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Computational analysis of antiviral drugs against South African (B.1.351) SARS-CoV-2 spike protein variant

I.V. Ferrari1 , M. Di Mario2

Section:Research Paper, Product Type: Journal-Paper
Vol.9 , Issue.6 , pp.121-128, Dec-2021


Online published on Dec 31, 2021


Copyright © I.V. Ferrari, M. Di Mario . 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.
 

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IEEE Style Citation: I.V. Ferrari, M. Di Mario, “Computational analysis of antiviral drugs against South African (B.1.351) SARS-CoV-2 spike protein variant,” International Journal of Scientific Research in Computer Science and Engineering, Vol.9, Issue.6, pp.121-128, 2021.

MLA Style Citation: I.V. Ferrari, M. Di Mario "Computational analysis of antiviral drugs against South African (B.1.351) SARS-CoV-2 spike protein variant." International Journal of Scientific Research in Computer Science and Engineering 9.6 (2021): 121-128.

APA Style Citation: I.V. Ferrari, M. Di Mario, (2021). Computational analysis of antiviral drugs against South African (B.1.351) SARS-CoV-2 spike protein variant. International Journal of Scientific Research in Computer Science and Engineering, 9(6), 121-128.

BibTex Style Citation:
@article{Ferrari_2021,
author = {I.V. Ferrari, M. Di Mario},
title = {Computational analysis of antiviral drugs against South African (B.1.351) SARS-CoV-2 spike protein variant},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {12 2021},
volume = {9},
Issue = {6},
month = {12},
year = {2021},
issn = {2347-2693},
pages = {121-128},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=2617},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=2617
TI - Computational analysis of antiviral drugs against South African (B.1.351) SARS-CoV-2 spike protein variant
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - I.V. Ferrari, M. Di Mario
PY - 2021
DA - 2021/12/31
PB - IJCSE, Indore, INDIA
SP - 121-128
IS - 6
VL - 9
SN - 2347-2693
ER -

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Abstract :
The present work is intended to study, through the “Molecular Docking” approach, about 100 antiviral drugs, against the South African (B.1.351) SARS-CoV-2 spike protein variant. The analysis was performed by Autodock Vina, in which we scan the active area of three key amino acids belonging to the Spike Protein RBD, responsible for a higher binding with the ACE2 receptor. They are ASN 417; Lys 484, and Tyr 501 respectively. From our results, we have found out five potential inhibitor drugs of the hepatitis C virus (HCV ), which have been shown a good Binding Energy score of -10 kcal mol-1. They are Furaprevir, Simeprevir, Odalasvir, and Paritaprevir respectively. In addition, their best-docked pose can bind to two of the three investigated residues of the Spike-RBD, which are N 417 and Y 501. As known, these last residues have been found in other Coronavirus variants as the most recent case of the Omicron one.

Key-Words / Index Term :
Docking; SARS-CoV-2 spike protein variant

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