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Advanced bioinformatics rapidly identifies existing therapeutics for patients with COVID-19)


Abstract

The recent global pandemic has placed a high priority on identifying drugs to prevent or lessen clinical infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), caused by Coronavirus disease-2019 (COVID-19). Methods We applied two computational approaches to identify potential therapeutics. First, we sought to identify existing FDA approved drugs that could block coronaviruses from entering cells by binding to ACE2 or TMPRSS2 using a high-throughput AI-based binding affinity prediction platform. Second, we sought to identify FDA approved drugs that could attenuate the gene expression patterns induced by coronaviruses, using our Disease Cancelling Technology (DCT) platform. Results Top results for ACE2 binding iincluded several ACE inhibitors, a beta-lactam antibiotic, two antiviral agents (Fosamprenavir and Emricasan) and glutathione. The platform also assessed specificity for ACE2 over ACE1, important for avoiding counterregulatory effects. Further studies are needed to weigh the benefit of blocking virus entry against potential counterregulatory effects and possible protective effects of ACE2. However, the data herein suggest readily available drugs that warrant experimental evaluation to assess potential benefit. DCT was run on an animal model of SARS-CoV, and ranked compounds by their ability to induce gene expression signals that counteract disease-associated signals. Top hits included Vitamin E, ruxolitinib, and glutamine. Glutathione and its precursor glutamine were highly ranked by two independent methods, suggesting both warrant further investigation for potential benefit against SARS-CoV-2.





Glutamine is a top hit for cancelling out Coronavirus associated gene expression. a Gene expression changes associated with 2 days of MA15 infection expression in mouse pulmonary epithelial cells. X axis is log fold change, Y axis is -log10 p value. b Genes driving Glutamine to be a top hit. Each dot is a gene. X axis represents t-statistic of gene expression changes associated with coronavirus model, y axis represents t-statistics of gene expression changes associated with glutamine



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https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-020-02430-9


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https://translational-medicine.biomedcentral.com/track/pdf/10.1186/s12967-020-02430-9


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