Molecular screening of antimalarial, antiviral, anti-inflammatory and HIV protease inhibitors against spike glycoprotein of coronavirus

Abstract

Coronavirus outbreak in December 2019 (COVID-19) is an emerging viral disease that poses major menace to Humans and it's a crucial need to find the possible treatment strategies. Spike protein (S2), a envelop glycoprotein aids viral entry into the host cells that corresponds to immunogenic ACE2 receptor binding and represents a potential antiviral drug target. Several drugs such as antimalarial, antibiotic, anti-inflammatory and HIV-protease inhibitors are currently undergoing treatment as clinical studies to test the efficacy and safety of COVID-19. Some promising results have been observed with the patients and also with high mortality rate. Hence, there is a need to screen the best CoV inhibitors using insilico analysis. The Molecular methodologies applied in the present study are, Molecular docking, virtual screening, drug-like and ADMET prediction helps to target CoV inhibitors. The results were screened based on docking score, H-bonds, and amino acid interactions. The results shows HIV-protease inhibitors such as cobicistat (-8.3kcal/mol), Darunavir (-7.4kcal/mol), Lopinavir (-9.1kcal/mol) and Ritonavir (-8.0 kcal/mol), anti-inflammatory drugs such as Baricitinib (-5.8kcal/mol), Ruxolitinib (-6.5kcal/mol), Thalidomide (-6.5kcal/mol), antibiotic drugs such as Erythromycin(-9.0kcal/mol) and Spiramycin (-8.5kcal/mol) molecules have good affinity towards spike protein compared to antimalarial drugs Chloroquine (-6.2kcal/mol), Hydroxychloroquine (-5.2kcal/mol) and Artemisinin (-6.8kcal/mol) have poor affinity to spike protein. The insilico pharmacological evaluation shows that these molecules exhibit good affinity of drug-like and ADMET properties. Hence, we propose that HIVprotease, anti-inflammatory and antibiotic inhibitors are the potential lead drug molecules for spike protein and preclinical studies needed to confirm the promising therapeutic ability against COVID-19.

Keywords: Anti-inflammatory drugs; Antiviral drugs; COVID-19; Coronavirus; Homology modeling; Molecular docking.

Graphical abstract

Fig. 1

Spike protein structure predicted using I-TASSER, the red label represents (1) Spike receptor binding domain (330–583) which corresponds to immunogenic ACE2 receptor binding domain. (2) Coronavirus S2 glycoprotein (662–1270) is translated as a large polypeptide that is subsequently cleaved to S1 and S2 domains from. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2

Antimalarial inhibitors docking with spike protein using AutoDock Vina. The 2D structures of protein-ligand interactions are visualized using DS visualize and the interactions are predicted based on binding energy (kcal/mol) and hydrogen bonds.

Fig. 3

HIV-Protease inhibitors docking with spike protein using AutoDock Vina. The 2D structures of protein-ligand interactions are visualized using DS visualize and the interactions are predicted based on binding energy (kcal/mol) and hydrogen bonds.

Fig. 4

Anti-inflammatory inhibitors docking with spike protein using AutoDock Vina. The 2D structures of protein-ligand interactions are visualized using DS visualize and the interactions are predicted based on binding energy (kcal/mol) and hydrogen bonds.

Fig. 5

Antimicrobial inhibitors docking with spike protein using AutoDock Vina. The 2D structures of protein-ligand interactions are visualized using DS visualize and the interactions are predicted based on binding energy (kcal/mol) and hydrogen bonds.