In the last months, many studies have clearly described several mechanisms of
SARS-CoV-2 infection at cell and tissue level, but the mechanisms of interaction between host and SARS-CoV-2, determining the grade of
COVID-19 severity, are still unknown. We provide a network analysis on
protein-
protein interactions (PPI) between viral and host
proteins to better identify host biological responses, induced by both whole
proteome of SARS-CoV-2 and specific
viral proteins. A host-virus interactome was inferred, applying an explorative algorithm (Random Walk with Restart, RWR) triggered by 28
proteins of SARS-CoV-2. The analysis of PPI allowed to estimate the distribution of SARS-CoV-2
proteins in the host cell. Interactome built around one single
viral protein allowed to define a different response, underlining as ORF8 and ORF3a modulated
cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, the network-based approach highlighted a possible direct action of ORF3a and NS7b to enhancing
Bradykinin Storm. This network-based representation of
SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific clinical outcomes. We identified possible host responses induced by specific
proteins of SARS-CoV-2, underlining the important role of specific
viral accessory proteins in pathogenic phenotypes of severe
COVID-19 patients.