Identification of terpenoids as potential inhibitors of SARS-CoV-2 (main protease) and spike (RBD) via computer-aided drug design

Abstract

The scientific community has been faced with a major challenge in the fight against the SARS-CoV-2 virus responsible for the COVID-19 pandemic, due to the lack of targeted antiviral drugs. To address this issue, we used an in silico approach to screen 23 natural compounds from the terpenoid class for their ability to target key SARS-CoV-2 therapeutic proteins. The results revealed that several compounds showed promising interactions with SARS-CoV-2 proteins, specifically the main protease and the spike receptor binding domain. The molecular docking analysis revealed the importance of certain residues, such as GLY143, SER144, CYS145 and GLU166, in the main protease of the SARS-CoV-2 protein, which play a crucial role in interactions with the ligand. In addition, our study highlighted the importance of interactions with residues GLY496, ARG403, SER494 and ARG393 of the spike receptor-binding domain within the SARS-CoV-2 protein. ADMET and drug similarity analyses were also performed, followed by molecular dynamics and MM-GBSA calculations, to identify potential drugs could be repurposed to combat COVID-19. Indeed, the results suggest that certain terpenoid compounds of plant origin have promising potential as therapeutic targets for SARS-CoV-2. However, additional experimental studies are required to confirm their efficacy as drugs against COVID-19.

Communicated by Ramaswamy H. Sarma

Keywords:

• Terpenoid family
• COVID-19
• molecular docking
• ADMET properties
• drug likeness
• molecular dynamics simulation
• MM-GBSA method

Acknowledgements

This research project, entitled "COV19Sim Morocco: An intelligent system for spatiotemporal prediction and control of the spread of the Coronavirus pandemic in Morocco," was supported by the Scientific and Technological Research Grant Program under the framework of "COVID-19" at the National Center for Scientific and Technical Research (CNRST) and Sidi Mohamed Ben Abdellah University (USMBA). The grant number is Cov/2020/54.

Disclosure statement

No potential conflict of interest was reported by the authors.

Université Sidi Mohamed Ben Abdellah;