Predictor factors for non-invasive mechanical ventilation failure in severe COVID-19 patients in the intensive care unit: a single-center retrospective study.

BACKGROUND: During the COVID-19 pandemia, non-invasive mechanical ventilation (NIV) has been largely applied. Few data are available about predictors of NIV failure in critical COVID-19 patients admitted to ICU. The aim of this study is to analyze clinical and laboratory features able to predict non-invasive ventilation success in avoiding endotracheal intubation. METHODS: A retrospective observational study was performed in our COVID-19 ICU during a 6-month period. Demographic, clinical, laboratory, imaging, and outcome data were extracted from electronic and paper medical records and anonymously collected. RESULTS: Eighty-two severe COVID-19 patients were supported by NIV at ICU admission. The median PaO2/FiO2 ratio was 125 [98.5-177.7]. NIV failed in 44 cases (53%). Patients who experienced NIV failure had a higher Charlson Comorbidity Index (median value 4) compared to those who were dismissed without endotracheal intubation (median 2, p < 0.0001). At Cox regression analysis, the Charlson Comorbidity Index represented a predictive factor related to NIV failure. PaO2/FiO2, CPK, INR, and AT III at ICU admission showed a significant relationship with the outcome, when single variables were adjusted for the Charlson Comorbidity Index. CONCLUSION: The Charlson Comorbidity Index may be helpful to stratify patients' risk of NIV failure in a severe COVID-19 population; even if this study, retrospective design does not allow definitive conclusions.

Identification of a dual acting SARS-CoV-2 proteases inhibitor through in silico design and step-by-step biological characterization.

COVID-19 pandemic, starting from the latest 2019, and caused by SARS-CoV-2 pathogen, led to the hardest health-socio-economic disaster in the last century. Despite the tremendous scientific efforts, mainly focused on the development of vaccines, identification of potent and efficient anti-SARS-CoV-2 therapeutics still represents an unmet need. Remdesivir, an anti-Ebola drug selected from a repurposing campaign, is the only drug approved, so far, for the treatment of the infection. Nevertheless, WHO in later 2020 has recommended against its use in COVID-19. In the present paper, we describe a step-by-step in silico design of a small library of compounds as main protease (Mpro) inhibitors. All the molecules were screened by an enzymatic assay on Mpro and, then, cellular activity was evaluated using Vero cells viral infection model. The cellular screening disclosed compounds 29 and 34 as in-vitro SARS-CoV-2 replication inhibitors at non-toxic concentrations (0.32 < EC50 < 5.98 µM). To rationalize these results, additional in-vitro assays were performed, focusing on papain like protease (PLpro) and spike protein (SP) as potential targets for the synthesized molecules. This pharmacological workflow allowed the identification of compound 29, as a dual acting SARS-CoV-2 proteases inhibitor featuring micromolar inhibitory potency versus Mpro (IC50 = 1.72 µM) and submicromolar potency versus PLpro (IC50 = 0.67 µM), and of compound 34 as a selective SP inhibitor (IC50 = 3.26 µM).

Accelerating the repurposing of FDA-approved drugs against coronavirus disease-19 (COVID-19).

The recent release of the main protein structures belonging to SARS CoV-2, responsible for the coronavirus disease-19 (COVID-19), strongly pushed for identifying valuable drug treatments. With this aim, we show a repurposing study on FDA-approved drugs applying a new computational protocol and introducing a novel parameter called IVSratio. Starting with a virtual screening against three SARS CoV-2 targets (main protease, papain-like protease, spike protein), the top-ranked molecules were reassessed combining the Inverse Virtual Screening novel approach and MM-GBSA calculations. Applying this protocol, a list of drugs was identified against the three investigated targets. Also, the top-ranked selected compounds on each target (rutin vs. main protease, velpatasvir vs. papain-like protease, lomitapide vs. spike protein) were further tested with molecular dynamics simulations to confirm the promising binding modes, obtaining encouraging results such as high stability of the complex during the simulation and a good protein-ligand interaction network involving some important residues of each target. Moreover, the recent outcomes highlighting the inhibitory activity of quercetin, a natural compound strictly related to rutin, on the SARS-CoV-2 main protease, strengthened the applicability of the proposed workflow.