Identification of potential host proteins for influenza A virus based on topological and biological characteristics by proteome-wide network approach

Abstract

A proteome-wide network approach was performed to characterize significant patterns of influenza A virus (IAV)-human interactions, and to further identify potentially valuable targets for prophylactic and therapeutic interventions. Topological analysis demonstrated a strong tendency for IAV to interplay with highly connected and central proteins located in sparsely connected sub-networks. Additionally, functional analysis based on biological process revealed a number of functional groups overrepresented for IAV interactions, in which regulation of cell death and apoptosis, and phosphorus metabolic process is the most highly enriched. In order to investigate whether these topological and biological features are significant enough to distinguish IAV targets from human proteome, a discrimination model was constructed based on these features using support vector machine coupled with genetic algorithm. The average result of overall prediction accuracy is 71.04% by leave-one-out across validation test. The optimized classifier was then applied to 9706 human proteins. As a result, 1418 novel genes were identified from human interactome, some of which were experimentally validated by others' works to be important for IAV infection. The findings presented in this study might be important in discovering new drug targets for therapeutic treatments as well as revealing topological features and functional properties specific for viral infection.