Computational Drug Discovery and Repurposing for the Treatment of COVID-19: A Systematic Review

42 Pages Posted: 29 Apr 2020

See all articles by Kawthar Mohamed

Kawthar Mohamed

Universal Scientific Education and Research Network (USERN)

Niloufar Yazdanpanah

Universal Scientific Education and Research Network (USERN)

Amene Saghazadeh

Universal Scientific Education and Research Network (USERN)

Nima Rezaei

Tehran University of Medical Sciences - Children's Medical Centre

Date Written: April 23, 2020

Abstract

Background: Since the beginning of the novel coronavirus (SARS-CoV-2) disease outbreak, there has been an increasing interest in finding a potential therapeutic agent for the disease. Considering the matter of time, the computational methods of drug repurposing offer the best chance of selecting one drug from a list of approved drugs for the life-threatening condition of COVID-19. The present systematic review aims to provide an overview of studies that have used computational methods for drug repurposing in COVID-19.

Methods: We undertook a systematic search in five databases and included original articles in English that applied computational methods for drug repurposing in COVID-19.

Results: Twenty-one original articles utilizing computational drug methods for COVID-19 drug repurposing were included in the systematic review. Regarding the quality of eligible studies, high-quality items including the use of two or more approved drug databases, analysis of molecular dynamic simulation, multi-target assessment, the use of crystal structure for the generation of the target sequence, and the use of AutoDock Vina combined with other docking tools occurred in about 52%, 38%, 24%, 48%, and 19% of included studies. Studies included repurposed drugs mainly against non-structural proteins of SARS-CoV2: the main 3C-like protease (Lopinavir, Ritonavir, Indinavir, Atazanavir, Nelfinavir, and Clocortolone), RNA-dependent RNA polymerase (Remdesivir and Ribavirin), and the papain-like protease (Mycophenolic acid, Telaprevir, Boceprevir, Grazoprevir, Darunavir, Chloroquine, and Formoterol). The review revealed the best-documented multi-target drugs repurposed by computational methods for COVID-19 therapy as follows: antiviral drugs commonly used to treat AIDS/HIV (Atazanavir, Efavirenz, and Dolutegravir Ritonavir, Raltegravir, and Darunavir, Lopinavir, Saquinavir, Nelfinavir, and Indinavir), HCV (Grazoprevir, Lomibuvir, Asunaprevir, Ribavirin, and Simeprevir), HBV (Entecavir), HSV (Penciclovir), CMV (Ganciclovir), and Ebola (Remdesivir), anticoagulant drug (Dabigatran), and an antifungal drug (Itraconazole).

Conclusions: The present systematic review provides a list of existing drugs that have the potential to influence SARS-CoV2 through different mechanisms of action. For the majority of these drugs, direct clinical evidence on their efficacy for the treatment of COVID-19 is lacking. Future clinical studies examining these drugs might come to conclude, which can be more useful to inhibit COVID-19 progression.

Note: Funding: There is no funding for the present study.

Conflict of Interest: The authors declare that they have no competing interests.

Ethical Approval: Not applicable.

Keywords: Drug Discovery; Drug Repurposing; Computational methods; SARS-CoV-2; COVID-2019

JEL Classification: I1

Suggested Citation

Mohamed, Kawthar and Yazdanpanah, Niloufar and Saghazadeh, Amene and Rezaei, Nima, Computational Drug Discovery and Repurposing for the Treatment of COVID-19: A Systematic Review (April 23, 2020). Available at SSRN: https://ssrn.com/abstract=3583748 or http://dx.doi.org/10.2139/ssrn.3583748

Kawthar Mohamed

Universal Scientific Education and Research Network (USERN)

Ahvaz
Iran

Niloufar Yazdanpanah

Universal Scientific Education and Research Network (USERN)

Ahvaz
Iran

Amene Saghazadeh

Universal Scientific Education and Research Network (USERN) ( email )

Ahvaz
Iran

Nima Rezaei (Contact Author)

Tehran University of Medical Sciences - Children's Medical Centre ( email )

Tehran
Iran

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