Blind Docking Analysis of Potential Drugs against SARS-COV-1 and SARS-COV-2 Proteins

Ivan Vito Ferrari¹

Section:Research Paper, Product Type: Journal-Paper
Vol.9 , Issue.6 , pp.85-89, Dec-2021

Online published on Dec 31, 2021

Copyright © Ivan Vito Ferrari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library

XML View     PDF Download

How to Cite this Paper

Abstract :
— In this short communication, more than 300 drugs were investigated by Blind Docking approach, by Autodock Vina Scoring Function with Pyrx Software. From Blind Docking Results, Deslanoside, Dactinomycin, Teicoplanin aglycone, Conivaptan, Paritaprevir, Acetyldigitoxin, Nafarelin, Lanatoside_C, Dydroergocristine, Dydroergotamine, Tirilazad, and Ubrogepant are potential candidates against SARS-COV-1 and SARS-COV-2 proteins. Particular attention, Acetyldigitoxin, Dactinomycin, and Deslanoside with Binding Energy about -12 .00 kcal mol -1 are higher binding Energies values against SARS-COV-2 Mpro. Regarding SARS-COV-2 RBD, Teicoplanin aglycone and Dactinomycin have a potentially significant role with a binding energy value of -12.50 kcal mol -1.

Key-Words / Index Term :
Autodock Vina, PyRx

References :
[1] Dallakyan, S., and Olson, A. J. “Small-molecule library screening by docking with PyRx”, Methods in molecular biology (Clifton, N.J.), Vol. 1263, pp. 243–250, 2015.https://doi.org/10.1007/978-1-4939-2269-7_19.
[2] Llabrés, M., and Valiente, G. “ Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2”, PloS one, Vol.15, Issue. 12, pp.e0236304, 2020.https://doi.org/10.1371/journal.pone.0236304.
[3] Forli, S., Huey, R., Pique, M. E., Sanner, M. F., Goodsell, D. S., and Olson, A. J. “Computational protein-ligand docking and virtual drug screening with the AutoDock suite”, Nature protocols, Vol.11, Issue.5, pp.905–919,2016. https://doi.org/10.1038/nprot.2016.051.
[4] Trott, O., and Olson, A. J. “AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading”, Journal of computational chemistry, Vol.31, Issue.2, pp. 455–461, 2010. https://doi.org/10.1002/jcc.21334
[5] Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., and Olson, A. J.” AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility”, Journal of computational chemistry, Vol.30, Isssue.16, pp.2785–2791, 2009. https://doi.org/10.1002/jcc.21256.
[6] Kaplan, W., & Littlejohn, T. G.” Swiss-PDB Viewer (Deep View)”Briefings in bioinformatics, Vol.2, Issue. 2, pp.195–197, 2001. https://doi.org/10.1093/bib/2.2.195.
[7] Sulimov, A. V., Kutov, D. K., Ilin, I. S., & Sulimov, V. B. “Doking s kombinirovannym primeneniem silovogo polia i kvantovo-khimicheskogo metoda [Docking with combined use of a force field and a quantum-chemical method]”, Biomeditsinskaia khimiia, Vol.65, Issue.2, pp.80–85, 2019.