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Abstract

Emergence and spread of corona virus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus, is considered a public health emergency threatening global health systems, as of June, 2020, It caused a cumulative total of 9,033,423 confirmed cases and more than 469,539 deaths across 215 countries, person to-person transmission has being identified as the route for spreading. So far, the lack of effective vaccines for the treatment or prevention of Covid-19 has further worsened the situation. In this context, the present study aims to assess whether naturally occurring components have an antiviral effect via a computational modeling approach. Density Functional theory (DFT) was performed to estimate the kinetic parameters, frontier molecular orbitals, molecular electrostatic potential as well as chemical reactivity descriptors of various ligands. The results revealed that Crocin and Digitoxigenin exhibited a potential applicant with the lowest resistance to electronic charge transfer with a chemical hardness of 2.19eV and 2.96eV respectively, as well as the lowest HOMO-LUMO difference. In addition to the DFT calculation, a docking simulation study was conducted on the SARS-CoV-2 base protease (PDB: 6LU7) to determine the binding affinity of ligands. The findings show that Crocin exhibits the lowest binding energy of -8.1 Kcal/mol and may be a good inhibitor of CoV-2-SARS compared to hydroxychloroquine and chloroquine, which have a binding affinity of -5.4 and -4.9 Kcal/mol, respectively. The high binding affinity of L3 was assigned to the existence of 14 hydrogen bonds connecting the ligand to the critical amino acid residues of the receptor.