Repurposing naproxen as a potential nucleocapsid antagonist of beta-coronaviruses: targeting a conserved protein in the search for a broad-spectrum treatment option

Abstract

Ongoing mutations in the coronavirus family, especially beta-coronaviruses, raise new concerns about the possibility of new unexpected outbreaks. Therefore, it is crucial to explore new alternative treatments to reduce the impact of potential future strains until new vaccines can be developed. A promising approach to combat the virus is to target its conserved parts such as the nucleocapsid, especially via repurposing of existing drugs. The possibility of this approach is explored here to find a potential anti-nucleocapsid compound to target these viruses. 3D models of the N- and C-terminal domains (CTDs) of the nucleocapsid consensus sequence were constructed. Each domain was then screened against an FDA-approved drug database, and the most promising candidate was selected for further analysis. A 100 ns molecular dynamics (MD) simulation was conducted to analyze the final candidate in more detail. Naproxen was selected and found to interact with the N-terminal domain via conserved salt bridges and hydrogen bonds which are completely conserved among all Coronaviridae members. MD analysis also revealed that all relevant coordinates of naproxen with N terminal domain were kept during 100 ns of simulation time. This study also provides insights into the specific interaction of naproxen with conserved RNA binding pocket of the nucleocapsid that could interfere with the packaging of the viral genome into capsid and virus assembly. Additionally, the in-vitro binding assay demonstrated direct interaction between naproxen and recombinant nucleocapsid protein, further supporting the computational predictions.

Communicated by Ramaswamy H. Sarma

Keywords:

• Repurposing
• naproxen
• molecular docking
• molecular dynamics
• coronaviruses
• nucleocapsid

Acknowledgments

The authors gratefully acknowledge the valuable support of Mazandaran University of Medical Sciences in funding this research (Grant no: 7274). We also thank the University of Sistan and Baluchestan for providing the cloud computing facility that was used in this study.

Disclosure statement

The authors declare no competing interests.

Additional information

Funding

This work was supported by Mazandaran University of Medical Sciences.