Role of specialized pro-resolving lipid mediators and their receptors in virus infection: a promising therapeutic strategy for SARS-CoV-2 cytokine storm.
Chang Hoon LeePublished in: Archives of pharmacal research (2021)
Unexpected viral infections outbreaks, significantly affect human health, leading to increased mortality and life disruption. Among them is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged as a deadly pandemic, calling for intense research efforts on its pathogenicity mechanism and development of therapeutic strategies. In the SARS-CoV-2 cytokine storm, systemic inflammation has been associated with severe illness and mortality. Recent studies have demonstrated special pro-resolving lipids mediators (SPMs) lipoxins, resolvins, maresins, and protectins as potential therapeutic options for abnormal viral-triggered inflammation. Pro-resolving lipids mediators have shown great promise for the treatment of Herpes simplex virus, respiratory syncytial virus, human immunodeficiency virus, and hepatitis C virus. Based on this, studies are being conducted on their therapeutic effects in SARS-CoV-2 infection. In this review, we discussed SPMs and reviewed evidence from recent studies on SPMs as therapeutic options for viral infections, including SARS-CoV2. Based on our analysis of the previous study, we argue that SPMs are a potential treatment for SARS-CoV-2 infection and other viral infections. We expect further research on how SPMs modulate viral-triggered inflammation through G-protein-coupled receptors (GPCRs), and chemical stability and druggability of SPMs.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- human immunodeficiency virus
- hepatitis c virus
- human health
- risk assessment
- oxidative stress
- respiratory syncytial virus
- anti inflammatory
- herpes simplex virus
- cardiovascular events
- antiretroviral therapy
- case control
- risk factors
- palliative care
- cardiovascular disease
- coronary artery disease
- machine learning
- combination therapy
- big data