Please use this identifier to cite or link to this item:
https://www.arca.fiocruz.br/handle/icict/20560
A NEW ENSEMBLE COEVOLUTION SYSTEM FOR DETECTING HIV-1 PROTEIN COEVOLUTION
Author
Affilliation
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
University Duisburg-Essen. University hospital. Institute of Virology. Essen, Germany
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium / Universidad del Rosario. Faculty of Sciences and Mathematics. Clinical and Molecular Infectious Disease Group. Bogotá, Colombia
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
Universidade Nova de Lisboa. Instituto de Higiene e Medicina Tropical. Centro de Malária e Outras Doenças Tropicais and Unidade de Microbiologia. Lisboa, Portugal
KU Leuven - University of Leuven. Department of Computer Science. Leuven, Belgium
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium / Universidade Nova de Lisboa. Instituto de Higiene e Medicina Tropical. Centro de Malária e Outras Doenças Tropicais and Unidade de Microbiologia. Lisboa, Portugal
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
University Duisburg-Essen. University hospital. Institute of Virology. Essen, Germany
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium / Universidad del Rosario. Faculty of Sciences and Mathematics. Clinical and Molecular Infectious Disease Group. Bogotá, Colombia
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium
Universidade Nova de Lisboa. Instituto de Higiene e Medicina Tropical. Centro de Malária e Outras Doenças Tropicais and Unidade de Microbiologia. Lisboa, Portugal
KU Leuven - University of Leuven. Department of Computer Science. Leuven, Belgium
KU Leuven - University of Leuven. Rega Institute for Medical Research. Clinical and Epidemiological Virology. Department of Microbiology and Immunology. Leuven, Belgium / Universidade Nova de Lisboa. Instituto de Higiene e Medicina Tropical. Centro de Malária e Outras Doenças Tropicais and Unidade de Microbiologia. Lisboa, Portugal
Abstract
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.
Share