Computational analysis of macrolides as SARS-CoV-2 main protease inhibitors: a pattern recognition study based on molecular topology and validated by molecular docking?

New Journal of Chemistry Pub Date: 2021-04-13 DOI: 10.1039/D0NJ05983H

Abstract

Since the outbreak of the current SARS-CoV-2 pandemic, much has been discussed about the effectiveness of treatments based on hydroxychloroquine combined with azithromycin or another macrolide. However, few articles have dealt with the possibility of using macrolides alone in treating the disease. In the present article, the authors’ hypothesis centers on the possibility that macrolides are effective against SARS-CoV-2 by inhibiting the virus protease. In support of this hypothesis, significant results are collected by following an in silico strategy based on a combination of molecular topology and docking. The results are in accordance with recent clinical data generated during the pandemic which indicate that macrolides are capable of significantly reducing the viral load, reinforcing the necessity of further clinical trials. Among the most effective macrolides identified by molecular topology are azithromycin, clarithromycin, lexithromycin, flurithromycin and neutramycin.

Graphical abstract: Computational analysis of macrolides as SARS-CoV-2 main protease inhibitors: a pattern recognition study based on molecular topology and validated by molecular docking
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