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relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data
Nuclear magnetic resonance (NMR) is a powerful tool for observing the motion of biomolecules at the atomic level. One technique, the analysis of relaxation dispersion phenomenon, is highly suited for studying the kinetics and thermodynamics of biological processes. Built on top of the relax computat...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103588/ https://www.ncbi.nlm.nih.gov/pubmed/24764461 http://dx.doi.org/10.1093/bioinformatics/btu166 |
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author | Morin, Sébastien Linnet, Troels E. Lescanne, Mathilde Schanda, Paul Thompson, Gary S. Tollinger, Martin Teilum, Kaare Gagné, Stéphane Marion, Dominique Griesinger, Christian Blackledge, Martin d’Auvergne, Edward J. |
author_facet | Morin, Sébastien Linnet, Troels E. Lescanne, Mathilde Schanda, Paul Thompson, Gary S. Tollinger, Martin Teilum, Kaare Gagné, Stéphane Marion, Dominique Griesinger, Christian Blackledge, Martin d’Auvergne, Edward J. |
author_sort | Morin, Sébastien |
collection | PubMed |
description | Nuclear magnetic resonance (NMR) is a powerful tool for observing the motion of biomolecules at the atomic level. One technique, the analysis of relaxation dispersion phenomenon, is highly suited for studying the kinetics and thermodynamics of biological processes. Built on top of the relax computational environment for NMR dynamics is a new dispersion analysis designed to be comprehensive, accurate and easy-to-use. The software supports more models, both numeric and analytic, than current solutions. An automated protocol, available for scripting and driving the graphical user interface (GUI), is designed to simplify the analysis of dispersion data for NMR spectroscopists. Decreases in optimization time are granted by parallelization for running on computer clusters and by skipping an initial grid search by using parameters from one solution as the starting point for another —using analytic model results for the numeric models, taking advantage of model nesting, and using averaged non-clustered results for the clustered analysis. Availability and implementation: The software relax is written in Python with C modules and is released under the GPLv3+ license. Source code and precompiled binaries for all major operating systems are available from http://www.nmr-relax.com. Contact: edward@nmr-relax.com |
format | Online Article Text |
id | pubmed-4103588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41035882014-07-18 relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data Morin, Sébastien Linnet, Troels E. Lescanne, Mathilde Schanda, Paul Thompson, Gary S. Tollinger, Martin Teilum, Kaare Gagné, Stéphane Marion, Dominique Griesinger, Christian Blackledge, Martin d’Auvergne, Edward J. Bioinformatics Applications Notes Nuclear magnetic resonance (NMR) is a powerful tool for observing the motion of biomolecules at the atomic level. One technique, the analysis of relaxation dispersion phenomenon, is highly suited for studying the kinetics and thermodynamics of biological processes. Built on top of the relax computational environment for NMR dynamics is a new dispersion analysis designed to be comprehensive, accurate and easy-to-use. The software supports more models, both numeric and analytic, than current solutions. An automated protocol, available for scripting and driving the graphical user interface (GUI), is designed to simplify the analysis of dispersion data for NMR spectroscopists. Decreases in optimization time are granted by parallelization for running on computer clusters and by skipping an initial grid search by using parameters from one solution as the starting point for another —using analytic model results for the numeric models, taking advantage of model nesting, and using averaged non-clustered results for the clustered analysis. Availability and implementation: The software relax is written in Python with C modules and is released under the GPLv3+ license. Source code and precompiled binaries for all major operating systems are available from http://www.nmr-relax.com. Contact: edward@nmr-relax.com Oxford University Press 2014-08-01 2014-04-09 /pmc/articles/PMC4103588/ /pubmed/24764461 http://dx.doi.org/10.1093/bioinformatics/btu166 Text en © The Author 2014. Published by Oxford University Press http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Morin, Sébastien Linnet, Troels E. Lescanne, Mathilde Schanda, Paul Thompson, Gary S. Tollinger, Martin Teilum, Kaare Gagné, Stéphane Marion, Dominique Griesinger, Christian Blackledge, Martin d’Auvergne, Edward J. relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data |
title | relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data |
title_full | relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data |
title_fullStr | relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data |
title_full_unstemmed | relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data |
title_short | relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data |
title_sort | relax: the analysis of biomolecular kinetics and thermodynamics using nmr relaxation dispersion data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103588/ https://www.ncbi.nlm.nih.gov/pubmed/24764461 http://dx.doi.org/10.1093/bioinformatics/btu166 |
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