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How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations

We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ens...

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Detalles Bibliográficos
Autores principales: Kozak, Fanny, Kurzbach, Dennis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085671/
https://www.ncbi.nlm.nih.gov/pubmed/33995905
http://dx.doi.org/10.1016/j.csbj.2021.04.020
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author Kozak, Fanny
Kurzbach, Dennis
author_facet Kozak, Fanny
Kurzbach, Dennis
author_sort Kozak, Fanny
collection PubMed
description We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches.
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spelling pubmed-80856712021-05-13 How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations Kozak, Fanny Kurzbach, Dennis Comput Struct Biotechnol J Review We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches. Research Network of Computational and Structural Biotechnology 2021-04-21 /pmc/articles/PMC8085671/ /pubmed/33995905 http://dx.doi.org/10.1016/j.csbj.2021.04.020 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Kozak, Fanny
Kurzbach, Dennis
How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations
title How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations
title_full How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations
title_fullStr How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations
title_full_unstemmed How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations
title_short How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations
title_sort how to assess the structural dynamics of transcription factors by integrating sparse nmr and epr constraints with molecular dynamics simulations
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085671/
https://www.ncbi.nlm.nih.gov/pubmed/33995905
http://dx.doi.org/10.1016/j.csbj.2021.04.020
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