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  1. National Taiwan Ocean University Research Hub
  2. 電機資訊學院
  3. 資訊工程學系
請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/19011
DC 欄位值語言
dc.contributor.authorYifei Wuen_US
dc.contributor.authorKuan Y. Changen_US
dc.contributor.authorLei Louen_US
dc.contributor.authorLorette G. Edwardsen_US
dc.contributor.authorBly K. Domaen_US
dc.contributor.authorZhong-Ru Xieen_US
dc.date.accessioned2021-12-09T06:34:28Z-
dc.date.available2021-12-09T06:34:28Z-
dc.date.issued2020-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/19011-
dc.description.abstractThe COVID-19 pandemic has caused unprecedented health and economic crisis throughout the world. However, there is no effective medication or therapeutic strategy for treatment of this disease currently. Here, to elucidate the inhibitory effects, we first tested binding affinities of 11 HIV-1 protease inhibitors or their pharmacoenhancers docked onto SARS-CoV-2 main protease (Mpro), and 12 nucleotide-analog inhibitors docked onto RNA dependent RNA polymerase (RdRp). To further obtain the effective drug candidates, we screened 728 approved drugs via virtual screening on SARS-CoV-2 Mpro. Our results demonstrate that remdesivir shows the best binding energy on RdRp and saquinvir is the best inhibitor of Mpro. Based on the binding energies, we also list 10 top-ranked approved drugs which can be potential inhibitors for Mpro. Overall, our results do not only propose drug candidates for further experiments and clinical trials but also pave the way for future lead optimization and drug design.en_US
dc.language.isoen_USen_US
dc.publisherELSEVIERen_US
dc.relation.ispartofInformatics in Medicine Unlockeden_US
dc.subjectCOVID-19en_US
dc.subjectLigand-protein dockingen_US
dc.subjectVirtual screeningen_US
dc.subjectRemdesiviren_US
dc.subjectDrug repurposingen_US
dc.subjectMain proteaseen_US
dc.subjectRNA-dependent RNA polymeraseen_US
dc.titleIn silico identification of drug candidates against COVID-19en_US
dc.typejournal articleen_US
dc.identifier.doi10.1016/j.imu.2020.100461-
dc.relation.journalvolume21en_US
item.fulltextno fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en_US-
item.openairetypejournal article-
crisitem.author.deptCollege of Electrical Engineering and Computer Science-
crisitem.author.deptDepartment of Computer Science and Engineering-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.orcid0000-0002-2262-5218-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Electrical Engineering and Computer Science-
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