About: Repositioning of 8565 Existing Drugs for COVID-19

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Repositioning of 8565 Existing Drugs for COVID-19
Creator	Wang, Rui Chen, Jiahui Gao, Kaifu Duy, Duc Id, Guo-Wei Id, Nguyen
Source	Medline; PMC
abstract	[Image: see text] The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 7.1 million people and led to over 0.4 million deaths. Currently, there is no specific anti-SARS-CoV-2 medication. New drug discovery typically takes more than 10 years. Drug repositioning becomes one of the most feasible approaches for combating COVID-19. This work curates the largest available experimental data set for SARS-CoV-2 or SARS-CoV 3CL (main) protease inhibitors. On the basis of this data set, we develop validated machine learning models with relatively low root-mean-square error to screen 1553 FDA-approved drugs as well as another 7012 investigational or off-market drugs in DrugBank. We found that many existing drugs might be potentially potent to SARS-CoV-2. The druggability of many potent SARS-CoV-2 3CL protease inhibitors is analyzed. This work offers a foundation for further experimental studies of COVID-19 drug repositioning.
has issue date	2020-06-16(xsd:dateTime)
bibo:doi	10.1021/acs.jpclett.0c01579
bibo:pmid	32543196
has license	no-cc
sha1sum (hex)	8591bddddb70ee839f07aea29e1b5b87fddfabe3
schema:url	https://doi.org/10.1021/acs.jpclett.0c01579
resource representing a document's title	Repositioning of 8565 Existing Drugs for COVID-19
has PubMed Central identifier	PMC7313673
has PubMed identifier	32543196
schema:publication	J Phys Chem Lett
resource representing a document's body	covid:8591bddddb70ee839f07aea29e1b5b87fddfabe3#body_text
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