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Bioorganic & Medicinal Chemistry Letters
Article . 2021 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Bioorganic & Medicinal Chemistry Letters
Article
License: CC BY NC ND
Data sources: UnpayWall
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PubMed Central
Other literature type . 2021
Data sources: PubMed Central
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Identification of non-covalent 3C-like protease inhibitors against severe acute respiratory syndrome coronavirus-2 via virtual screening of a Korean compound library

Authors: Young-Sik Jung; Eunhye Jung; Joo-Youn Lee; Jin Soo Shin; Po-Huang Liang; Po-Huang Liang; Chih-Jung Kuo;

Identification of non-covalent 3C-like protease inhibitors against severe acute respiratory syndrome coronavirus-2 via virtual screening of a Korean compound library

Abstract

The outbreak of coronavirus (CoV) disease 2019 (COVID-19) caused by the severe acute respiratory syndrome CoV-2 (SARS-CoV-2) has turned into a pandemic. The enzyme 3C-like protease (3CLpro) is essential for the maturation of viral polyproteins in SARS-CoV-2 and is therefore regarded as a key drug target for treating the disease. To identify 3CLpro inhibitors that can suppress SARS-CoV-2 replication, we performed a virtual screening of 500,282 compounds in a Korean compound bank. We then subjected the top computational hits to inhibitory assays against 3CLpro in vitro, leading to the identification of a class of non-covalent inhibitors. Among these inhibitors, compound 7 showed an EC50 of 39.89 μM against SARS-CoV-2 and CC50 of 453.5 μM. This study provides candidates for the optimization of potent 3CLpro inhibitors showing antiviral effects against SARS-CoV-2.

Keywords

SARS-CoV-2, Drug Evaluation, Preclinical, Microbial Sensitivity Tests, Antiviral Agents, Article, Molecular Docking Simulation, Small Molecule Libraries, Chlorocebus aethiops, Republic of Korea, Animals, Protease Inhibitors, Vero Cells, Coronavirus 3C Proteases, Protein Binding

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    9
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
Green
hybrid