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Research Articles

Discovery of potential SARS-CoV 3CL protease inhibitors from approved antiviral drugs using: virtual screening, molecular docking, pharmacophore mapping evaluation and dynamics simulation

, , , &
Pages 12574-12591 | Received 09 Feb 2021, Accepted 23 Aug 2021, Published online: 20 Sep 2021
 

Abstract

The spread of corona-virus disease 2019 (COVID-19) has been faster than any other corona-viruses that have succeeded in crossing the animal-human barrier. This disease, caused by the severe acute respiratory syndrome corona-virus 2 (SARS-CoV-2/2019-nCoV) posing a serious threat to global public health and local economies. There are three responsible for this disease; SARS-CoV-2, SARS-CoV and MERS-CoV. Whereas our goal is to test the affinity for a new class of compounds obtained from a hybridization of Chloroquine, Amodiaquine and Mefloquine with three targets SARS-CoV-2, SARS-CoV and MERS-CoV, in order to find new compounds as new inhibitors against Covid-19. In this work, we first used: the molecular docking/dynamics methods and ADME properties to study interaction and affinity between eight new compounds against three targets involved in the Covid-19. The results of the docking simulations and dynamics revealed that inhibitor of the malaria (Ligand 87) has an affinity to interact with SARS-CoV-2, SARS-CoV and MERS-CoV targets and they can be good inhibitors for treatment of Covid-19. Moreover, they give best affinity compared to the Remdesivir and Chloroquine and other clinical tests. The Pharmacokinetics was justified by means of lipophilicity and high coefficient of skin permeability. The in silico evaluation of ADME and drug-likeness revealed that L87 has higher absorption in the intestines with good bioavailability. However, an additional in vitro and/or in vivo experimental study should make it possible to verify the theoretical results obtained in silico.

Communicated by Ramaswamy H. Sarma

Acknowledgements

Authors thank the Algerian Ministry of Higher Education and Scientific Research for the support under the PRFU project (approval No. B00L01UN130120190009). The authors thank director of Laboratory—LASNABIO Pr Said GHALEM for his financial support and ensure that there is no conflict of interest regarding this paper.

Disclosure statement

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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