Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19
The SARS-CoV-2 pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for COVID-19. Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a Network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently rerank the identified candidate drugs. We concluded to a highly informed integrated drug shortlist by combining structural diversity filtering along with experts’ curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src Tyrosine Kinase (bosutinib, dasatinib, cytarabine and saracatinib) which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflamatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action.
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Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
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Top 150 over- and under-expressed genes/proteins/metabolites – regulators
Top 150 over- and under-expressed genes/proteins/metabolites – regulators
GWAS analysis
GWAS analysis
Top 50 and Top 20 drug lists
Top 50 and Top 20 drug lists
Integration Scores
Integration Scores
Complete antiviral drugs from TaxAV and HPAV
Complete antiviral drugs from TaxAV and HPAV
Detailed table of the top 65 drugs
Detailed table of the top 65 drugs
Posted 18 Sep, 2020
Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19
Posted 18 Sep, 2020
The SARS-CoV-2 pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for COVID-19. Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a Network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently rerank the identified candidate drugs. We concluded to a highly informed integrated drug shortlist by combining structural diversity filtering along with experts’ curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src Tyrosine Kinase (bosutinib, dasatinib, cytarabine and saracatinib) which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflamatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action.
Figure 1
Figure 1
Figure 2
Figure 2
Figure 3
Figure 3
Figure 4
Figure 4
Figure 5
Figure 5
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.