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Screening of drugs by FRET analysis identifies inhibitors of SARS-CoV 3CL protease.

ABSTRACT: SARS-CoV 3CL protease is essential for viral protein processing and is regarded as a good drug target to prevent SARS-CoV replication. In the present study, we established a high-throughput FRET technique for screening for anti-SARS-CoV 3CL protease drugs. Of a thousand existing drugs examined, hexachlorophene was identified as the most potent in inhibiting SARS-CoV 3CL protease. Further characterization showed that it was effective at micromolar concentrations (K(i) = 4 microM). The binding mode was competitive, and the inhibitory effect was dependent on preincubation time. Two other drugs, triclosan and nelfinavir, were about 10 times less potent. The structure-based search and biological evaluation of various hexachlorophene analogues were described. These analogues gave optimal inhibitory activity against SARS-CoV 3CL protease with IC(50) values ranging from 7.6 to 84.5 microM. Optimization of hexachlorophene analogues was shown to provide several active 3CL protease inhibitors that function as potential anti-SARS agents.

SUBMITTER: Liu YC

PROVIDER: S-EPMC7092914 | biostudies-literature | 2005 Jul

REPOSITORIES: biostudies-literature

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Screening of drugs by FRET analysis identifies inhibitors of SARS-CoV 3CL protease.

Liu Yu-Chih YC Huang Vicky V Chao Ti-Chun TC Hsiao Chwan-Deng CD Lin Atsui A Chang Ming-Fu MF Chow Lu-Ping LP

Biochemical and biophysical research communications 20050701 1

SARS-CoV 3CL protease is essential for viral protein processing and is regarded as a good drug target to prevent SARS-CoV replication. In the present study, we established a high-throughput FRET technique for screening for anti-SARS-CoV 3CL protease drugs. Of a thousand existing drugs examined, hexachlorophene was identified as the most potent in inhibiting SARS-CoV 3CL protease. Further characterization showed that it was effective at micromolar concentrations (K(i) = 4 microM). The binding mod ...[more]

PMID: 15950190

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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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Screening of drugs by FRET analysis identifies inhibitors of SARS-CoV 3CL protease.

Publications

Screening of drugs by FRET analysis identifies inhibitors of SARS-CoV 3CL protease.

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