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dc.contributor.authorLiu, Sen
dc.contributor.authorZheng, Qiang
dc.contributor.authorWang, Zhiying
dc.date.accessioned2020-04-07T20:40:05Z
dc.date.available2020-04-07T20:40:05Z
dc.date.issued2020-04-01
dc.identifier.urihttps://doi.org/10.1093/bioinformatics/btaa224en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12663/956
dc.description.abstractMotivation: Since December 2019, the newly identified coronavirus SARS-CoV-2 has caused a massive health crisis worldwide and resulted in over 70,000 COVID-19 infections so far. Clinical drugs targeting SARS-CoV-2 are urgently needed to decrease the high fatality rate of confirmed COVID-19 patients. Traditional de novo drug discovery needs more than 10 years, so drug repurposing seems the best option currently to find potential drugs for treating COVID-19. Results: Compared with traditional non-covalent drugs, covalent drugs have attracted escalating attention recent years due to their advantages in potential specificity upon careful design, efficiency, and patient burden. We recently developed a computational protocol named as SCAR for discovering covalent drugs. In this work, we used the SCAR protocol to identify possible covalent drugs (approved or clinically tested) targeting the main protease (3CLpro) of SARS-CoV-2. We identified 11 potential hits, among which at least 6 hits were exclusively enriched by the SCAR protocol. Since the preclinical or clinical information of these identified drugs is already available, they might be ready for being clinically tested in the treatment of COVID-19.en_US
dc.languageEnglishen_US
dc.subjectCOVID-19en_US
dc.subjectCoronavirusen_US
dc.subjectInfectious Diseasesen_US
dc.subjectPharmaceutical Preparationsen_US
dc.titlePotential covalent drugs targeting the main protease of the SARS-CoV-2 coronavirusen_US
eihealth.countryOthersen_US
eihealth.categoryEpidemiology and epidemiological studiesen_US
eihealth.typeOther publicationsen_US
eihealth.maincategorySave Lives / Salvar Vidasen_US
dc.relation.ispartofjournalBioinformaticsen_US


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