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Automated selection of homologs to track the evolutionary history of proteins

BACKGROUND: The selection of distant homologs of a query protein under study is a usual and useful application of protein sequence databases. Such sets of homologs are often applied to investigate the function of a protein and the degree to which experimental results can be transferred from one orga...

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Autores principales: Mier, Pablo, Pérez-Pulido, Antonio J., Andrade-Navarro, Miguel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6245638/
https://www.ncbi.nlm.nih.gov/pubmed/30453878
http://dx.doi.org/10.1186/s12859-018-2457-y
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author Mier, Pablo
Pérez-Pulido, Antonio J.
Andrade-Navarro, Miguel A.
author_facet Mier, Pablo
Pérez-Pulido, Antonio J.
Andrade-Navarro, Miguel A.
author_sort Mier, Pablo
collection PubMed
description BACKGROUND: The selection of distant homologs of a query protein under study is a usual and useful application of protein sequence databases. Such sets of homologs are often applied to investigate the function of a protein and the degree to which experimental results can be transferred from one organism to another. In particular, a variety of databases facilitates static browsing for orthologs. However, these resources have a limited power when identifying orthologs between taxonomically distant species. In addition, in some situations, for a given query protein, it is advantageous to compare the sets of orthologs from different specific organisms: this recursive step-wise search might give an idea of the evolutionary path of the protein as a series of consecutive steps, for example gaining or losing domains. However, a step-wise orthology search is a time-consuming task if the number of steps is high. RESULTS: To illustrate a solution for this problem, we present the web tool ProteinPathTracker, which allows to track the evolutionary history of a query protein by locating homologs in selected proteomes along several evolutionary paths. Additional functionalities include locking a region of interest to follow its evolution in the discovered homologous sequences and the study of the protein function evolution by analysis of the annotations of the homologs. CONCLUSIONS: ProteinPathTracker is an easy-to-use web tool that automatises the practice of looking for selected homologs in distant species in a straightforward way for non-expert users. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2457-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-62456382018-11-26 Automated selection of homologs to track the evolutionary history of proteins Mier, Pablo Pérez-Pulido, Antonio J. Andrade-Navarro, Miguel A. BMC Bioinformatics Methodology Article BACKGROUND: The selection of distant homologs of a query protein under study is a usual and useful application of protein sequence databases. Such sets of homologs are often applied to investigate the function of a protein and the degree to which experimental results can be transferred from one organism to another. In particular, a variety of databases facilitates static browsing for orthologs. However, these resources have a limited power when identifying orthologs between taxonomically distant species. In addition, in some situations, for a given query protein, it is advantageous to compare the sets of orthologs from different specific organisms: this recursive step-wise search might give an idea of the evolutionary path of the protein as a series of consecutive steps, for example gaining or losing domains. However, a step-wise orthology search is a time-consuming task if the number of steps is high. RESULTS: To illustrate a solution for this problem, we present the web tool ProteinPathTracker, which allows to track the evolutionary history of a query protein by locating homologs in selected proteomes along several evolutionary paths. Additional functionalities include locking a region of interest to follow its evolution in the discovered homologous sequences and the study of the protein function evolution by analysis of the annotations of the homologs. CONCLUSIONS: ProteinPathTracker is an easy-to-use web tool that automatises the practice of looking for selected homologs in distant species in a straightforward way for non-expert users. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2457-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-19 /pmc/articles/PMC6245638/ /pubmed/30453878 http://dx.doi.org/10.1186/s12859-018-2457-y Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Mier, Pablo
Pérez-Pulido, Antonio J.
Andrade-Navarro, Miguel A.
Automated selection of homologs to track the evolutionary history of proteins
title Automated selection of homologs to track the evolutionary history of proteins
title_full Automated selection of homologs to track the evolutionary history of proteins
title_fullStr Automated selection of homologs to track the evolutionary history of proteins
title_full_unstemmed Automated selection of homologs to track the evolutionary history of proteins
title_short Automated selection of homologs to track the evolutionary history of proteins
title_sort automated selection of homologs to track the evolutionary history of proteins
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6245638/
https://www.ncbi.nlm.nih.gov/pubmed/30453878
http://dx.doi.org/10.1186/s12859-018-2457-y
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