Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease

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Abstract

COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments were progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.

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  1. SciScore for 10.1101/2020.05.27.118117: (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
    2020); heterocyclic electrophiles (Keeley et al., 2019); and the SpotFinder library (Bajusz and Keserü).
    SpotFinder
    suggested: (Spotfinder, RRID:SCR_000085)
    Further analysis was performed with XChemExplorer (Krojer et al., 2017): electron density maps were generated with Dimple (Keegan et al., 2015); ligand-binding events were identified using PanDDA (Pearce et al., 2017) (both the released version 0.2 and the pre-release development version (https://github.com/ConorFWild/pandda)); ligands were modelled into PanDDA-calculated event maps using Coot (Emsley et al., 2010); restraints were calculated with ACEDRG or GRADE (Long et al., 2017, Smart et al., 2010); and structures were refined with Refmac (Murshudov et al., 2011) and Buster (Bricogne et al., 2017).
    Coot
    suggested: (Coot, RRID:SCR_014222)
    Refmac
    suggested: (Refmac, RRID:SCR_014225)

    Results from OddPub: Thank you for sharing your code and 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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04353128RecruitingEfficacy of Melatonin in the Prophylaxis of Coronavirus Dise…


    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

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