An updated research focus on the employment of computer-aided drug discovery and repurposing techniques for the identification and evaluation of SARS-CoV-2 Main protease inhibitors: A protocol for a systematic review and meta-analysis
Authors: Mushebenge Aganze Gloire-Aimé , Ugbaja Samuel Chima , Mbatha Nonkululeko Avril , Riziki Manimani Ghislain , Muzumbukilwa Tambwe Willy , kadima Mukanda Gedeon , Nlooto Manimbulu , Kumalo Hezekiel M. 
Published: August 2023

Background

With the onset of the COVID-19 pandemic caused by the novel coronavirus (SARS-CoV-2), there has been a surge in the pursuit of potential therapeutic interventions for this deadly disease. Given the urgency of the situation, computational drug repurposing methods have emerged as a promising strategy for identifying effective treatments from a pool of approved drugs. This systematic review and meta-analaysis will assess the existing research on the use of computational approaches for drug repurposing in the context of COVID-19. SARS-CoV-2 Main Protease is a critical enzyme that plays a vital role in the replication cycle of the SARS-CoV-2 virus, and its inhibition is a promising strategy for the development of antiviral therapies.

Methods/Design

Different databases (PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), MEDLINE via EBSCOhost, Google Scholar, and WILEY online Library) will be utilized to identify and incorporate primary research articles in English and French that employed computational methodologies for drug repurposing in the context of COVID-19 and SARS-CoV-2 Main protease inhibition published between March 2020 to May 2023. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR), we will undertake a comprehensive search of relevant studies. Authors will also search peer-reviewed articles, grey literature sources, and reference lists to identify eligible studies. Title screening will be followed by independent abstract and full-text screening by two reviewers. Any study that focuses on the inhibition of the Mpro using computer aided methods will be included. The analysis of data will be carried out by utilizing two software tools - Review Manager software (version 5.3.5) and R software (version 3.6.1). To determine statistical heterogeneity, a standard chi-square test will be applied with a significance level of P < 0.10. Potential biases related to study size (such as publication bias) will be examined through the application of several techniques, including funnel plots, Egger’s test, Begg’s test, as well as Trim and Fill analysis.

Discussion

This study will provide evidence-based information and conduct a comprehensive analysis of the computer-aided drug discovery and repurposing of the SARS-CoV-2 Main protease inhibitors, thereby producing a high-quality synthesis of information. The study will also explore potential innovative therapeutic applications for preventing or treating the novel viral infection by the inhibition of the Main Protease. In addition, the review will highlight research gaps in the treatment of COVID-19 and provide suggestions for future research. The outcomes of this review will be shared through a peer-reviewed publication and presented at relevant conferences while ensuring proper dissemination to reach a wide audience.

Systematic review registration: CRD42023409682

(https://www.crd.york.ac.uk/prospero/display_record.asp?ID=CRD42023409682)