Network bioinformatics analysis provides insight into drug repurposing for COVID-19

Abstract

The COVID-19 disease caused by the SARS-CoV-2 virus is a health crisis worldwide. While developing novel drugs and vaccines is long, repurposing existing drugs against COVID-19 can yield treatments with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter clinical trials. In this study, we present a novel network-based drug repurposing platform to identify candidates for the treatment of COVID-19. At the time of the initial outbreak, knowledge about SARS-CoV-2 was lacking, but based on its similarity with other viruses, we sought to identify repurposing candidates to be tested rapidly at the clinical or preclinical levels. We first analyzed the genome sequence of SARS-CoV-2 and confirmed SARS as the closest virus by genome similarity, followed by MERS and other human coronaviruses. Using text mining and database searches, we obtained 34 COVID-19-related genes to seed the construction of a molecular network where our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules, and 78 drugs to repurpose. Based on clinical knowledge, we re-prioritized 30 potentially repurposable drugs against COVID-19 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide). Our work shows how in silico repurposing analyses can yield testable candidates to accelerate the response to novel disease outbreaks.

DrugWAS: Drug‐wide Association Studies for COVID‐19 Drug Repurposing

“…26,31 In a network-based bioinformatics analysis, pseudoephedrine was ranked as the best treatment candidate against COVID-19. 32 In contrast to our results, dextromethorphan, a common over-the-counter cough suppressant, was found to have proviral activity on animal cells in laboratory settings; however, further controlled clinical studies are needed to validate the results in humans. 33 Of note, other studies suggest that sigma-1 receptor agonists (which include drugs such as dextromethorphan and fluvoxamine) are essential inhibitors of cytokine production in COVID-19.…”

In silico studies of selected xanthophylls as potential candidates against SARS-CoV-2 targeting main protease (Mpro) and papain-like protease (PLpro)

“…In silico studies allow for fast prediction of activity and toxicity of natural compounds. SARS-CoV-2 computational analyses are important in searching for ac-tive drugs or designing vaccines [30][31][32][33][34]. The main protease (Mpro) and the papain-like protease (PLpro) can be targets for anti-SARS-CoV-2 drugs.…”

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

“…Also, closely knitted areas to CVD are genetics and microscopy. Genetics can be used to tackle the COVID-19 pandemic by tracking its origin (Cui et al, 2019;Phan, 2020;, finding reasons for the outbreak (Zhao and Yuan, 2020), and developing new vaccines (Álvarez-Machancoses et al, 2020;Hampel et al, 2020;Li et al, 2020c;Peng et al, 2020;Yan et al, 2020b;Yassine and Shah, 2020). Similarly, microscopy imaging is a very important part of AI-based COVID research for live-cell visualization to understand the behavior of SARS-CoV-2 (Lugagne et al, 2020;van Valen et al, 2016).…”