Losartan Inhibits SARS-CoV-2 Replication in Vitro.

PURPOSE: SARS-CoV-2 infection is associated with substantial mortality and high morbidity. This study tested the effect of angiotensin II type I receptor blocker, losartan, on SARS-CoV-2 replication and inhibition of the papain-like protease of the virus. METHODS: The dose-dependent inhibitory effect of losartan, in concentrations from 1µM to 100µM as determined by quantitative cell analysis combining fluorescence microscopy, image processing, and cellular measurements (Cellomics analysis) on SARS-CoV-2 replication was investigated in Vero E6 cells. The impact of losartan on deubiquitination and deISGylation of SARS-CoV-2 papain-like protease (PLpro) were also evaluated.  Results: Losartan reduced PLpro cleavage of tetraUbiquitin to diUbiquitin.  It was less effective in inhibiting PLpro's cleavage of ISG15-AMC than Ubiquitin-AMC.  To determine if losartan inhibited SARS-CoV-2 replication, losartan treatment of SARS-CoV-2 infected Vero E6 was examined. Losartan treatment one hour prior to SARS-CoV-2 infection reduced levels of SARS-CoV-2 nuclear protein, an indicator of virus replication, by 80% and treatment one-hour post-infection decreased viral replication by 70%. CONCLUSION: Losartan was not an effective inhibitor of deubiquitinase or deISGylase activity of the PLpro but affected the SARS-CoV-2 replication of Vero E6 cells in vitro.  As losartan has a favorable safety profile and is currently available it has features necessary for efficacious drug repurposing and treatment of COVID-19.

A combination of clinical balance measures and FRAX® to improve identification of high-risk fallers.

BACKGROUND: The FRAX® algorithm quantifies a patient's 10-year probability of a hip or major osteoporotic fracture without taking an individual's balance into account. Balance measures assess the functional ability of an individual and the FRAX® algorithm is a model that integrates the individual patients clinical risk factors [not balance] and bone mineral density. Thus, clinical balance measures capture aspects that the FRAX® algorithm does not, and vice versa. It is therefore possible that combining FRAX® and clinical balance measures can improve the identification of patients at high fall risk and thereby high fracture risk. Our study aim was to explore whether there is an association between clinical balance measures and fracture prediction obtained from FRAX®. METHOD: A cross-sectional study design was used where post hoc was performed on a dataset of 82 participants (54 to 89 years of age, mean age 71.4, 77 female), with a fall-related wrist-fracture between 2008 and 2012. Balance was measured by tandem stance, standing one leg, walking in the figure of eight, walking heel to toe on a line, walking as fast as possible for 30 m and five times sit to stand balance measures [tandem stance and standing one leg measured first with open and then with closed eyes] and each one analyzed for bivariate relations with the 10-year probability values for hip and major osteoporotic fractures as calculated by FRAX® using Spearman's rank correlation test. RESULTS: Individuals with high FRAX® values had poor outcome in balance measures; however the significance level of the correlation differed between tests. Standing one leg eyes closed had strongest correlation to FRAX® (0.610 p = < 0.01) and Five times sit to stand was the only test that did not correlate with FRAX® (0.013). CONCLUSION: This study showed that there is an association between clinical balance measures and FRAX®. Hence, the use of clinical balance measures and FRAX® in combination, might improve the identification of individuals with high risk of falls and thereby following fractures. Results enable healthcare providers to optimize treatment and prevention of fall-related fractures. TRIAL REGISTRATION: The study has been registered in Clinical Trials.gov, registration number NCT00988572 .

S Protein, ACE2 and Host Cell Proteases in SARS-CoV-2 Cell Entry and Infectivity; Is Soluble ACE2 a Two Blade Sword? A Narrative Review.

Since the spread of the deadly virus SARS-CoV-2 in late 2019, researchers have restlessly sought to unravel how the virus enters the host cells. Some proteins on each side of the interaction between the virus and the host cells are involved as the major contributors to this process: (1) the nano-machine spike protein on behalf of the virus, (2) angiotensin converting enzyme II, the mono-carboxypeptidase and the key component of renin angiotensin system on behalf of the host cell, (3) some host proteases and proteins exploited by SARS-CoV-2. In this review, the complex process of SARS-CoV-2 entrance into the host cells with the contribution of the involved host proteins as well as the sequential conformational changes in the spike protein tending to increase the probability of complexification of the latter with angiotensin converting enzyme II, the receptor of the virus on the host cells, are discussed. Moreover, the release of the catalytic ectodomain of angiotensin converting enzyme II as its soluble form in the extracellular space and its positive or negative impact on the infectivity of the virus are considered.