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A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins

Because of the limited effectiveness of prevailing phylogenetic methods when applied to highly divergent protein sequences, the phylogenetic analysis problem remains challenging. Here, we propose a sequence-based evolutionary distance algorithm termed sequence distance (SD), which innovatively incor...

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Autores principales: Cao, Wei, Wu, Lu-Yun, Xia, Xia-Yu, Chen, Xiang, Wang, Zhi-Xin, Pan, Xian-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662474/
https://www.ncbi.nlm.nih.gov/pubmed/37985846
http://dx.doi.org/10.1038/s41598-023-47496-9
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author Cao, Wei
Wu, Lu-Yun
Xia, Xia-Yu
Chen, Xiang
Wang, Zhi-Xin
Pan, Xian-Ming
author_facet Cao, Wei
Wu, Lu-Yun
Xia, Xia-Yu
Chen, Xiang
Wang, Zhi-Xin
Pan, Xian-Ming
author_sort Cao, Wei
collection PubMed
description Because of the limited effectiveness of prevailing phylogenetic methods when applied to highly divergent protein sequences, the phylogenetic analysis problem remains challenging. Here, we propose a sequence-based evolutionary distance algorithm termed sequence distance (SD), which innovatively incorporates site-to-site correlation within protein sequences into the distance estimation. In protein superfamilies, SD can effectively distinguish evolutionary relationships both within and between protein families, producing phylogenetic trees that closely align with those based on structural information, even with sequence identity less than 20%. SD is highly correlated with the similarity of the protein structure, and can calculate evolutionary distances for thousands of protein pairs within seconds using a single CPU, which is significantly faster than most protein structure prediction methods that demand high computational resources and long run times. The development of SD will significantly advance phylogenetics, providing researchers with a more accurate and reliable tool for exploring evolutionary relationships.
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spelling pubmed-106624742023-11-20 A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins Cao, Wei Wu, Lu-Yun Xia, Xia-Yu Chen, Xiang Wang, Zhi-Xin Pan, Xian-Ming Sci Rep Article Because of the limited effectiveness of prevailing phylogenetic methods when applied to highly divergent protein sequences, the phylogenetic analysis problem remains challenging. Here, we propose a sequence-based evolutionary distance algorithm termed sequence distance (SD), which innovatively incorporates site-to-site correlation within protein sequences into the distance estimation. In protein superfamilies, SD can effectively distinguish evolutionary relationships both within and between protein families, producing phylogenetic trees that closely align with those based on structural information, even with sequence identity less than 20%. SD is highly correlated with the similarity of the protein structure, and can calculate evolutionary distances for thousands of protein pairs within seconds using a single CPU, which is significantly faster than most protein structure prediction methods that demand high computational resources and long run times. The development of SD will significantly advance phylogenetics, providing researchers with a more accurate and reliable tool for exploring evolutionary relationships. Nature Publishing Group UK 2023-11-20 /pmc/articles/PMC10662474/ /pubmed/37985846 http://dx.doi.org/10.1038/s41598-023-47496-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Cao, Wei
Wu, Lu-Yun
Xia, Xia-Yu
Chen, Xiang
Wang, Zhi-Xin
Pan, Xian-Ming
A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins
title A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins
title_full A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins
title_fullStr A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins
title_full_unstemmed A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins
title_short A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins
title_sort sequence-based evolutionary distance method for phylogenetic analysis of highly divergent proteins
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662474/
https://www.ncbi.nlm.nih.gov/pubmed/37985846
http://dx.doi.org/10.1038/s41598-023-47496-9
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