Qatar medical journal
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Qatar medical journal · Jan 2021
Identification of potential natural inhibitors of the receptor-binding domain of the SARS-CoV-2 spike protein using a computational docking approach.
Background: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only zoonotic-origin CoV to reach the pandemic stage, to which neither an effective vaccine nor a specific therapy is available. The spike glycoprotein harbors the receptor-binding domain (RBD) that mediates the virus's entry to host cells. This study aimed to identify novel inhibitors that target the spike protein's RBD domain through computational screening of chemical and natural compounds. ⋯ Additionally, the study reports a list of 25 natural compounds that showed effective binding with an improved average binding affinity of - 51.46 kcal/mol. Conclusions: Using computational screening, we identified potential SARS-CoV-2 S glycoprotein inhibitors that bind to the RBD region. Using structure-based design and combination-based drug therapy, the identified molecules could be used to generate anti-SARS-CoV-2 drug candidates.
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The presence of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and its associated disease, COVID-19 has had an enormous impact on the operations of the emergency department (ED), particularly the triage area. The aim of the study was to derive and validate a prediction rule that would be applicable to Qatar's adult ED population to predict COVID-19-positive patients. ⋯ The Q-PREDICT is a simple scoring system based on information readily collected from patients at the front desk of the ED and helps to predict COVID-19 status at triage. The scoring system performed well in the internal and external validation on datasets obtained from the state of Qatar.