Drugs repurposing for SARS-CoV-2: new insight of COVID-19 druggability

ABSTRACT

Introduction

The ongoing epidemic of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) creates a massive panic worldwide due to the absence of effective medicines. Developing a new drug or vaccine is time-consuming to pass safety and efficacy testing. Therefore, repurposing drugs have been introduced to treat COVID-19 until effective drugs are developed.

Area covered

A detailed search of repurposing drugs against SARS-CoV-2 was carried out using the PubMed database, focusing on articles published 2020 years onward. A different class of drugs has been described in this article to target hosts and viruses. Based on the previous pandemic experience of SARS-CoV and MERS, several antiviral and antimalarial drugs are discussed here. This review covers the failure of some repurposed drugs that showed promising activity in the earlier CoV-pandemic but were found ineffective against SARS-CoV-2. All these discussions demand a successful drug development strategy for screening and identifying an effective drug for better management of COVID-19.

Expert opinion

Repurposed drugs have been used since COVID-19 to eradicate disease propagation. Drugs found effective for MERS and SARS may not be effective against SARS-CoV-2. Drug libraries and artificial intelligence are helpful tools to screen and identify different molecules targeting viruses or hosts.

KEYWORDS:

• Repurpose
• COVID-19
• SARS-CoV-2
• druggability
• screening
• development strategy

Article highlights

• The repurposing strategy is an alternative solution for emergent infections like COVID-19.

• The molecular-cellular interaction is essential for repurposing drugs to achieve potential and rapid cure against COVID-19.

• S protein is responsible for viral entry into the host cell and can be a possible target site for eradicating this disease.

• All moderate to highly active drugs used in treating SARS-CoV and MERS-CoV may not be effective for the SARS-CoV-2.

• Deep learning is a handy tool for predicting drug-target interactions than a single

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Author contributions

All authors contributed to the study conception and design. BLINDED wrote the first draft and revised the entire manuscript. BLINDED supervised the work. All authors read and approved the manuscript.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.