In silico prediction of HIV-1-host molecular interactions and their directionality

Chai, H., Gu, Q. , Hughes, J. and Robertson, D. L. (2022) In silico prediction of HIV-1-host molecular interactions and their directionality. PLoS Computational Biology, 18(2), e1009720. (doi: 10.1371/journal.pcbi.1009720) (PMID:35134057) (PMCID:PMC8856524)

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Human immunodeficiency virus type 1 (HIV-1) continues to be a major cause of disease and premature death. As with all viruses, HIV-1 exploits a host cell to replicate. Improving our understanding of the molecular interactions between virus and human host proteins is crucial for a mechanistic understanding of virus biology, infection and host antiviral activities. This knowledge will potentially permit the identification of host molecules for targeting by drugs with antiviral properties. Here, we propose a data-driven approach for the analysis and prediction of the HIV-1 interacting proteins (VIPs) with a focus on the directionality of the interaction: host-dependency versus antiviral factors. Using support vector machine learning models and features encompassing genetic, proteomic and network properties, our results reveal some significant differences between the VIPs and non-HIV-1 interacting human proteins (non-VIPs). As assessed by comparison with the HIV-1 infection pathway data in the Reactome database (sensitivity > 90%, threshold = 0.5), we demonstrate these models have good generalization properties. We find that the ‘direction’ of the HIV-1-host molecular interactions is also predictable due to different characteristics of ‘forward’/pro-viral versus ‘backward’/pro-host proteins. Additionally, we infer the previously unknown direction of the interactions between HIV-1 and 1351 human host proteins. A web server for performing predictions is available at

Item Type:Articles
Additional Information:HC received finding from the China Scholarship Council under Grant 201706620069. JH, QG and DLR are funded by the Medical Research Council (MC_UU_1201412).
Glasgow Author(s) Enlighten ID:Robertson, Professor David and Hughes, Dr Joseph and Gu, Dr Quan and Chai, Haiting
Creator Roles:
Chai, H.Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review and editing
Gu, Q.Conceptualization, Supervision, Writing – review and editing
Hughes, J.Conceptualization, Supervision, Writing – review and editing
Robertson, D. L.Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review and editing
Authors: Chai, H., Gu, Q., Hughes, J., and Robertson, D. L.
College/School:College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research
Journal Name:PLoS Computational Biology
Publisher:Public Library of Science
ISSN (Online):1553-7358
Published Online:08 February 2022
Copyright Holders:Copyright © 2022 Chai et al.
First Published:First published in PLoS Computational Biology 18(2): e1009720
Publisher Policy:Reproduced under a Creative Commons License
Related URLs:

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172630014Cross-Cutting Programme – Viral Genomics and Bioinformatics (Programme 9)David RobertsonMedical Research Council (MRC)MC_UU_12014/12III - Centre for Virus Research