I’m happy to say our paper in Scientific Reports on identifying functionally important domains and residues in viral genomes using indepent site rate esimations with RevBayes is finally out. Details below.


Abstract:

Alphaherpesviruses are a subfamily of herpesviruses that include the significant human pathogens herpes simplex viruses (HSV) and varicella zoster virus (VZV). Glycoprotein K (gK), conserved in all alphaherpesviruses, is a multi-membrane spanning virion glycoprotein essential for virus entry into neuronal axons, virion assembly, and pathogenesis. Despite these critical functions, little is known about which gK domains and residues are most important for maintaining these functions across all alphaherpesviruses. Herein, we employed phylogenetic and structural analyses including the use of a novel model for evolutionary rate variation across residues to predict conserved gK functional domains. We found marked heterogeneity in the evolutionary rate at the level of both individual residues and domains, presumably as a result of varying selective constraints. To clarify the potential role of conserved sequence features, we predicted the structures of several gK orthologs. Congruent with our phylogenetic analysis, slowly evolving residues were identified at potentially structurally significant positions across domains. We found that using a quantitative measure of amino acid rate variation combined with molecular modeling we were able to identify amino acids predicted to be critical for gK protein structure/function. This analysis yields targets for the design of anti-herpesvirus therapeutic strategies across all alphaherpesvirus species that would be absent from more traditional analyses of conservation.

Keywords: Herpes virus, Bayesian inference, phylogenetics, molecular evolution, revbayes

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Citation:

Rider, P.J.F., Coghill, L.M., Naderi, M. et al. Identification and Visualization of Functionally Important Domains and Residues in Herpes Simplex Virus Glycoprotein K(gK) Using a Combination of Phylogenetics and Protein Modeling. Sci Rep 9, 14625 (2019) doi:10.1038/s41598-019-50490-9

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