About: A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19
Creator	Yang, Hui Xiao, Liang Zhu, Fengcai Chi, Ying Ge, Yiyue »more»
source	BioRxiv
abstract	The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19.
has issue date	2020-03-12(xsd:dateTime)
bibo:doi	10.1101/2020.03.11.986836
has license	biorxiv
sha1sum (hex)	d9c15766ee9c84d154c0f691fc42cbd847668193
schema:url	https://doi.org/10.1101/2020.03.11.986836
resource representing a document's title	A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19
schema:publication	bioRxiv
resource representing a document's body	covid:d9c15766ee9c84d154c0f691fc42cbd847668193#body_text
is schema:about of	named entity 'validation' named entity 'systematically' named entity 'toxicity' named entity 'literature' named entity 'high' »more»

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