Network Controllability-Based Prioritization of Candidates for SARS-CoV-2 Drug Repositioning

8 proteins are prioritized as possible drug repositioning targets for SARS-CoV-2 where two, PVR and SCARB1, are previously unexplored. Known compounds targeting these genes are suggested for viral inhibition study. Prioritized proteins in agreement with previous analysis and viral inhibition studies verify the ability of network controllability to predict biologically relevant candidates using small amounts of virus-specific data.

A Dual Controllability Analysis of Influenza Virus-Host Protein-Protein Interaction Networks for Antiviral Drug Target Discovery

Identified 24 proteins as holding regulatory roles specific to the infected cell by measures of topology, controllability, and functional role. This research aims to increase the efficiency of antiviral drug target discovery using existing protein-protein interaction data and network analysis methods.

Strain-Specific Immune Response to Influenza Virus Infection

Developed a mechanism-based mathematical model to compare the immune dynamics invoked by deadly H5N1 and moderately pathogenic H1N1 influenza viruses to aid in clinical understanding of infection severity. Results suggest that the kinetics of the immune response, specifically those related to the virus as well as those involved in interferon production, differ between H1N1 and H5N1 infections.

Network-Guided Discovery of Influenza Virus Replication Host Factors

Host factors of influenza infection are identified using a novel virus-host protein network. Interaction cascades between host proteins that directly interact with viral proteins and host factors that are important to influenza replication are enriched for signaling and immune processes. Novel host factors are validated with an siRNA screen, demonstrating that integrated virus-host networks are useful in the identification of antiviral drug target candidates.

A systems and treatment perspective of models of influenza virus-induced host responses

A review of the current state of mathematical models of influenza-induced host responses. Analysis shows that the structure of current models does not allow for significant responses to increased interferon concentrations, suggesting that the current library of available published models of influenza infection does not adequately represent the complex interactions of the virus, interferon, and other aspects of the immune response.