Quantitative Structure-Activity Relationships and Molecular Docking Simulation of Allicin Compounds as Inhibitors of COVID-19 Protease Enzyme
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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background

Coronavirus (CoV) is a group of viruses that cause disease in humans and animals. These viruses contain crown-shaped spike glycoproteins on their surface.

Objective

We conducted a quantitative structure-activity relationship (QSAR) study on a series of 36 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 of compounds, the COVID-19 protease enzyme, and the Allicin derivatives was obtained from the databases such as the Research Collaboratory for Structural Bioinformatics’ Protein Data Bank (PDB) and PubChem. The QSAR method, analysis of correlations and multiple linear regressions were carried out. Six molecular descriptors such as constitutional and molecular topology descriptors were selected for the model. Finally, molecular docking was 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, and developing novel antiviral agents with allicin-based scaffold.

Language:
English
Published:
Journal of Inflammatory Diseases, Volume:25 Issue: 3, Autumn 2021
Pages:
161 to 168
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