biostudies-literatureUnknown9(3)Maria NIMinistero dell’Istruzione, dell’Università e della RicercaThe current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells <i>in silico</i> to <i>i)</i> determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and <i>ii)</i> utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.Heliyone14115https://www.ebi.ac.uk/biostudies/studies/S-EPMC9986505biostudies-literatureApplication of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing.PMC9986505Rapicavoli RVRxCOVEA FrameworkBischof EMaria NIAlaimo SMishra BPulvirenti AFerro AStasuzzo ABroek JACDuits AJfalseApplication of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing.The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells <i>in silico</i> to <i>i)</i> determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and <i>ii)</i> utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.2023-01-01T00:00:00Z2023 Mar2026-06-23T03:19:42.463Z2025-02-19T00:49:56.377ZS-EPMC99865053691187810.1016/j.heliyon.2023.e14115