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Functional Protein Dynamics Directly from Sequences

[Image: see text] The sequence correlations within a protein multiple sequence alignment are routinely being used to predict contacts within its structure, but here we point out that these data can also be used to predict a protein’s dynamics directly. The elastic network protein dynamics models rel...

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Autores principales: Jia, Kejue, Kilinc, Mesih, Jernigan, Robert L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009744/
https://www.ncbi.nlm.nih.gov/pubmed/36848294
http://dx.doi.org/10.1021/acs.jpcb.2c05766
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author Jia, Kejue
Kilinc, Mesih
Jernigan, Robert L.
author_facet Jia, Kejue
Kilinc, Mesih
Jernigan, Robert L.
author_sort Jia, Kejue
collection PubMed
description [Image: see text] The sequence correlations within a protein multiple sequence alignment are routinely being used to predict contacts within its structure, but here we point out that these data can also be used to predict a protein’s dynamics directly. The elastic network protein dynamics models rely directly upon the contacts, and the normal modes of motion are obtained from the decomposition of the inverse of the contact map. To make the direct connection between sequence and dynamics, it is necessary to apply coarse-graining to the structure at the level of one point per amino acid, which has often been done, and protein coarse-grained dynamics from elastic network models has been highly successful, particularly in representing the large-scale motions of proteins that usually relate closely to their functions. The interesting implication of this is that it is not necessary to know the structure itself to obtain its dynamics and instead to use the sequence information directly to obtain the dynamics.
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spelling pubmed-100097442023-03-14 Functional Protein Dynamics Directly from Sequences Jia, Kejue Kilinc, Mesih Jernigan, Robert L. J Phys Chem B [Image: see text] The sequence correlations within a protein multiple sequence alignment are routinely being used to predict contacts within its structure, but here we point out that these data can also be used to predict a protein’s dynamics directly. The elastic network protein dynamics models rely directly upon the contacts, and the normal modes of motion are obtained from the decomposition of the inverse of the contact map. To make the direct connection between sequence and dynamics, it is necessary to apply coarse-graining to the structure at the level of one point per amino acid, which has often been done, and protein coarse-grained dynamics from elastic network models has been highly successful, particularly in representing the large-scale motions of proteins that usually relate closely to their functions. The interesting implication of this is that it is not necessary to know the structure itself to obtain its dynamics and instead to use the sequence information directly to obtain the dynamics. American Chemical Society 2023-02-27 /pmc/articles/PMC10009744/ /pubmed/36848294 http://dx.doi.org/10.1021/acs.jpcb.2c05766 Text en © 2023 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 Jia, Kejue
Kilinc, Mesih
Jernigan, Robert L.
Functional Protein Dynamics Directly from Sequences
title Functional Protein Dynamics Directly from Sequences
title_full Functional Protein Dynamics Directly from Sequences
title_fullStr Functional Protein Dynamics Directly from Sequences
title_full_unstemmed Functional Protein Dynamics Directly from Sequences
title_short Functional Protein Dynamics Directly from Sequences
title_sort functional protein dynamics directly from sequences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009744/
https://www.ncbi.nlm.nih.gov/pubmed/36848294
http://dx.doi.org/10.1021/acs.jpcb.2c05766
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