TMPRSS2 inhibitor discovery facilitated through an in silico and biochemical screening platform

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Abstract

The COVID-19 pandemic has highlighted the need for new antiviral targets, as many of the currently approved drugs have proven ineffective against mitigating SARS-CoV-2 infections. The host transmembrane serine protease TMPRSS2 is a highly promising antiviral target, as it plays a direct role in priming the spike protein before viral entry occurs. Further, unlike other targets such as ACE2, TMPRSS2 has no known biological role. Here we utilize virtual screening to curate large libraries into a focused collection of potential inhibitors. Optimization of a recombinant expression and purification protocol for the TMPRSS2 peptidase domain facilitates subsequent biochemical screening and characterization of selected compounds from the curated collection in a kinetic assay. In doing so, we demonstrate that serine protease inhibitors camostat, nafamostat, and gabexate inhibit through a covalent mechanism. We further identify new non-covalent compounds as TMPRSS2 protease inhibitors, demonstrating the utility of a combined virtual and experimental screening campaign in rapid drug discovery efforts.

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  1. SciScore for 10.1101/2021.03.22.436465: (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

    Antibodies
    SentencesResources
    TMPRSS2 antibody (Novus biologicals, NBP1-20984) was added to membrane (1:1000 dilution in Super Block) and incubated overnight at 4C with gentle shaking.
    TMPRSS2
    suggested: (Novus Cat# NBP1-20984, RRID:AB_1643199)
    Software and Algorithms
    SentencesResources
    Raw data was deconvoluted (intact protein of 20,000-25,000 Da) using BioConfirm software with background subtraction.
    BioConfirm
    suggested: None
    V0 was plotted vs substrate concentration and the data was fit to the Michaelis Menten equation using GraphPad Prism.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.
    • No funding statement was detected.
    • 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.