[en] The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression datasets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis, and pyrimidine metabolism. By in silico screening of Food and Drug Administration (FDA)-approved drugs on the putative disease-specific essential genes and gene pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 (https://github.com/sysbiolux/DCcov).
Research center :
ULHPC - University of Luxembourg: High Performance Computing
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
KISHK, Ali ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
PIRES PACHECO, Maria Irene ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
SAUTER, Thomas ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
External co-authors :
no
Language :
English
Title :
DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling.
Publication date :
2021
Journal title :
iScience
eISSN :
2589-0042
Publisher :
Elsevier, Cambridge, United States - Massachusetts
Adhanom, T., WHO Director-General's Opening Remarks at the Media Briefing on COVID-19. 2020, World Health Organization https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19-11-march-2020.
Agren, R., Bordel, S., Mardinoglu, A., Pornputtapong, N., Nookaew, I., Nielsen, J., Reconstruction of genome-scale Active metabolic networks for 69 human cell types and 16 cancer types using INIT. PLoS Comput. Biol., 8, 2012, e1002518, 10.1371/journal.pcbi.1002518.
Akhter, J., Pillai, K., Badar, S., Mekkawy, A., Valle, S.J., Morris, D.L., In vitro study of BromAc on SARS-CoV-2 spike and envelope protein shows synergy and disintegration at modest concentrations. bioRxiv, 2020, 10.1101/2020.09.07.286906.
Aller, S., Scott, A., Sarkar-Tyson, M., Soyer, O.S., Integrated human-virus metabolic stoichiometric modelling predicts host-based antiviral targets against Chikungunya, Dengue and Zika viruses. J. R. Soc. Interf., 15, 2018, 20180125, 10.1098/rsif.2018.0125.
Andersen, K.G., Rambaut, A., Lipkin, W.I., Holmes, E.C., Garry, R.F., The proximal origin of SARS-CoV-2. Nat. Med. 26 (2020), 450–452, 10.1038/s41591-020-0820-9.
Bernardes, J.P., Mishra, N., Tran, F., Bahmer, T., Best, L., Blase, J.I., Bordoni, D., Franzenburg, J., Geisen, U., Josephs-Spaulding, J., et al. Longitudinal multi-omics analysis identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories. medRxiv, 2020, 10.1101/2020.09.11.20187369.
Blanco-Melo, D., Nilsson-Payant, B.E., Liu, W.-C., Uhl, S., Hoagland, D., Møller, R., Jordan, T.X., Oishi, K., Panis, M., Sachs, D., et al. Imbalanced host response to SARS-CoV-2 drives development of COVID-19. Cell 181 (2020), 1036–1045.e9, 10.1016/j.cell.2020.04.026.
Blätke, M.-A., Bräutigam, A., Evolution of C4 photosynthesis predicted by constraint-based modelling. eLife, 8, 2019, e49305, 10.7554/eLife.49305.
Bordbar, A., Lewis, N.E., Schellenberger, J., Palsson, B.Ø., Jamshidi, N., Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions. Mol. Syst. Biol., 6, 2010, 422, 10.1038/msb.2010.68.
Brenner, E.J., Ungaro, R.C., Gearry, R.B., Kaplan, G.G., Kissous-Hunt, M., Lewis, J.D., Ng, S.C., Rahier, J.-F., Reinisch, W., Ruemmele, F.M., et al. Corticosteroids, but not TNF antagonists, are associated with adverse COVID-19 outcomes in patients with inflammatory bowel diseases: results from an international registry. Gastroenterology 159 (2020), 481–491.e3, 10.1053/j.gastro.2020.05.032.
Brunk, E., Sahoo, S., Zielinski, D.C., Altunkaya, A., Dräger, A., Mih, N., Gatto, F., Nilsson, A., Preciat Gonzalez, G.A., Aurich, M.K., et al. Recon3D enables a three-dimensional view of gene variation in human metabolism. Nat. Biotechnol. 36 (2018), 272–281, 10.1038/nbt.4072.
Cañas, N., Valero, T., Villarroya, M., Montell, E., Vergés, J., García, A.G., López, M.G., Chondroitin sulfate protects SH-SY5Y cells from oxidative stress by inducing heme oxygenase-1 via phosphatidylinositol 3-kinase/Akt. J. Pharmacol. Exp. Ther. 323 (2007), 946–953, 10.1124/jpet.107.123505.
Clough, E., Barrett, T., The gene expression Omnibus database. Methods Mol. Biol. 1418 (2016), 93–110, 10.1007/978-1-4939-3578-9_5.
Coronavirus data download - targeting COVID-19 portal, https://ghddi-ailab.github.io/Targeting2019-nCoV/CoV_Experiment_Data/#broad-spectrum-antiviral-agents, 2020.
