title: A new ensemble coevolution system for detecting HIV-1 protein coevolution.
abstract: 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.
authors.affiliation: KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium. liguangdi.research@gmail.com.
authors.forename: Guangdi
authors.initials: G
authors.lastname: Li
authors.affiliation: KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium. Kristof.Theys@rega.kuleuven.be.
authors.forename: Kristof
authors.initials: K
authors.lastname: Theys
authors.affiliation: Institute of Virology, University hospital, University Duisburg-Essen, Essen, Germany. jens.verheyen@uk-essen.de.
authors.forename: Jens
authors.initials: J
authors.lastname: Verheyen
authors.affiliation: KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium. andrea.pinedapena@rega.kuleuven.be.|Clinical and Molecular Infectious Disease Group, Faculty of Sciences and Mathematics, Universidad del Rosario, Bogotá, Colombia. andrea.pinedapena@rega.kuleuven.be.
authors.forename: Andrea-Clemencia
authors.initials: AC
authors.lastname: Pineda-Peña
authors.affiliation: KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium. ricardo_khouri@hotmail.com.
authors.forename: Ricardo
authors.initials: R
authors.lastname: Khouri
authors.affiliation: KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium. supinya.piampongsant@student.kuleuven.be.
authors.forename: Supinya
authors.initials: S
authors.lastname: Piampongsant
authors.affiliation: Centro de Malária e Outras Doenças Tropicais and Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal. monicasdeusebio@gmail.com.
authors.forename: Mónica
authors.initials: M
authors.lastname: Eusébio
authors.affiliation: Department of Computer Science, KU Leuven - University of Leuven, Leuven, Belgium. jan.ramon@cs.kuleuven.be.
authors.forename: Jan
authors.initials: J
authors.lastname: Ramon
authors.affiliation: KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium. Annemie.Vandamme@uzleuven.be.|Centro de Malária e Outras Doenças Tropicais and Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal. Annemie.Vandamme@uzleuven.be.
authors.forename: Anne-Mieke
authors.initials: AM
authors.lastname: Vandamme
mesh_terms: D019540:Area Under Curve; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D019143:Evolution, Molecular; D015683:Gene Products, gag / Q000737:chemistry; D016333:HIV Protease / Q000235:genetics*; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D008958:Models, Molecular; D015233:Models, Statistical; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D015203:Reproducibility of Results; D014764:Viral Proteins / Q000737:chemistry; D054301:gag Gene Products, Human Immunodeficiency Virus / Q000235:genetics*
chemical_list: D015683:Gene Products, gag; D014764:Viral Proteins; D054301:gag Gene Products, Human Immunodeficiency Virus; D016333:HIV Protease