Comparative Computational Study of SARS-CoV-2 Receptors Antagonists from Already Approved Drugs

02 April 2020, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

According to the World Health Organisation, on March 27, 2020, the number of confirmed cases of COVID-19 has already exceeded 509.000 with about of 23.000 deaths worldwide. Given this, the impact of COVID-19 on humanity cannot be overlooked, and basic research are urgently needed. This research aims to find antagonists already approved for another diseases, that may inhibit activity of the main protease (Mpro) of the SARS-CoV-2 virus, as well as modulate the ACE2 receptors, largely found in lung cells and reduce viral replication by inhibiting NSP12 RNA Polymerase. Docking molecular simulations were realized among a total of 28 ligands published in the literature against COVID-19. Docking studies were made with algorithm of AutoDock Vina 1.1.2 software. A structure-based virtual screening was performed with MTiOpenScreen. Subsequently, the physical-chemical and pharmacokinetic parameters were analyzed with SwissADME in order to select only the most promising ones. Finally, simulations of molecular dynamics with elapsed time of 4 nanoseconds (ns) were analysed in order to better understand the action of drugs to the detriment of the limitations of molecular docking. This work has shown that, in comparative terms, Simeprevir, Paritaprevir, Remdesivir and Baricitinib are currently among the most promising in remission of symptoms from the disease. Hydroxy-chloroquine, Chloroquine and Azithromicin were not showed effective, as monotherapies, against COVID-19 or lung cell receptors. Nevertheless, it has not been able to reach conclusive results due to the limitations of computational techniques that do not take into account numerous empirical parameters.

Keywords

SARS-CoV-2
ACE2 antagonists
Remdesivir
Molecular Docking
Molecular Dynamics
Virtual Screening
ADME

Supplementary materials

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virtual screening
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