Drugs against SARS-CoV-2: What do we know about their mode of action?
Coralie ValleBaptiste MartinFranck TouretAshleigh ShannonBruno CanardJean-Claude GuillemotBruno CoutardEtienne DecrolyPublished in: Reviews in medical virology (2020)
The health emergency caused by the recent Covid-19 pandemic highlights the need to identify effective treatments against the virus causing this disease (SARS-CoV-2). The first clinical trials have been testing repurposed drugs that show promising anti-SARS-CoV-2 effects in cultured cells. Although more than 2400 clinical trials are already under way, the actual number of tested compounds is still limited to approximately 20, alone or in combination. In addition, knowledge on their mode of action (MoA) is currently insufficient. Their first results reveal some inconsistencies and contradictory results and suggest that cohort size and quality of the control arm are two key issues for obtaining rigorous and conclusive results. Moreover, the observed discrepancies might also result from differences in the clinical inclusion criteria, including the possibility of early treatment that may be essential for therapy efficacy in patients with Covid-19. Importantly, efforts should also be made to test new compounds with a documented MoA against SARS-CoV-2 in clinical trials. Successful treatment will probably be based on multitherapies with antiviral compounds that target different steps of the virus life cycle. Moreover, a multidisciplinary approach that combines artificial intelligence, compound docking, and robust in vitro and in vivo assays will accelerate the development of new antiviral molecules. Finally, large retrospective studies on hospitalized patients are needed to evaluate the different treatments with robust statistical tools and to identify the best treatment for each Covid-19 stage. This review describes different candidate antiviral strategies for Covid-19, by focusing on their mechanism of action.
Keyphrases
- sars cov
- clinical trial
- artificial intelligence
- respiratory syndrome coronavirus
- healthcare
- public health
- machine learning
- life cycle
- big data
- coronavirus disease
- induced apoptosis
- quality improvement
- randomized controlled trial
- deep learning
- molecular dynamics
- emergency department
- mental health
- phase ii
- cross sectional
- genome wide
- endothelial cells
- open label
- gene expression
- cell cycle arrest
- health information
- combination therapy
- cell death
- single cell
- endoplasmic reticulum stress
- small molecule
- stem cells
- replacement therapy