Abstract
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.
Highlights
The conventional approach to countering viral infections has been to develop drugs that target viral genetic material or proteins
By exploring the concept that short linear peptide motifs involved in human protein-protein interactions may be mimicked by viruses to hijack certain host cellular processes and thereby assist viral infection/survival, we developed a bioinformatics strategy to computationally identify entry factors of hepatitis C virus (HCV) infection, which is a worldwide health problem
Analysis of cellular functions and biochemical pathways indicated that the human proteins we identified usually play a role in cell entry and/or carcinogenesis, and results of the analysis are generally supported by experimental studies on HCV infection, including the ~80% (15 of 19) prediction rate of known HCV hepatocyte entry factors
Summary
The conventional approach to countering viral infections has been to develop drugs that target viral genetic material or proteins. Two major roadblocks to this strategy exist: 1) the limited number of druggable viral proteins owing to small viral genomes, and 2) drug resistance that occurs on a relatively short time scale owing to substantial viral genomic mutation rates. To circumvent these problems, over the past decade antiviral drug development has shifted from targeting viral proteins to host proteins that interact with components of the virus [1]. Cell-based genomic and proteomic assays that screen for host targets that interact with viral proteins have been reported [4,5,6]. Given the large amount of biological data that has been accumulated from high-throughput omics-type experiments, development of a bioinformatics-sleuthing strategy that identifies potential antiviral host targets to complement experimental screens should be of considerable merit
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