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

Hossein Piri; Elham Hajialilo; Sayyed Nima  Hashemi Ghermezi; Mohammad Taghi Goodarzi; Saeede  Salemi-Bazargani; Anoosh  eghdami

Journal of Inflammatory Diseases

The Official Journal of Qazvin University of Medical Sciences

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

Author(s):

Hossein Piri,

Elham Hajialilo¹,

Sayyed Nima Hashemi Ghermezi²,

Mohammad Taghi Goodarzi³,

Saeede Salemi-Bazargani⁴,

Anoosh eghdami^5,*

1Department of Parasitology and Mycology, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran.

2Department of Industrial Engineering, Faculty of Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran.

3Department of Biochemistry, Islamic Azad University, Shahrood Branch, Shahrood, Iran.

4Student Research Committee, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran.

5Department of Biochemistry, School of Medicine, Saveh Branch, Islamic Azad University, Saveh, Iran.

Journal of Inflammatory Diseases:Vol. 25, issue 3; 161-168

Published online:Dec 31, 2021

Article type:Research Article

How to Cite:Piri H, Hajialilo E, Hashemi Ghermezi SN, Goodarzi MT, Salemi-Bazargani S, et al. Quantitative Structure-Activity Relationships and Molecular Docking Simulation of Allicin Compounds as Inhibitors of COVID-19 Protease Enzyme. J Inflamm Dis. 2024;25(3):e156289. doi:

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.

Keywords

Quantitative structure-activity relationship

COVID-19

Allicin

Protease inhibitors

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Author(s):

Hossein Piri:[PubMed][Scholar]
Elham Hajialilo:[PubMed][Scholar]
Sayyed Nima Hashemi Ghermezi:[PubMed][Scholar]
Mohammad Taghi Goodarzi:[PubMed][Scholar]
Saeede Salemi-Bazargani:[PubMed][Scholar]
Anoosh eghdami:[PubMed][Scholar]

The Official Journal of Qazvin University of Medical Sciences

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

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