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Temperature dependence of NMR chemical shifts: Tracking and statistical analysis
Isotropic chemical shifts measured by solution nuclear magnetic resonance (NMR) spectroscopy offer extensive insights into protein structure and dynamics. Temperature dependences add a valuable dimension; notably, the temperature dependences of amide proton chemical shifts are valuable probes of hyd...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6933856/ https://www.ncbi.nlm.nih.gov/pubmed/31730280 http://dx.doi.org/10.1002/pro.3785 |
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author | Trainor, Kyle Palumbo, Jeffrey A. MacKenzie, Duncan W. S. Meiering, Elizabeth M. |
author_facet | Trainor, Kyle Palumbo, Jeffrey A. MacKenzie, Duncan W. S. Meiering, Elizabeth M. |
author_sort | Trainor, Kyle |
collection | PubMed |
description | Isotropic chemical shifts measured by solution nuclear magnetic resonance (NMR) spectroscopy offer extensive insights into protein structure and dynamics. Temperature dependences add a valuable dimension; notably, the temperature dependences of amide proton chemical shifts are valuable probes of hydrogen bonding, temperature‐dependent loss of structure, and exchange between distinct protein conformations. Accordingly, their uses include structural analysis of both folded and disordered proteins, and determination of the effects of mutations, binding, or solution conditions on protein energetics. Fundamentally, these temperature dependences result from changes in the local magnetic environments of nuclei, but correlations with global thermodynamic parameters measured via calorimetric methods have been observed. Although the temperature dependences of amide proton and nitrogen chemical shifts are often well approximated by a linear model, deviations from linearity are also observed and may be interpreted as evidence of fast exchange between distinct conformational states. Here, we describe computational methods, accessible via the Shift‐T web server, including an automated tracking algorithm that propagates initial (single temperature) (1)H—(15)N cross peak assignments to spectra collected over a range of temperatures. Amide proton and nitrogen temperature coefficients (slopes determined by fitting chemical shift vs. temperature data to a linear model) are subsequently calculated. Also included are methods for the detection of systematic, statistically significant deviation from linearity (curvature) in the temperature dependences of amide proton chemical shifts. The use and utility of these methods are illustrated by example, and the Shift‐T web server is freely available at http://meieringlab.uwaterloo.ca/shiftt. |
format | Online Article Text |
id | pubmed-6933856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69338562019-12-30 Temperature dependence of NMR chemical shifts: Tracking and statistical analysis Trainor, Kyle Palumbo, Jeffrey A. MacKenzie, Duncan W. S. Meiering, Elizabeth M. Protein Sci Tools for Protein Science Isotropic chemical shifts measured by solution nuclear magnetic resonance (NMR) spectroscopy offer extensive insights into protein structure and dynamics. Temperature dependences add a valuable dimension; notably, the temperature dependences of amide proton chemical shifts are valuable probes of hydrogen bonding, temperature‐dependent loss of structure, and exchange between distinct protein conformations. Accordingly, their uses include structural analysis of both folded and disordered proteins, and determination of the effects of mutations, binding, or solution conditions on protein energetics. Fundamentally, these temperature dependences result from changes in the local magnetic environments of nuclei, but correlations with global thermodynamic parameters measured via calorimetric methods have been observed. Although the temperature dependences of amide proton and nitrogen chemical shifts are often well approximated by a linear model, deviations from linearity are also observed and may be interpreted as evidence of fast exchange between distinct conformational states. Here, we describe computational methods, accessible via the Shift‐T web server, including an automated tracking algorithm that propagates initial (single temperature) (1)H—(15)N cross peak assignments to spectra collected over a range of temperatures. Amide proton and nitrogen temperature coefficients (slopes determined by fitting chemical shift vs. temperature data to a linear model) are subsequently calculated. Also included are methods for the detection of systematic, statistically significant deviation from linearity (curvature) in the temperature dependences of amide proton chemical shifts. The use and utility of these methods are illustrated by example, and the Shift‐T web server is freely available at http://meieringlab.uwaterloo.ca/shiftt. John Wiley & Sons, Inc. 2019-11-26 2020-01 /pmc/articles/PMC6933856/ /pubmed/31730280 http://dx.doi.org/10.1002/pro.3785 Text en © 2019 The Protein Society Open access. |
spellingShingle | Tools for Protein Science Trainor, Kyle Palumbo, Jeffrey A. MacKenzie, Duncan W. S. Meiering, Elizabeth M. Temperature dependence of NMR chemical shifts: Tracking and statistical analysis |
title | Temperature dependence of NMR chemical shifts: Tracking and statistical analysis |
title_full | Temperature dependence of NMR chemical shifts: Tracking and statistical analysis |
title_fullStr | Temperature dependence of NMR chemical shifts: Tracking and statistical analysis |
title_full_unstemmed | Temperature dependence of NMR chemical shifts: Tracking and statistical analysis |
title_short | Temperature dependence of NMR chemical shifts: Tracking and statistical analysis |
title_sort | temperature dependence of nmr chemical shifts: tracking and statistical analysis |
topic | Tools for Protein Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6933856/ https://www.ncbi.nlm.nih.gov/pubmed/31730280 http://dx.doi.org/10.1002/pro.3785 |
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