A dual controllability analysis of influenza virus-host protein-protein interaction networks for antiviral drug target discovery

Ackerman, Emily E.; Alcorn, John F.; Hase, Takeshi; Shoemaker, Jason E.

Alternatively, network analysis methods applied to protein-protein interaction (PPI) data have been used to model cell-wide systemic changes associated with disease, changes in cell function, or cell fate [5] . This strategy provides a holistic understanding of system behavior by viewing proteins as interdependent states, regardless of specific interaction mechanisms, and allows for the exploration of cell level relationships. The field of network theory is well established. Several basic network metrics like degree (the number of interactions a protein is involved in) and betweenness (the importance of a protein to information flow through a network, or, how much of a bottleneck a protein is to system behavior) [6] are commonly used to describe the significance of network components in a wide range of applications [7] [8] [9] . These analyses have repeatedly revealed the importance of specific proteins within biological processes that cannot be found from traditional modeling approaches [10] [11] [12] [13] [14] . Disease networks have identified genes involved with cancer [15] [16] [17] [18] , demonstrated that the genes responsible for similar diseases are likely to interact with each other [19, 20] , and predicted novel drug targets [21, 22] .