An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19
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Abstract
The global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires an urgent need to find effective therapeutics for the treatment of coronavirus disease 2019 (COVID-19). In this study, we developed an integrative drug repositioning framework, which fully takes advantage of 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. 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 can interact with the nucleocapsid (N) protein of SARS-CoV-2 and is able to suppress the LPS-induced production of several inflammatory cytokines that are highly relevant to the prevention of immunopathology induced by SARS-CoV-2 infection.
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SciScore for 10.1101/2020.03.11.986836: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources The cells were further incubated with a rabbit polyclonal antibody against a SARS-CoV nucleocapsid protein (Cambridgebio, USA) as primary antibody at a dilution of 1:200 for 2 h, followed by incubation with the secondary Alexa 488-labeled goat anti-rabbit antibody (Beyotime, China) at a dilution of 1:500. SARS-CoV nucleocapsid proteinsuggested: (Creative Diagnostics Cat# DMAB8869, RRID:AB_2392503)anti-rabbitsuggested: NoneThe blot was probed with the antibody against the viral nucleocapsid protein (Cambridgebio, USA) and the horseradish peroxidase-conjugated Goat Anti-Rabbit IgG (Abcam, USA) as the … SciScore for 10.1101/2020.03.11.986836: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources The cells were further incubated with a rabbit polyclonal antibody against a SARS-CoV nucleocapsid protein (Cambridgebio, USA) as primary antibody at a dilution of 1:200 for 2 h, followed by incubation with the secondary Alexa 488-labeled goat anti-rabbit antibody (Beyotime, China) at a dilution of 1:500. SARS-CoV nucleocapsid proteinsuggested: (Creative Diagnostics Cat# DMAB8869, RRID:AB_2392503)anti-rabbitsuggested: NoneThe blot was probed with the antibody against the viral nucleocapsid protein (Cambridgebio, USA) and the horseradish peroxidase-conjugated Goat Anti-Rabbit IgG (Abcam, USA) as the primary and the secondary antibodies, respectively. Anti-Rabbit IgGsuggested: NoneExperimental Models: Cell Lines Sentences Resources Indirect immunofluorescence assay: Vero E6 cells were treated with CVL218 at 5 µM, 15 µM and 25 µM, respectively, following the same procedure of “full-time” treatment. Vero E6suggested: RRID:CVCL_XD71)Experimental Models: Organisms/Strains Sentences Resources Pharmacokinetics and toxicity study: Sprague-Dawley rats were purchased from Shanghai Laboratory Animal Center, China. Sprague-Dawleysuggested: RRID:RGD_70508)Software and Algorithms Sentences Resources The virus target-drug interaction network was constructed from the integrated data from DrugBank (version 5.1.0) [17], ChEMBL (release 26) [54], TTD (last update 11 Nov, 2019) [55], IUPHAR BPS (release 13, Nov, 2019) [56], BindindDB [57] and GHDDI (https://ghddi-ailab.github.io/Targeting2019-nCoV/CoV_Experiment_Data/), with a cut-off threshold of IC50/EC50/Ki/Kd <10 µM. DrugBanksuggested: (DrugBank, RRID:SCR_002700)ChEMBLsuggested: (ChEMBL, RRID:SCR_014042)The human protein-protein interaction network and the virus protein-human protein interaction network were constructed from the integrated data from BioGRID (release 3.5.181) [58], HuRI [59], Instruct [60], MINT (2012 update) [61], PINA (V2.0) [62], SignaLink (V2.0) [63] and innatedb [64]. BioGRIDsuggested: (BioGrid Australia, RRID:SCR_006334)MINTsuggested: (MINT, RRID:SCR_001523)SignaLinksuggested: (SignaLink, RRID:SCR_003569)Noted that we collected additional protein sequences of SARS-CoV-2 from UniProt [66] and added them into the corresponding networks for the final prediction. UniProtsuggested: (UniProtKB, RRID:SCR_004426)The training corpus we used was curated automatically from nearly 20 million PubMed (http://www.pubmed.gov) abstracts by a distant supervision technique [75]. PubMedsuggested: (PubMed, RRID:SCR_004846)We used the connectivity map (CMap) [5], which contains the cellular gene expression profiles under the perturbation of 2428 well annotated reference compounds, to measure the associations of gene expression patterns between SARS-CoV infected patients and the reference compound-perturbed cells. CMapsuggested: (CMAP, RRID:SCR_009034)The dose-response curves were plotted according to viral RNA copies and the drug concentrations using GraphPad Prism (GraphPad Software, USA). 4.9. GraphPad Prismsuggested: (GraphPad Prism, RRID:SCR_002798)The plasma concentration-time data were analyzed using a non-compartmental method (Phoenix, version 1.3, USA) to derive the pharmacokinetic parameters. 4.14. Phoenixsuggested: (Phoenix, RRID:SCR_003163)The figures were prepared using GraphPad Prism (GraphPad Software, USA). GraphPadsuggested: (GraphPad Prism, RRID:SCR_002798)The statistical significance was calculated by SPSS (ver.12), and two values were considered significantly different if the p-value is < 0.05. 4.17. SPSSsuggested: (SPSS, RRID:SCR_002865)The AutoGrid program was used to generate a grid map with 60×60×60 points spaced equally at 0.375 Å for evaluating the binding energies between the protein and the ligands. AutoGridsuggested: (Autogrid, RRID:SCR_015982)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04257656 Terminated A Trial of Remdesivir in Adults With Severe COVID-19 Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
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- No protocol registration statement was detected.
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