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Research Articles

Identification of bioactive compounds from Glycyrrhiza glabra as possible inhibitor of SARS-CoV-2 spike glycoprotein and non-structural protein-15: a pharmacoinformatics study

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Pages 4686-4700 | Received 15 May 2020, Accepted 03 Jun 2020, Published online: 18 Jun 2020
 

Abstract

At present, the world is facing a pandemic named as COVID-19, caused by SARS-CoV-2. Traditional Chinese medicine has recommended the use of liquorice (Glycyrrhiza species) in the treatment of infections caused by SARS-CoV-2. Therefore, the present investigation was carried out to identify the active molecule from the liquorice against different protein targets of COVID-19 using an in-silico approach. The molecular docking simulation study of 20 compounds along with two standard antiviral drugs (Lopinavir and Rivabirin) was carried out with the help of Autodock vina software using two protein targets from COVID-19 i.e. spike glycoprotein (PDB ID: 6VSB) and Non-structural Protein-15 (Nsp15) endoribonuclease (PDB ID: 6W01). From the observed binding energy and the binding interactions, glyasperin A showed high affinity towards Nsp15 endoribonuclease with uridine specificity, while glycyrrhizic acid was found to be best suited for the binding pocket of spike glycoprotein and also prohibited the entry of the virus into the host cell. Further, the dynamic behavior of the best-docked molecules inside the spike glycoprotein and Nsp15 endoribonuclease were explored through all-atoms molecular dynamics (MD) simulation study. Several parameters from the MD simulation have substantiated the stability of protein-ligand stability. The binding free energy of both glyasperin A and glycyrrhizic acid was calculated from the entire MD simulation trajectory through the MM-PBSA approach and found to high binding affinity towards the respective protein receptor cavity. Thus, glyasperin A and glycyrrhizic acid could be considered as the best molecule from liquorice, which could find useful against COVID-19.

Communicated by Ramaswamy H. Sarma

Acknowledgements

The CHPC (www.chpc.ac.za) is thankfully acknowledged for computational resources and tools.

Disclosure statement

The author declares that there are no known conflicts of interest with regards to this work.

Funding

This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia through the Fast-track Research Funding Program.

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