Boesenbergia rotunda-Derived Phytochemicals as Potent Inhibitors of SARS-CoV-2 Papain-Like Protease (PLpro): Insights From Molecular Docking and Dynamic Simulation.

Abstract

The papain-like protease (PLpro) of SARS-CoV-2 plays fundamental roles in its replication, and its mechanistic inhibition can impede the virus's replication and infection. Most Plpro inhibitors identified thus far are chemically synthesized and subject to numerous restrictions regarding stability and adverse side effects. Nevertheless, the inhibitors of those compounds can be replaced with natural, selective PLpro inhibitors that are highly stable and have minimal adverse effects. Since ancient times, extracts of Boesenbergia rotunda (L.) Mansf. have been recognized for their antiviral and other properties. Consequently, the objective of the investigation was to investigate the inhibitory activity of B. rotunda extract compounds against the virus, with the intention of inhibiting PLpro's signaling function in its replicative pathway, as a result, preventing viral infections. Molecular docking was initially suggested to evaluate the level of binding affinity among 57 natural compounds identified from B. rotunda to the desired protein. The results of this computational analysis have additionally been compared against molnupiravir, which has been addressed experimentally for its interacting efficiency towards the PLpro receptor protein of SARS-CoV-2 lately. This comparison indicates that the proposed dietary compounds have a significantly noticeable interaction efficiency regarding binding efficiency and other energetic contributions. Furthermore, the structure of PLpro was significantly influenced by compounds in MD-simulation experiments that were validated through some standard analyses, such as RMSF (root mean square fluctuation), RMSD (root mean square deviation), solvent accessible surface area, radius of gyration, MolSA, and PSA. The most promising three phytochemicals that could be established as an antiviral curative option against SARS-CoV-2 infection have been identified through computational approaches: rubranine, boesenbergin B, and panduratin A. The results of our computational investigation indicate that our proposed medications require clinical experimentation; consequently, they may be a superior treatment against SARS-CoV-2 viral infection.