged highly mobile C-terminal residues of ubiquitin. American Chemical Society 2022-03-04 2022-04-12 /pmc/articles/PMC9009080/ /pubmed/35245056 http://dx.doi.org/10.1021/acs.jctc.1c01165 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Anderson, Janet S. Hernández, Griselda LeMaster, David M. Molecular Dynamics-Assisted Optimization of Protein NMR Relaxation Analysis |
title | Molecular Dynamics-Assisted Optimization of Protein
NMR Relaxation Analysis |
title_full | Molecular Dynamics-Assisted Optimization of Protein
NMR Relaxation Analysis |
title_fullStr | Molecular Dynamics-Assisted Optimization of Protein
NMR Relaxation Analysis |
title_full_unstemmed | Molecular Dynamics-Assisted Optimization of Protein
NMR Relaxation Analysis |
title_short | Molecular Dynamics-Assisted Optimization of Protein
NMR Relaxation Analysis |
title_sort | molecular dynamics-assisted optimization of protein
nmr relaxation analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009080/ https://www.ncbi.nlm.nih.gov/pubmed/35245056 http://dx.doi.org/10.1021/acs.jctc.1c01165 |
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