Virtual screening and molecular dynamics simulation study of abyssomicins as potential inhibitors of COVID‐19 virus main protease and spike protein

Abstract

The lack of any effective cure for the infectious COVID-19 disease has created a sense of urgency and motivated the search for effective antiviral drugs. Abyssomicins are actinomyces-derived spirotetronates polyketides antibiotics known for their promising antibacterial, antitumor, and antiviral activities. In this study, computational approaches were used to investigate the binding mechanism and the inhibitory ability of 38 abyssomicins against the main protease (M^pro) and the spike protein receptor-binding domain (RBD) of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The results identified abyssomicins C, J, W, atrop-O-benzyl abyssomicin C, and atrop-O-benzyl desmethyl abyssomicin C as the most potential inhibitors of M^pro and RBD with binding energy ranges between −8.1 and −9.9 kcal mol⁻¹; and between −6.9 and −8.2 kcal mol⁻¹, respectively. Further analyses of physicochemical properties and drug-likeness suggested that all selected active abyssomicins, with the exception of abyssomicin J, obeyed Lipinski’s rule of five. The stability of protein–ligand complexes was confirmed by performing molecular dynamics simulation for 100 ns and evaluating parameters such as such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), total number of contacts, and secondary structure. Prime/MM-GBSA (Molecular Mechanics-General Born Surface Area) and principal component analysis (PCA) analyses also confirmed the stable nature of protein–ligand complexes. Overall, the results showed that the studied abyssomicins have significant interactions with the selected protein targets; therefore, they were deemed viable candidates for further in vitro and in vivo evaluation.

Communicated by Ramaswamy H. Sarma

Keywords:

• Abyssomicins
• SARS-CoV-2
• 3CL Mpro
• spike RBD
• ADMET
• virtual screening
• molecular dynamics

Acknowledgments

This work was funded by the Deanship of Scientific Research at Princess Nourah Bint Abdulrahman University, through the Research Groups Program Grant no. (RGP-1440-0014)(2).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was funded by the Deanship of Scientific Research at Princess Nourah Bint Abdulrahman University, through the Research Groups Program Grant no. (RGP-1440-0014)(2).