Targeting SARS-CoV-2 receptors as a means for reducing infectivity and improving antiviral and immune response: an algorithm-based method for overcoming resistance to antiviral agents.
Ram GelmanAreej BayatraAsa KesslerAsaf SchwartzYaron IlanPublished in: Emerging microbes & infections (2020)
The ongoing severe acute respiratory syndrome pandemic caused by the novel coronavirus 2 (SARS-CoV-2) is associated with high morbidity and mortality rates, and it has created a pressing global need for effective antiviral therapies against it. COVID-19 disease pathogenesis is characterized by an initial virus-mediated phase, followed by inappropriate hyperactivation of the immune system leading to organ damage. Targeting of the SARS-CoV-2 viral receptors is being explored as a therapeutic option for these patients. In this paper, we summarize several potential receptors associated with the infectivity of SARS-CoV-2 and discuss their association with the immune-mediated inflammatory response. The potential for the development of resistance towards antiviral drugs is also presented. An algorithm-based platform to improve the efficacy of and overcome resistance to viral receptor blockers through the introduction of personalized variability is described. This method is designed to ensure sustained antiviral effectiveness when using SARS-CoV-2 receptor blockers.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- inflammatory response
- immune response
- machine learning
- end stage renal disease
- newly diagnosed
- ejection fraction
- deep learning
- systematic review
- coronavirus disease
- oxidative stress
- case report
- climate change
- risk assessment
- angiotensin ii
- binding protein
- patient reported outcomes