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Leri: A web-server for identifying protein functional networks from evolutionary couplings
Information on the co-evolution of amino acid pairs in a protein can be used for endeavors such as protein engineering, mutation design, and structure prediction. Here we report a method that captures significant determinants of proteins using estimated co-evolution information to identify networks...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239741/ https://www.ncbi.nlm.nih.gov/pubmed/34257835 http://dx.doi.org/10.1016/j.csbj.2021.06.002 |
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author | Cheung, Ngaam J. John Peter, Arun T. Kornmann, Benoit |
author_facet | Cheung, Ngaam J. John Peter, Arun T. Kornmann, Benoit |
author_sort | Cheung, Ngaam J. |
collection | PubMed |
description | Information on the co-evolution of amino acid pairs in a protein can be used for endeavors such as protein engineering, mutation design, and structure prediction. Here we report a method that captures significant determinants of proteins using estimated co-evolution information to identify networks of residues, termed ”residue communities”, relevant to protein function. On the benchmark dataset (67 proteins with both catalytic and allosteric residues), the Pearson’s correlation between the identified residues in the communities at functional sites is 0.53, and it is higher than 0.8 by taking account of conserved residues derived from the method. On the endoplasmic reticulum-mitochondria encounter structure complex, the results indicate three distinguishable residue communities that are relevant to functional roles in the protein family, suggesting that the residue communities could be general evolutionary signatures in proteins. Based on the method, we provide a webserver for the scientific community to explore the signatures in protein families, which establishes a powerful tool to analyze residue-level profiling for the discovery of functional sites and biological pathway identification. This web-server is freely available for non-commercial users at https://kornmann.bioch.ox.ac.uk/leri/services/ecs.html, neither login nor e-mail required. |
format | Online Article Text |
id | pubmed-8239741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-82397412021-07-12 Leri: A web-server for identifying protein functional networks from evolutionary couplings Cheung, Ngaam J. John Peter, Arun T. Kornmann, Benoit Comput Struct Biotechnol J Method Article Information on the co-evolution of amino acid pairs in a protein can be used for endeavors such as protein engineering, mutation design, and structure prediction. Here we report a method that captures significant determinants of proteins using estimated co-evolution information to identify networks of residues, termed ”residue communities”, relevant to protein function. On the benchmark dataset (67 proteins with both catalytic and allosteric residues), the Pearson’s correlation between the identified residues in the communities at functional sites is 0.53, and it is higher than 0.8 by taking account of conserved residues derived from the method. On the endoplasmic reticulum-mitochondria encounter structure complex, the results indicate three distinguishable residue communities that are relevant to functional roles in the protein family, suggesting that the residue communities could be general evolutionary signatures in proteins. Based on the method, we provide a webserver for the scientific community to explore the signatures in protein families, which establishes a powerful tool to analyze residue-level profiling for the discovery of functional sites and biological pathway identification. This web-server is freely available for non-commercial users at https://kornmann.bioch.ox.ac.uk/leri/services/ecs.html, neither login nor e-mail required. Research Network of Computational and Structural Biotechnology 2021-06-06 /pmc/articles/PMC8239741/ /pubmed/34257835 http://dx.doi.org/10.1016/j.csbj.2021.06.002 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Method Article Cheung, Ngaam J. John Peter, Arun T. Kornmann, Benoit Leri: A web-server for identifying protein functional networks from evolutionary couplings |
title | Leri: A web-server for identifying protein functional networks from evolutionary couplings |
title_full | Leri: A web-server for identifying protein functional networks from evolutionary couplings |
title_fullStr | Leri: A web-server for identifying protein functional networks from evolutionary couplings |
title_full_unstemmed | Leri: A web-server for identifying protein functional networks from evolutionary couplings |
title_short | Leri: A web-server for identifying protein functional networks from evolutionary couplings |
title_sort | leri: a web-server for identifying protein functional networks from evolutionary couplings |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239741/ https://www.ncbi.nlm.nih.gov/pubmed/34257835 http://dx.doi.org/10.1016/j.csbj.2021.06.002 |
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