Abstract
With the world threatened by a second surge in the number of Coronavirus cases, there is an urgent need for the development of effective treatment for the novel coronavirus (COVID-19). Recently, global attention has turned to preliminary reports on the promising anti-COVID-19 effect of histamine H2-receptor antagonists (H2RAs), most especially Famotidine. Therefore, this study was designed to exploit a possible molecular basis for the efficacy of H2RAs against coronavirus. Molecular docking was performed between four H2RAs, Cimetidine, Famotidine, Nizatidine, Ranitidine, and three non-structural proteins viz. NSP3, NSP7/8 complex, and NSP9. Thereafter, a 100 ns molecular dynamics simulation was carried out with the most outstanding ligands to determine the stability. Thereafter, Famotidine and Cimetidine were subjected to gene target prediction analysis using HitPickV2 and eXpression2Kinases server to determine the possible network of genes associated with their anti-COVID activities. Results obtained from molecular docking showed the superiority of Famotidine and Cimetidine compared to other H2RAs with a higher binding affinity to all selected targets. Molecular dynamic simulation and MMPBSA results revealed that Famotidine as well as Cimetidine bind to non-structural proteins more efficiently with high stability over 100 ns. Results obtained suggest that Famotidine and Cimetidine could be a viable option to treat COVID-19 with a mechanism of action that involves the inhibition of viral replication through the inhibition of non-structural proteins. Therefore, Famotidineand Cimetidine qualify for further study as a potential treatment for COVID-19.
Graphical Abstract
Communicated by Ramaswamy H. Sarma
Acknowledgements
The authors are thankful to Kumaun University, Nainital for providing high-speed internet facilities. The authors also acknowledge Rashtriya Uchchattar Shiksha Abhiyan (RUSA), Ministry of Human Resource Development, Government of India to provide Computational infrastructure for the establishment of Bioinformatics Centre in Kumaun University, S.S.J Campus, Almora.
Disclosure statement
The authors declare that there is no conflict of interest regarding the publication of this paper.