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A new ensemble coevolution system for detecting HIV-1 protein coevolution
BACKGROUND: A key challenge in the field of HIV-1 protein evolution is the identification of coevolving amino acids at the molecular level. In the past decades, many sequence-based methods have been designed to detect position-specific coevolution within and between different proteins. However, an e...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332441/ https://www.ncbi.nlm.nih.gov/pubmed/25564011 http://dx.doi.org/10.1186/s13062-014-0031-8 |
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author | Li, Guangdi Theys, Kristof Verheyen, Jens Pineda-Peña, Andrea-Clemencia Khouri, Ricardo Piampongsant, Supinya Eusébio, Mónica Ramon, Jan Vandamme, Anne-Mieke |
author_facet | Li, Guangdi Theys, Kristof Verheyen, Jens Pineda-Peña, Andrea-Clemencia Khouri, Ricardo Piampongsant, Supinya Eusébio, Mónica Ramon, Jan Vandamme, Anne-Mieke |
author_sort | Li, Guangdi |
collection | PubMed |
description | BACKGROUND: A key challenge in the field of HIV-1 protein evolution is the identification of coevolving amino acids at the molecular level. In the past decades, many sequence-based methods have been designed to detect position-specific coevolution within and between different proteins. However, an ensemble coevolution system that integrates different methods to improve the detection of HIV-1 protein coevolution has not been developed. RESULTS: We integrated 27 sequence-based prediction methods published between 2004 and 2013 into an ensemble coevolution system. This system allowed combinations of different sequence-based methods for coevolution predictions. Using HIV-1 protein structures and experimental data, we evaluated the performance of individual and combined sequence-based methods in the prediction of HIV-1 intra- and inter-protein coevolution. We showed that sequence-based methods clustered according to their methodology, and a combination of four methods outperformed any of the 27 individual methods. This four-method combination estimated that HIV-1 intra-protein coevolving positions were mainly located in functional domains and physically contacted with each other in the protein tertiary structures. In the analysis of HIV-1 inter-protein coevolving positions between Gag and protease, protease drug resistance positions near the active site mostly coevolved with Gag cleavage positions (V128, S373-T375, A431, F448-P453) and Gag C-terminal positions (S489-Q500) under selective pressure of protease inhibitors. CONCLUSIONS: This study presents a new ensemble coevolution system which detects position-specific coevolution using combinations of 27 different sequence-based methods. Our findings highlight key coevolving residues within HIV-1 structural proteins and between Gag and protease, shedding light on HIV-1 intra- and inter-protein coevolution. REVIEWERS: This article was reviewed by Dr. Zoltán Gáspári. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13062-014-0031-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4332441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43324412015-02-19 A new ensemble coevolution system for detecting HIV-1 protein coevolution Li, Guangdi Theys, Kristof Verheyen, Jens Pineda-Peña, Andrea-Clemencia Khouri, Ricardo Piampongsant, Supinya Eusébio, Mónica Ramon, Jan Vandamme, Anne-Mieke Biol Direct Research BACKGROUND: A key challenge in the field of HIV-1 protein evolution is the identification of coevolving amino acids at the molecular level. In the past decades, many sequence-based methods have been designed to detect position-specific coevolution within and between different proteins. However, an ensemble coevolution system that integrates different methods to improve the detection of HIV-1 protein coevolution has not been developed. RESULTS: We integrated 27 sequence-based prediction methods published between 2004 and 2013 into an ensemble coevolution system. This system allowed combinations of different sequence-based methods for coevolution predictions. Using HIV-1 protein structures and experimental data, we evaluated the performance of individual and combined sequence-based methods in the prediction of HIV-1 intra- and inter-protein coevolution. We showed that sequence-based methods clustered according to their methodology, and a combination of four methods outperformed any of the 27 individual methods. This four-method combination estimated that HIV-1 intra-protein coevolving positions were mainly located in functional domains and physically contacted with each other in the protein tertiary structures. In the analysis of HIV-1 inter-protein coevolving positions between Gag and protease, protease drug resistance positions near the active site mostly coevolved with Gag cleavage positions (V128, S373-T375, A431, F448-P453) and Gag C-terminal positions (S489-Q500) under selective pressure of protease inhibitors. CONCLUSIONS: This study presents a new ensemble coevolution system which detects position-specific coevolution using combinations of 27 different sequence-based methods. Our findings highlight key coevolving residues within HIV-1 structural proteins and between Gag and protease, shedding light on HIV-1 intra- and inter-protein coevolution. REVIEWERS: This article was reviewed by Dr. Zoltán Gáspári. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13062-014-0031-8) contains supplementary material, which is available to authorized users. BioMed Central 2015-01-07 /pmc/articles/PMC4332441/ /pubmed/25564011 http://dx.doi.org/10.1186/s13062-014-0031-8 Text en © Li et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 | Research Li, Guangdi Theys, Kristof Verheyen, Jens Pineda-Peña, Andrea-Clemencia Khouri, Ricardo Piampongsant, Supinya Eusébio, Mónica Ramon, Jan Vandamme, Anne-Mieke A new ensemble coevolution system for detecting HIV-1 protein coevolution |
title | A new ensemble coevolution system for detecting HIV-1 protein coevolution |
title_full | A new ensemble coevolution system for detecting HIV-1 protein coevolution |
title_fullStr | A new ensemble coevolution system for detecting HIV-1 protein coevolution |
title_full_unstemmed | A new ensemble coevolution system for detecting HIV-1 protein coevolution |
title_short | A new ensemble coevolution system for detecting HIV-1 protein coevolution |
title_sort | new ensemble coevolution system for detecting hiv-1 protein coevolution |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332441/ https://www.ncbi.nlm.nih.gov/pubmed/25564011 http://dx.doi.org/10.1186/s13062-014-0031-8 |
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