Abstract:
Developing therapeutics for infectious diseases requires understanding the
main processes driving host and pathogen through which molecular
interactions influence cellular functions. The outcome of those infectious
diseases, including influenza A (IAV) depends greatly on how the host
responds to the virus and how the virus manipulates the host, which is
facilitated by protein-protein functional inter-actions and analyzing infection
associated genes at the systems level, which may enable us to characterize
specific molecular mechanisms which allow the virus of influenza A strains
H1N1 and H3N2 to persist and survive inside the host. The system level
analysis based on experimental and computational approaches was used to
predict human protein-protein functional inter-actions. This human proteinprotein functional interaction is a graph consisting of nodes which are
proteins, and links joining them. Using this graph, we analyse topological
properties of this human protein-protein functional interactions, identify
candidate proteins using centrality measures and a map set of IAV infection
associated proteins to elucidate genes related to IAV infection and identify
essential dense sub-graphs underlying IAV infection outcome. We performed
functional closeness and enrichment analyses to identify statistically and
biologically significant processes and pathways implicated in IAV infection.
These IAV infection associated proteins have shown to be relevant for further
research towards new drugs and vaccine development. This study enhances
our understanding on the interplay between influenza A and its host and may
contribute to the process of designing novel drugs.
