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Computational evidence based perspective on the plausible repositioning of fluoroquinolones for COVID-19 treatment.
Yadav, Vikas.
  • Yadav V; Interdisciplinary Cluster for Applied Genoproteomics (GIGA), University of Liège, Sart-Tilman, 4000, Liège, Belgium.
Curr Comput Aided Drug Des ; 2022 Sep 09.
Article in English | MEDLINE | ID: covidwho-2022284
ABSTRACT
The coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a serious global healthcare crisis, so there is an emergence of identifying efficacious therapeutic options. In a setting where there is an unavailability of definitive medication along with the constant eruption of vaccine-related controversies, the drug-repositioning approach seems to be an ideal step for the management of COVID-19 patients. Fluoroquinolones (FQs) are commonly prescribed antibiotics for the treatment of genitourinary tract and upper respiratory tract infections, including severe community-acquired pneumonia. Research over the years has postulated multifaceted implications of FQs in various pathological conditions. Previously, it has been reported that few, but not all FQs, possess strong antiviral activity with an unknown mechanism of action. Herein, an interesting perspective is discussed on repositioning possibilities of FQs for the SARS-CoV-2 infections based on the recent in silico evidential support. Noteworthy, FQs possess immunomodulatory and bactericidal activity which could be valuable for patients dealing with COVID-19 related complications. Conclusively, the current perspective could pave the way to initiate pre-clinical testing of FQs against several strains of SARS-CoV-2.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal subject: Pharmacology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: 1573409918666220909094645

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal subject: Pharmacology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: 1573409918666220909094645