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    Flexibility and intrinsic disorder are conserved features of hepatitis C virus E2 glycoprotein

    Stejskal, L. and Lees, William D. and Moss, David S. and Palor, M. and Bingham, R.J. and Shepherd, Adrian J. and Grove, J. (2020) Flexibility and intrinsic disorder are conserved features of hepatitis C virus E2 glycoprotein. PLOS Computational Biology 16 (2), e1007710. ISSN 1553-7358.

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    Abstract

    The glycoproteins of hepatitis C virus, E1E2, are unlike any other viral fusion machinery yet described, and are the current focus of immunogen design in HCV vaccine development; thus, making E1E2 both scientifically and medically important. We used pre-existing, but fragmentary, structures to model a complete ectodomain of the major glycoprotein E2 from three strains of HCV. We then performed molecular dynamic simulations to explore the conformational landscape of E2, revealing a number of important features. Despite high sequence divergence, and subtle differences in the models, E2 from different strains behave similarly, possessing a stable core flanked by highly flexible regions, some of which perform essential functions such as receptor binding. Comparison with sequence data suggest that this consistent behaviour is conferred by a network of conserved residues that act as hinge and anchor points throughout E2. The variable regions (HVR-1, HVR-2 and VR-3) exhibit particularly high flexibility, and bioinformatic analysis suggests that HVR-1 is a putative intrinsically disordered protein region. Dynamic cross-correlation analyses demonstrate intramolecular communication and suggest that specific regions, such as HVR-1, can exert influence throughout E2. To support our computational approach we performed small-angle X-ray scattering with purified E2 ectodomain; this data was consistent with our MD experiments, suggesting a compact globular core with peripheral flexible regions. This work captures the dynamic behaviour of E2 and has direct relevance to the interaction of HCV with cell-surface receptors and neutralising antibodies.

    Metadata

    Item Type: Article
    School: Birkbeck Schools and Departments > School of Science > Biological Sciences
    Research Centres and Institutes: Data Analytics, Birkbeck Institute for
    Depositing User: Administrator
    Date Deposited: 23 Mar 2020 16:14
    Last Modified: 30 Jun 2020 11:44
    URI: http://eprints.bbk.ac.uk/id/eprint/31440

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