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Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods

Identifieur interne : 000997 ( 2020/Analysis ); précédent : 000996; suivant : 000998

Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods

Auteurs : Canrong Wu [République populaire de Chine] ; Yang Liu [République populaire de Chine] ; Yueying Yang [République populaire de Chine] ; Peng Zhang [République populaire de Chine] ; Wu Zhong [République populaire de Chine] ; Yali Wang [République populaire de Chine] ; Qiqi Wang [République populaire de Chine] ; Yang Xu [République populaire de Chine] ; Mingxue Li [République populaire de Chine] ; Xingzhou Li [République populaire de Chine] ; Mengzhu Zheng [République populaire de Chine] ; Lixia Chen [République populaire de Chine] ; Hua Li [République populaire de Chine]

Source :

RBID : PMC:7102550

Abstract

SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.


Url:
DOI: 10.1016/j.apsb.2020.02.008
PubMed: 32292689
PubMed Central: 7102550


Affiliations:


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PMC:7102550

Le document en format XML

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<name sortKey="Wang, Yali" sort="Wang, Yali" uniqKey="Wang Y" first="Yali" last="Wang">Yali Wang</name>
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<nlm:aff id="aff2">Wuya College of Innovation, Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, China</nlm:aff>
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<wicri:regionArea>Wuya College of Innovation, Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016</wicri:regionArea>
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<name sortKey="Wang, Qiqi" sort="Wang, Qiqi" uniqKey="Wang Q" first="Qiqi" last="Wang">Qiqi Wang</name>
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<name sortKey="Xu, Yang" sort="Xu, Yang" uniqKey="Xu Y" first="Yang" last="Xu">Yang Xu</name>
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<name sortKey="Li, Mingxue" sort="Li, Mingxue" uniqKey="Li M" first="Mingxue" last="Li">Mingxue Li</name>
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<name sortKey="Li, Xingzhou" sort="Li, Xingzhou" uniqKey="Li X" first="Xingzhou" last="Li">Xingzhou Li</name>
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</placeName>
</affiliation>
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<name sortKey="Zheng, Mengzhu" sort="Zheng, Mengzhu" uniqKey="Zheng M" first="Mengzhu" last="Zheng">Mengzhu Zheng</name>
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<name sortKey="Chen, Lixia" sort="Chen, Lixia" uniqKey="Chen L" first="Lixia" last="Chen">Lixia Chen</name>
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<author>
<name sortKey="Li, Hua" sort="Li, Hua" uniqKey="Li H" first="Hua" last="Li">Hua Li</name>
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<series>
<title level="j">Acta Pharmaceutica Sinica. B</title>
<idno type="ISSN">2211-3835</idno>
<idno type="eISSN">2211-3843</idno>
<imprint>
<date when="2020">2020</date>
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<div type="abstract" xml:lang="en">
<p>SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further
<italic>in vitro</italic>
and
<italic>in vivo</italic>
studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.</p>
</div>
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</TEI>
<affiliations>
<list>
<country>
<li>République populaire de Chine</li>
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<region>
<li>Hubei</li>
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<settlement>
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</tree>
</affiliations>
</record>

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