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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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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. |
format | Online Article Text |
id | pubmed-10009744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT jiakejue functionalproteindynamicsdirectlyfromsequences AT kilincmesih functionalproteindynamicsdirectlyfromsequences AT jerniganrobertl functionalproteindynamicsdirectlyfromsequences |