Computer-Aided Prediction and Identification of Phytochemicals as Potential Drug Candidates against MERS-CoV

Abstract

The Middle East respiratory syndrome coronavirus (MERS-CoV) is the major leading cause of respiratory infections listed as blueprint of diseases by the World Health Organization. It needs immediate research in the developing countries including Saudi Arabia, South Korea, and China. Still no vaccine has been developed against MERS-CoV; therefore, an effective strategy is required to overcome the devastating outcomes of MERS. Computer-aided drug design is the effective method to find out potency of natural phytochemicals as inhibitors of MERS-CoV. In the current study, the molecular docking approach was employed to target receptor binding of CoV. A total of 150 phytochemicals were docked as ligands in this study and found that some of the phytochemicals successfully inhibited the catalytic triad of MERS-CoV. The docking results brought novel scaffolds which showed strong ligand interactions with Arg178, Arg339, His311, His230, Lys146, and Arg139 residues of the viral domains. From the top ten ligands found in this study (i.e., rosavin, betaxanthin, quercetin, citromitin, pluviatilol, digitogenin, ichangin, methyl deacetylnomilinate, kobusinol A, and cyclocalamin) based on best $S$ -score values, two phytochemicals (i.e., pluviatilol and kobusinol A) exhibited all drug-likeness properties following the pharmacokinetic parameters which are important for bioavailability of drug-like compounds, and hence, they can serve as potential drug candidates to stop the viral load. The study revealed that these phytochemicals would serve as strong potential inhibitors and a starting point for the development of vaccines and proteases against MERS-CoV. Further, in vivo studies are needed to confirm the efficacy of these potential drug candidates.