Abstract
A year after the initial outbreak, the COVID-19 pandemic caused by SARS-CoV-2 virus remains a serious threat to global health, while current treatment options are insufficient to bring major improvements. The aim of this study is to identify repurposable drug candidates with a potential to reverse transcriptomic alterations in the host cells infected by SARS-CoV-2. We have developed a rational computational pipeline to filter publicly available transcriptomic datasets of SARS-CoV-2-infected biosamples based on their responsiveness to the virus, to generate a list of relevant differentially expressed genes, and to identify drug candidates for repurposing using LINCS connectivity map. Pathway enrichment analysis was performed to place the results into biological context. We identified 37 structurally heterogeneous drug candidates and revealed several biological processes as druggable pathways. These pathways include metabolic and biosynthetic processes, cellular developmental processes, immune response and signaling pathways, with steroid metabolic process being targeted by half of the drug candidates. The pipeline developed in this study integrates biological knowledge with rational study design and can be adapted for future more comprehensive studies. Our findings support further investigations of some drugs currently in clinical trials, such as itraconazole and imatinib, and suggest 31 previously unexplored drugs as treatment options for COVID-19.
Subject
Drug Discovery,Pharmaceutical Science,Molecular Medicine
Reference74 articles.
1. SARS-CoV-2 pathophysiology and its clinical implications: An integrative overview of the pharmacotherapeutic management of COVID-19
2. Clinical Characteristics of Coronavirus Disease 2019 in China
3. Listings of WHO’s Response to COVID-19https://www.who.int/news/item/29-06-2020-covidtimeline
4. Center for Systems Science and Engineering at Johns Hopkins University Interactive Real-Time Web-Based COVID-19 Dashboardhttps://coronavirus.jhu.edu/map.html
5. Coronavirus Update (Live): 78,475,152 Cases and 1726,535 Deaths from COVID-19 Virus Pandemic—Worldometerhttps://www.worldometers.info/coronavirus/
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