Dataset Information

Luminescent Assay for the Screening of SARS-CoV-2 M^Pro Inhibitors.

ABSTRACT: Since the outbreak of SARS-CoV-2 in December 2019 millions of infections have been reported globally. The viral chymotrypsin-like main protease (M^Pro ) exhibits a crucial role in viral replication and represents a relevant target for antiviral drug development. In order to screen potential M^Pro inhibitors we developed a luminescent assay using a peptide based probe containing a cleavage site specific for M^Pro . This assay was validated showing IC₅₀ values similar to those reported in the literature for known M^Pro inhibitors and can be used to screen new inhibitors.

SUBMITTER: Sondag D

PROVIDER: S-EPMC9401586 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Luminescent Assay for the Screening of SARS-CoV-2 MPro Inhibitors.

Sondag Daan D Merx Jona J Rossing Emiel E Boltje Thomas J TJ Löwik Dennis W P M DWPM Nelissen Frank H T FHT van Geffen Mark M van 't Veer Cornelis C van Heerde Waander L WL Rutjes Floris P J T FPJT

Chembiochem : a European journal of chemical biology 20220614 15

Since the outbreak of SARS-CoV-2 in December 2019 millions of infections have been reported globally. The viral chymotrypsin-like main protease (MPro ) exhibits a crucial role in viral replication and represents a relevant target for antiviral drug development. In order to screen potential MPro inhibitors we developed a luminescent assay using a peptide based probe containing a cleavage site specific for MPro . This assay was validated showing IC50 val ...[more]

PMID: 35649961

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Project description:COVID-19 caused by a novel coronavirus (SARS-CoV-2) has been spreading all over the world since the end of 2019, and no specific drug has been developed yet. 3C-like protease (3CLpro) acts as an important part of the replication of novel coronavirus and is a promising target for the development of anticoronavirus drugs. In this paper, eight machine learning models were constructed using naïve Bayesian (NB) and recursive partitioning (RP) algorithms for 3CLpro on the basis of optimized two-dimensional (2D) molecular descriptors (MDs) combined with ECFP_4, ECFP_6, and MACCS molecular fingerprints. The optimal models were selected according to the results of 5-fold cross verification, test set verification, and external test set verification. A total of 5766 natural compounds from the internal natural product database were predicted, among which 369 chemical components were predicted to be active compounds by the optimal models and the EstPGood values were more than 0.6, as predicted by the NB (MD + ECFP_6) model. Through ADMET analysis, 31 compounds were selected for further biological activity determination by the fluorescence resonance energy transfer (FRET) method and cytopathic effect (CPE) detection. The results indicated that (+)-shikonin, shikonin, scutellarein, and 5,3',4'-trihydroxyflavone showed certain activity in inhibiting SARS-CoV-2 3CLpro with the half-maximal inhibitory concentration (IC50) values ranging from 4.38 to 87.76 μM. In the CPE assay, 5,3',4'-trihydroxyflavone showed a certain antiviral effect with an IC50 value of 8.22 μM. The binding mechanism of 5,3',4'-trihydroxyflavone with SARS-CoV-2 3CLpro was further revealed through CDOCKER analysis. In this study, 3CLpro prediction models were constructed based on machine learning algorithms for the prediction of active compounds, and the activity of potential inhibitors was determined by the FRET method and CPE assay, which provide important information for further discovery and development of antinovel coronavirus drugs.

Dataset Information

Luminescent Assay for the Screening of SARS-CoV-2 M^Pro Inhibitors.

Publications

Luminescent Assay for the Screening of SARS-CoV-2 M<sup>Pro</sup> Inhibitors.

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