A new ensemble coevolution system for detecting HIV-1 protein coevolution

dc.creatorLi, Guangdi
dc.creatorTheys, Kristof
dc.creatorVerheyen, Jens
dc.creatorPeña, Andrea Clemencia Pineda
dc.creatorCunha, Antonio Ricardo Khouri
dc.creatorPiampongsant, Supinya
dc.creatorEusébio, Mónica
dc.creatorRamon, Jan
dc.creatorVandamme, Anne Mieke
dc.date2017-08-09T13:09:56Z
dc.date2017-08-09T13:09:56Z
dc.date2015
dc.date.accessioned2023-09-26T22:00:36Z
dc.date.available2023-09-26T22:00:36Z
dc.identifierLI, G. et al. A new ensemble coevolution system for detecting HIV-1 protein coevolution. Biology Direct, v. 10, p. 1, 2015.
dc.identifier1745-6150
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/20560
dc.identifier10.1186/s13062-014-0031-8
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8874356
dc.descriptionKhouri, Antonio Ricardo “Documento produzido em parceria ou por autor vinculado à Fiocruz, mas não consta à informação no documento”.
dc.descriptionFonds voor Wetenschappelijk Onderzoek – Flanders (FWO) [PDO/11 to K.T., G.0692.14]; the European Community’s Seventh Framework Programme (FP7/2007-2013) under the project “Collaborative HIV and Anti-HIV Drug Resistance Network (CHAIN)” [223131].
dc.descriptionA 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.
dc.formatapplication/pdf
dc.languageeng
dc.publisherBioMed Central
dc.rightsopen access
dc.subjectHIV-1
dc.subjectProteínas
dc.subjectProtease
dc.subjectMétodos
dc.subjectHumanos
dc.subjectHIV-1
dc.subjectProtein coevolution
dc.subjectGag
dc.subjectProtease
dc.subjectEnsemble coevolution system
dc.subjectSequence-based method
dc.titleA new ensemble coevolution system for detecting HIV-1 protein coevolution
dc.typeArticle


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