Screening Efficacy of Available HIV Protease Inhibitors on COVID-19 Protease

Document Type : Original Research

Authors

1 Biosensor Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

2 Universitas Muhammadiyah Surakarta

3 Isfahan University of Medical Sciences

Abstract

Background and Aim: Advent of COVID-19 attracted the attentions of researchers to develop drugs for its treatment. Besides efforts on developing new drugs, screening available drugs for efficacy on COVID-19 could be an urgent action of initiating its pharmacotherapy. In this study, efficacy of HIV protease inhibitors on COVID-19 protease has been examined.
Methods: Molecular docking based screening by AutoDock software has been done to examine the efficacy of ligand-receptor interactions.
Results: Obtained results of binding energy, inhibitory constant and interactions quality have approved the idea of efficacy of HIV protease inhibitors on COVID-19 protease.
Conclusion: Quantitative results indicated different levels of efficacy of investigated ligands for inhibitory activity of COVID-19 and qualitative results indicated various localizations of ligands in the proposed active site of protease. The concluding remarks of this study are to introduce Nelfinavir as the best ligand in quantitative respect and each of Saquinavir, Amprenavir and Fosamprenavir as the best ligands inqualitative respect for possible inhibitory effects on COVID-19 protease.

Keywords

References

1. Farnoosh G, Alishiri G, Hosseini Zijoud S R, Dorostkar R, Jalali Farahani A. Understanding the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Coronavirus Disease (COVID-19) Based on Available Evidence - A Narrative Review. J Mil Med. 2020; 22 (1) :1-11. 2. Ahmed SF, Quadeer AA, McKay MR. Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies. Viruses 2020;12 (3): 254. 3. Liu X, Zhang B, Jin Z, Yang H, Rao Z. The crystal structure of COVID-19 main protease in complex with an inhibitor N3. 2020. 4. Elfiky AA. Anti-HCV, nucleotide inhibitors, repurposing against COVID-19. Life sciences. 2020 Feb 28:117477. 5. Kapetanovic IM. Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach. Chemico-biological interactions. 2008;171(2):165-76. 6. Guney E, Menche J, Vidal M, Barábasi AL. Network-based in silico drug efficacy screening. Nature communications. 2016;7:10331. 7. Drugs.com. Prescription Drug Information, Interactions & Side Effects. 8. Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, et al. RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic acids research. 2019;47(D1):D464-74. 9. Pence HE, Williams A. Chem Spider: An Online Chemical Information Resource. J Chem Edu. 2010; 87:1123-1124. 10. Hosseini SA, Moghimi A, Iman M. Design and docking study of novel oximes as reactivators of inhibited acetylcholinesterase with nerve agents. Journal Mil Med. 2018;20(2):170-80. 11. Iman M, AsnaAshari B, Davood A. Docking and QSAR study on triazolederivatives as more potent and effective antifungal agents. J Mil Med. 2015; 17(2):97-105. 12. Davood A, Iman M. Molecular docking and QSAR study on imidazole derivatives as 14/alpha-demethylase inhibitors. Turk J Chem. 2013;37 (1):119-133. 13. Alidoosti ZS, Mirzaei M. Comparative Examination of Moclobemide, Tranylcypromine, Phenelzine and Isocarboxazid for Monoamine Oxidase–A Inhibition. Advanced Journal of Chemistry-Section B: Natural Products and Medical Chemistry. 2019;1(1):23-8. 14. Nazemi H, Mirzaei M, Jafari E. Antidepressant activity of curcumin by monoamine oxidase–A inhibition. J Adv Chem B. 2019;1:3-9. 15. Esfahani AN, Mirzaei M. Flavonoid derivatives for monoamine oxidase–A inhibition. Adv J Chem B. 2019;1(1):17-22. 16. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009;30(16): 2785-2791.
Journal of Military Medicine
Volume 22, Issue 2 - Serial Number 86
March and April 2020
Pages 100-107

Files

Share

How to cite

Statistics