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Identification of Vitamin K3 and its analogues as covalent inhibitors of SARS-CoV-2 3CL^pro.

ABSTRACT: After the emergence of the pandemic, repurposed drugs have been considered as a quicker way of finding potential antiviral agents. SARS-CoV-2 3CL^pro is essential for processing the viral polyproteins into mature non-structural proteins, making it an attractive target for developing antiviral agents. Here we show that Vitamin K3 screened from the FDA-Approved Drug Library containing an array of 1,018 compounds has potent inhibitory activity against SARS-CoV-2 3CL^pro with the IC₅₀ value of 4.78 ± 1.03 μM, rather than Vitamin K1, K2 and K4. Next, the time-dependent inhibitory experiment was carried out to confirm that Vitamin K3 could form the covalent bond with SARS-CoV-2 3CL^pro. Then we analyzed the structure-activity relationship of Vitamin K3 analogues and identified 5,8-dihydroxy-1,4-naphthoquinone with 9.8 times higher inhibitory activity than Vitamin K3. Further mass spectrometric analysis and molecular docking study verified the covalent binding between Vitamin K3 or 5,8-dihydroxy-1,4-naphthoquinone and SARS-CoV-2 3CL^pro. Thus, our findings provide valuable information for further optimization and design of novel inhibitors based on Vitamin K3 and its analogues, which may have the potential to fight against SARS-CoV-2.

SUBMITTER: Wang R

PROVIDER: S-EPMC8064871 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.

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Identification of Vitamin K3 and its analogues as covalent inhibitors of SARS-CoV-2 3CL^pro.

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Dataset Information

Identification of Vitamin K3 and its analogues as covalent inhibitors of SARS-CoV-2 3CLpro.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Identification of Vitamin K3 and its analogues as covalent inhibitors of SARS-CoV-2 3CL^pro.