Discovery of Drug-like Ligands for the Mac1 Domain of SARS-CoV-2 Nsp3

  1. Rajdeep S. Virdi
  2. Robert V. Bavisotto
  3. Nicholas C. Hopper
  4. Nemanja Vuksanovic
  5. Trevor R. Melkonian
  6. Nicholas R. Silvaggi
  7. David N. Frick

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Abstract

Small molecules that bind the SARS-CoV-2 non-structural protein 3 Mac1 domain in place of ADP-ribose could be useful as molecular probes or scaffolds for COVID-19 antiviral drug discovery because Mac1 has been linked to coronavirus’ ability to evade cellular detection. A high-throughput assay based on differential scanning fluorimetry (DSF) was therefore optimized and used to identify possible Mac1 ligands in small libraries of drugs and drug-like compounds. Numerous promising compounds included nucleotides, steroids, beta-lactams, and benzimidazoles. The main drawback to this approach was that a high percentage of compounds in some libraries were found to influence the observed Mac1 melting temperature. To prioritize DSF screening hits, the shapes of the observed melting curves and initial assay fluorescence were examined, and the results were compared with virtual screens performed using Autodock VINA. The molecular basis for alternate ligand binding was also examined by determining a structure of one of the hits, cyclic adenosine monophosphate, with atomic resolution.

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    SciScore for 10.1101/2020.07.06.190413: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Tm’s were calculated by fitting the data to equation 1 using either GraphPad Prism or TSA-CRAFT (https://sourceforge.net/projects/tsa-craft/).8

    In Eq. 1, Fobs (T) is the observed fluorescence at each temperature (T), Fmin is the minimum observed fluorescence, Fmax is maximum observed fluorescence, and a is a Hill slope.

    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Docking box location was configured prior to using AutoDock tools.
    AutoDock
    suggested: (AutoDock, RRID:SCR_012746)

    Results from OddPub: Thank you for sharing your data.

    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.

  2. Version published to 10.1101/2020.07.06.190413 on bioRxiv