Corsello, S.M., Bittker, J.A., Liu, Z., Gould, J., McCarren, P., Hirschman, J.E., Johnston, S.E., Vrcic, A., Wong, B., Khan, M., et al. The drug repurposing hub: A next-generation drug library and information resource. Nat. Med. 23 (2017), 405–408, 10.1038/nm.4306.
Emanuel, W., Kirstin, M., Vedran, F., Asija, D., Theresa, G.L., Roberto, A., Filippos, K., David, K., Salah, A., Christopher, B., et al. Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention. bioRxiv, 2020, 10.1101/2020.05.05.079194.
Eslami, G., Mousaviasl, S., Radmanesh, E., Jelvay, S., Bitaraf, S., Simmons, B., Wentzel, H., Hill, A., Sadeghi, A., Freeman, J., et al. The impact of sofosbuvir/daclatasvir or ribavirin in patients with severe COVID-19. J. Antimicrob. Chemother. 75 (2020), 3366–3372, 10.1093/jac/dkaa331.
Fadini, G.P., Morieri, M.L., Longato, E., Avogaro, A., Prevalence and impact of diabetes among people infected with SARS-CoV-2. J. Endocrinol. Invest. 43 (2020), 867–869, 10.1007/s40618-020-01236-2.
Fung, M., Babik, J.M., COVID-19 in immunocompromised hosts: what we know so far. Clin. Infect. Dis. 72 (2020), 340–350, 10.1093/cid/ciaa863.
Gille, C., Bölling, C., Hoppe, A., Bulik, S., Hoffmann, S., Hübner, K., Karlstädt, A., Ganeshan, R., König, M., Rother, K., et al. HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. Mol. Syst. Biol., 6, 2010, 411, 10.1038/msb.2010.62.
Gordon, D.E., Jang, G.M., Bouhaddou, M., Xu, J., Obernier, K., White, K.M., O'Meara, M.J., Rezelj, V.V., Guo, J.Z., Swaney, D.L., et al. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 583 (2020), 459–468, 10.1038/s41586-020-2286-9.
Halpin, S.J., McIvor, C., Whyatt, G., Adams, A., Harvey, O., McLean, L., Walshaw, C., Kemp, S., Corrado, J., Singh, R., et al. Postdischarge symptoms and rehabilitation needs in survivors of COVID-19 infection: a cross-sectional evaluation. J. Med. Virol. 93 (2021), 1013–1022, 10.1002/jmv.26368.
Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S.N., Richelle, A., Heinken, A., Haraldsdóttir, H.S., Wachowiak, J., Keating, S.M., Vlasov, V., et al. Creation and analysis of biochemical constraint-based models using the COBRA toolbox v.3.0. Nat. Protoc. 14 (2019), 639–702, 10.1038/s41596-018-0098-2.
Hippisley-Cox, J., Young, D., Coupland, C., Channon, K.M., Tan, P.S., Harrison, D.A., Rowan, K., Aveyard, P., Pavord, I.D., Watkinson, P.J., Risk of severe COVID-19 disease with ACE inhibitors and angiotensin receptor blockers: cohort study including 8.3 million people. Heart 106 (2020), 1503–1511, 10.1136/heartjnl-2020-317393.
Hirsch, J.S., Ng, J.H., Ross, D.W., Sharma, P., Shah, H.H., Barnett, R.L., Hazzan, A.D., Fishbane, S., Jhaveri, K.D., Abate, M., et al. Acute kidney injury in patients hospitalized with COVID-19. Kidney Int. 98 (2020), 209–218, 10.1016/j.kint.2020.05.006.
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395 (2020), 497–506, 10.1016/S0140-6736(20)30183-5.
Huang, L., Shi, Y., Gong, B., Jiang, L., Zhang, Z., Liu, X., Yang, J., He, Y., Jiang, Z., Zhong, L., et al. Dynamic blood single-cell immune responses in patients with COVID-19. Signal Transduct. Target. Ther., 6, 2021, 110, 10.1038/s41392-021-00526-2.
Kanehisa, M., Goto, S., KEGG: kyoto Encyclopedia of genes and genomes. Nucleic Acids Res. 28 (2000), 27–30, 10.1093/nar/28.1.27.
Kragstrup, T.W., Singh, H.S., Grundberg, I., Nielsen, A.L.-L., Rivellese, F., Mehta, A., Goldberg, M.B., Filbin, M.R., Qvist, P., Bibby, B.M., Plasma ACE2 predicts outcome of COVID-19 in hospitalized patients. PLoS One, 16, 2021, e0252799, 10.1371/journal.pone.0252799.
Kronbichler, A., Kresse, D., Yoon, S., Lee, K.H., Effenberger, M., Shin, J.I., Asymptomatic patients as a source of COVID-19 infections: a systematic review and meta-analysis. Int. J. Infect. Dis. 98 (2020), 180–186, 10.1016/j.ijid.2020.06.052.
