Identification of Entry Factors Involved in Hepatitis C Virus Infection Based on Host-Mimicking Short Linear Motifs.
In: PLoS Computational Biology, Jg. 13 (2017-01-27), Heft 1, S. 1-24
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Zugriff:
Host factors that facilitate viral entry into cells can, in principle, be identified from a virus-host protein interaction network, but for most viruses information for such a network is limited. To help fill this void, we developed a bioinformatics approach and applied it to hepatitis C virus (HCV) infection, which is a current concern for global health. Using this approach, we identified short linear sequence motifs, conserved in the envelope proteins of HCV (E1/E2), that potentially can bind human proteins present on the surface of hepatocytes so as to construct an HCV (envelope)-host protein interaction network. Gene Ontology functional and KEGG pathway analyses showed that the identified host proteins are enriched in cell entry and carcinogenesis functionalities. The validity of our results is supported by much published experimental data. Our general approach should be useful when developing antiviral agents, particularly those that target virus-host interactions. [ABSTRACT FROM AUTHOR]
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Titel: |
Identification of Entry Factors Involved in Hepatitis C Virus Infection Based on Host-Mimicking Short Linear Motifs.
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Autor/in / Beteiligte Person: | Chiang, Austin W. T. ; Wu, Walt Y. L. ; Wang, Ting ; Hwang, Ming-Jing |
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Zeitschrift: | PLoS Computational Biology, Jg. 13 (2017-01-27), Heft 1, S. 1-24 |
Veröffentlichung: | 2017 |
Medientyp: | academicJournal |
ISSN: | 1553-734X (print) |
DOI: | 10.1371/journal.pcbi.1005368 |
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