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 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. © Li et al.

• Fecha de publicación: 2015
• Institución: Universidad del Rosario
• Repositorio: Repositorio EdocUR - U. Rosario
• Idioma: eng
• OAI Identifier: oai:repository.urosario.edu.co:10336/23525
• Acceso en línea: https://doi.org/10.1186/s13062-014-0031-8; https://repository.urosario.edu.co/handle/10336/23525
• Palabra clave: Human immunodeficiency virus 1; Gag protein; Human immunodeficiency virus proteinase; Protein binding; Viral protein; Area under the curve; Biology; Chemistry; Genetics; Human; Human immunodeficiency virus 1; Molecular evolution; Molecular model; Procedures; Protein database; Protein tertiary structure; Reproducibility; Statistical model; Area Under Curve; Computational Biology; HIV Protease; HIV-1; Humans; Protein Binding; Reproducibility of Results; Viral Proteins; Ensemble coevolution system; Gag; HIV-1; Protease; Protein coevolution; Sequence-based method; gag; Human Immunodeficiency Virus; Molecular; Molecular; Protein; Statistical; Tertiary; Databases; Evolution; Gag Gene Products; Gene Products; Models; Models; Protein Structure
• License: Abierto (Texto Completo)