Quantitative Structure-Activity Relationships and Molecular Docking Simulation of Allicin Compounds As Inhibitors of Covid-19 Protease Enzyme

Background: coronavirus (cov) is a group of viruses that cause disease in humans andanimals. these viruses contain crown-shaped spike glycoproteins on their surface.objective: we conducted a quantitative structure-activity relationship (qsar) study on a series of36 compounds of allicin to assess their antiviral activities against the main protease of covid-19.methods: in the present descriptive-analytic study, the information on the structure ofcompounds, the covid-19 protease enzyme, and the allicin derivatives was obtained fromthe databases such as the research collaboratory for structural bioinformatics’ proteindata bank (pdb) and pubchem. the qsar method, analysis of correlations and multiplelinear regressions were carried out. six molecular descriptors such as constitutional andmolecular topology descriptors were selected for the model. finally, molecular dockingwas performed in igemdock 2.1 software.results: the obtained multi-parametric model reported a correlation coefficient of about 0.89,indicating that the model was able to satisfactory predict the antiviral activity of allicin compounds.conclusion: the findings obtained can be valuable in designing, synthesizing, anddeveloping novel antiviral agents with allicin-based scaffold.