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Virtual high throughput screening: Potential Inhibitors for SARS-CoV-2 PL^PRO and 3CL^PRO Proteases.

ABSTRACT: The pandemic, COVID-19, has spread worldwide and affected millions of people. There is an urgent need, therefore, to find a proper treatment for the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent. This paper focuses on identifying inhibitors that target SARS-CoV-2 proteases, PL^PRO and 3CL^PRO, which control the duplication and manages the life cycle of SARS-CoV-2. We have carried out detailed in silico Virtual high-throughput screening using Food and Drug Administration (FDA) approved drugs from the Zinc database, COVID-19 clinical trial compounds from Pubchem database, Natural compounds from Natural Product Activity and Species Source (NPASS) database and Maybridge database against PL^PRO and 3CL^PRO proteases. After thoroughly analyzing the screening results, we found five compounds, Bemcentinib, Pacritinib, Ergotamine, MFCD00832476, and MFCD02180753 inhibit PL^PRO and six compounds, Bemcentinib, Clofazimine, Abivertinib, Dasabuvir, MFCD00832476, Leuconicine F inhibit the 3CL^PRO. These compounds are stable within the protease proteins' active sites at 20ns MD simulation. The stability is revealed by hydrogen bond formations, hydrophobic interactions, and salt bridge interactions. Our study results also reveal that the selected five compounds against PL^PRO and the six compounds against 3CL^PRO bind to their active sites with good binding free energy. These compounds that inhibit the activity of PL^PRO and 3CL^PRO may, therefore, be used for treating COVID-19 infection.

SUBMITTER: Jade D

PROVIDER: S-EPMC8018918 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Virtual high throughput screening: Potential inhibitors for SARS-CoV-2 PLPRO and 3CLPRO proteases.

Jade Dhananjay D Ayyamperumal Selvaraj S Tallapaneni Vyshnavi V Joghee Nanjan Chandrasekar Moola CM Barge Sagar S Mohan Surender S Nanjan Moola Joghee MJ

European journal of pharmacology 20210403

The pandemic, COVID-19, has spread worldwide and affected millions of people. There is an urgent need, therefore, to find a proper treatment for the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent. This paper focuses on identifying inhibitors that target SARS-CoV-2 proteases, PLPRO and 3CLPRO, which control the duplication and manages the life cycle of SARS-CoV-2. We have carried out detailed in silico Virtual high-throug ...[more]

PMID: 33823185

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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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Virtual high throughput screening: Potential Inhibitors for SARS-CoV-2 PL^PRO and 3CL^PRO Proteases.

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Virtual high throughput screening: Potential inhibitors for SARS-CoV-2 PL<sup>PRO</sup> and 3CL<sup>PRO</sup> proteases.

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Dataset Information

Virtual high throughput screening: Potential Inhibitors for SARS-CoV-2 PLPRO and 3CLPRO Proteases.

Publications

Virtual high throughput screening: Potential inhibitors for SARS-CoV-2 PL<sup>PRO</sup> and 3CL<sup>PRO</sup> proteases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Virtual high throughput screening: Potential Inhibitors for SARS-CoV-2 PL^PRO and 3CL^PRO Proteases.