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Review

Computational Chemistry to Repurposing Drugs for the Control of COVID-19

1
Institute for Health and Sport, Victoria University, Melbourne 3011, Australia
2
Department of Mechanical Engineering, Faculty of Immunology, K. N. Toosi University of Technology, Tehran 19697, Iran
3
Department of Chemical Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran
*
Author to whom correspondence should be addressed.
Academic Editor: Seth Pincus
Received: 11 June 2021 / Revised: 7 July 2021 / Accepted: 8 July 2021 / Published: 15 July 2021
(This article belongs to the Special Issue Anti-SARS-CoV-2/COVID-19 Drugs and Vaccines)
Thus far, in 2021, 219 countries with over 175 million people have been infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 is a positive sense, single-stranded RNA virus, and is the causal agent for coronavirus disease (COVID-19). Due to the urgency of the situation, virtual screening as a computational modeling method offers a fast and effective modality of identifying drugs that may be effective against SARS-CoV-2. There has been an overwhelming abundance of molecular docking against SARS-CoV-2 in the last year. Due to the massive volume of computational studies, this systematic review has been created to evaluate and summarize the findings of existing studies. Herein, we report on computational articles of drugs which target, (1) viral protease, (2) Spike protein-ACE 2 interaction, (3) RNA-dependent RNA polymerase, and (4) other proteins and nonstructural proteins of SARS-CoV-2. Based on the studies presented, there are 55 identified natural or drug compounds with potential anti-viral activity. The next step is to show anti-viral activity in vitro and translation to determine effectiveness into human clinical trials. View Full-Text
Keywords: COVID-19; SARS-CoV-2; computational modeling; molecular docking; molecular dynamics; nonstructural proteins; docking score COVID-19; SARS-CoV-2; computational modeling; molecular docking; molecular dynamics; nonstructural proteins; docking score
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MDPI and ACS Style

Hassanzadeganroudsari, M.; Ahmadi, A.H.; Rashidi, N.; Hossain, M.K.; Habib, A.; Apostolopoulos, V. Computational Chemistry to Repurposing Drugs for the Control of COVID-19. Biologics 2021, 1, 111-128. https://0-doi-org.brum.beds.ac.uk/10.3390/biologics1020007

AMA Style

Hassanzadeganroudsari M, Ahmadi AH, Rashidi N, Hossain MK, Habib A, Apostolopoulos V. Computational Chemistry to Repurposing Drugs for the Control of COVID-19. Biologics. 2021; 1(2):111-128. https://0-doi-org.brum.beds.ac.uk/10.3390/biologics1020007

Chicago/Turabian Style

Hassanzadeganroudsari, Majid, Amir H. Ahmadi, Niloufar Rashidi, Md K. Hossain, Amanda Habib, and Vasso Apostolopoulos. 2021. "Computational Chemistry to Repurposing Drugs for the Control of COVID-19" Biologics 1, no. 2: 111-128. https://0-doi-org.brum.beds.ac.uk/10.3390/biologics1020007

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