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Title: A new ensemble coevolution system for detecting HIV-1 protein coevolution
Authors: Li, Guangdi
Theys, Kristof
Verheyen, Jens
Pineda-Peña, Andrea-Clemencia
Khouri, Ricardo
Piampongsant, Supinya
Eusébio, Mónica
Ramon, Jan
Vandamme, Anne-Mieke # ×
Issue Date: Jan-2015
Publisher: BioMed Central
Series Title: Biology Direct vol:10 pages:1-20
Article number: 1
Abstract: BackgroundA 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.ResultsWe 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.ConclusionsThis 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.ReviewersThis article was reviewed by Dr. Zoltán Gáspári.
URI: 
ISSN: 1745-6150
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Laboratory of Clinical and Epidemiological Virology (Rega Institute)
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Informatics Section
× corresponding author
# (joint) last author

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Li2014-ECS-provisional.pdfOA Accepted 3633KbAdobe PDFView/Open
2015258.pdfOA article Published 2570KbAdobe PDFView/Open

 


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