Molecular Mechanism of Action of Repurposed Drugs and Traditional Chinese Medicine Used for the Treatment of Patients Infected With COVID-19: A Systematic Scoping Review

  1. Fui Fui Lem
  2. Fernandes Opook
  3. Dexter Jiunn Herng Lee
  4. Fong Tyng Chee
  5. Fahcina P. Lawson
  6. Su Na Chin

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Abstract

Background: The emergence of COVID-19 as a pandemic has resulted in the need for urgent development of vaccines and drugs and the conduction of clinical trials to fight the outbreak. Because of the time constraints associated with the development of vaccines and effective drugs, drug repurposing and other alternative treatment methods have been used to treat patients that have been infected by the SARS-CoV-2 virus and have acquired COVID-19.

Objective: The objective of this systematic scoping review is to provide an overview of the molecular mechanism of action of repurposed drugs or alternative treatment medicines used to attenuate COVID-19 disease.

Method: The research articles or gray literature, including theses, government reports, and official news online, were identified from four databases and one search engine. The full content of a total of 160 articles that fulfilled our inclusion criteria was analyzed and information about six drugs (ritonavir, lopinavir, oseltamivir, remdesivir, favipiravir, and chloroquine) and four Traditional Chinese Medicines ( Shuang Huang Lian Kou Fu Ye , TCM combination of Bu Huan Jin Zheng Qi San and Da Yuan Yin, Xue Bi Jing Injection , and Qing Fei Pai Du Tang ) was extracted.

Results: All of the repurposed drugs and complementary medicine that have been used for the treatment of COVID-19 depend on the ability of the drug to inhibit the proliferation of the SARS-CoV-2 virus by binding to enzyme active sites, viral chain termination, or triggering of the molecular pathway, whereas Traditional Chinese Medicine plays a pivotal role in triggering the inflammation pathway, such as the neuraminidase blocker, to fight the SARS-CoV-2 virus.

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  1. Version published to 10.3389/fphar.2020.585331
  2. ScreenIT

    SciScore for 10.1101/2020.04.10.20060376: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The list of publications was obtained from listed databases and search engines: PubMed (https://www.ncbi.nlm.nih.gov/pubmed/), Science Direct (https://www.sciencedirect.com/), Google Scholar(https://scholar.google.com/) and Semantic Scholar (https://www.semanticscholar.org/), whereas grey literature search such as guidelines, theses and dissertations, research and committee reports, government reports, conference papers, and abstracts were obtained from WHO, U.S National Library of Medicine, Chinese Clinical Trial Registry (http://www.chictr.org.cn/abouten.aspx), China Centre for disease control and prevention, China Important Conference Papers Database, China Dissertation Database, and online official news websites.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Google Scholar(https://scholar.google.com/
    suggested: None
    Semantic Scholar
    suggested: (VideoLectures.NET, RRID:SCR_001972)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.04.10.20060376v3 on medRxiv
  4. Version published to 10.1101/2020.04.10.20060376v2 on medRxiv
  5. Version published to 10.1101/2020.04.10.20060376v1 on medRxiv