Kuleshov, M.V., Jones, M.R., Rouillard, A.D., Fernandez, N.F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S.L., Jagodnik, K.M., Lachmann, A., et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44 (2016), W90–W97, 10.1093/nar/gkw377.
Larsson, I., Uhlén, M., Zhang, C., Mardinoglu, A., Genome-scale metabolic modeling of glioblastoma reveals promising targets for drug development. Front. Genet., 11, 2020, 381, 10.3389/fgene.2020.00381.
Lê, S., Josse, J., Husson, F., FactoMineR: an R package for multivariate analysis. J. Stat. Softw. 25 (2008), 1–18, 10.18637/jss.v025.i01.
Li, X., Ma, X., Acute respiratory failure in COVID-19: is it “typical” ARDS?. Crit. Care, 24, 2020, 198, 10.1186/s13054-020-02911-9.
Love, M.I., Huber, W., Anders, S., Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol., 15, 2014, 550, 10.1186/s13059-014-0550-8.
Luban, J., Sattler, R., Mühlberger, E., Graci, J.D., Cao, L., Weetall, M., Trotta, C., Colacino, J.M., Bavari, S., Strambio-De-Castillia, C., et al. The DHODH inhibitor PTC299 arrests SARS-CoV-2 replication and suppresses induction of inflammatory cytokines. bioRxiv, 2020, 10.1101/2020.08.05.238394.
Marfia, G., Navone, S., Guarnaccia, L., Campanella, R., Mondoni, M., Locatelli, M., Barassi, A., Fontana, L., Palumbo, F., Garzia, E., et al. Serum Sphingosine-1-Phosphate as Novel Prognostic and Predictive Biomarker for COVID-19 Severity and Morbidity and its Implications in Clinical Management (SSRN Scholarly Paper No. ID 3668364). 2020, Social Science Research Network, 10.2139/ssrn.3668364.
Marinos, G., Kaleta, C., Waschina, S., Defining the nutritional input for genome-scale metabolic models: a roadmap. PLoS One, 15, 2020, e0236890, 10.1371/journal.pone.0236890.
McGuinness, G., Zhan, C., Rosenberg, N., Azour, L., Wickstrom, M., Mason, D.M., Thomas, K.M., Moore, W.H., High incidence of barotrauma in patients with COVID-19 infection on invasive mechanical ventilation. Radiology, 2020, 202352, 10.1148/radiol.2020202352.
Moeller, R., Zapatero-Belinchon, F.J., Lasswitz, L., Kirui, J., Brogden, G., Gunesch, A.P., Pietschmann, T., Wichmann, D., Kluge, S., Gerold, G., Effect of statins on SARS-CoV-2 infection. medRxiv, 2020, 10.1101/2020.07.13.20152272.
Moghaddam, A., Heller, R.A., Sun, Q., Seelig, J., Cherkezov, A., Seibert, L., Hackler, J., Seemann, P., Diegmann, J., Pilz, M., et al. Selenium deficiency is associated with mortality risk from COVID-19. Nutrients, 12, 2020, 2098, 10.3390/nu12072098.
Morawska, L., Cao, J., Airborne transmission of SARS-CoV-2: the world should face the reality. Environ. Int., 139, 2020, 105730, 10.1016/j.envint.2020.105730.
Morselli Gysi, D., do Valle, Í., Zitnik, M., Ameli, A., Gan, X., Varol, O., Ghiassian, S.D., Patten, J.J., Davey, R.A., Loscalzo, J., Barabási, A.-L., Network medicine framework for identifying drug-repurposing opportunities for COVID-19. Proc Natl Acad Sci USA, 118, 2021 e2025581118. https://doi.org/10.1073/pnas.2025581118.
Pacheco, M.P., John, E., Kaoma, T., Heinäniemi, M., Nicot, N., Vallar, L., Bueb, J.L., Sinkkonen, L., Sauter, T., Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network. BMC Genomics, 16, 2015, 809, 10.1186/s12864-015-1984-4.
Orth, J.D., Thiele, I., Palsson, B.Ø., What is flux balance analysis?. Nat. Biotechnol. 28 (2010), 245–248, 10.1038/nbt.1614.
Ostaszewski, M., Mazein, A., Gillespie, M.E., Kuperstein, I., Niarakis, A., Hermjakob, H., Pico, A.R., Willighagen, E.L., Evelo, C.T., Hasenauer, J., et al. COVID-19 disease map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms. Sci. Data, 7, 2020, 136, 10.1038/s41597-020-0477-8.
Pacheco, M.P., Bintener, T., Ternes, D., Kulms, D., Haan, S., Letellier, E., Sauter, T., Identifying and targeting cancer-specific metabolism with network-based drug target prediction. EBioMedicine 43 (2019), 98–106, 10.1016/j.ebiom.2019.04.046.
Panepinto, J.A., Brandow, A., Mucalo, L., Yusuf, F., Singh, A., Taylor, B., Woods, K., Payne, A.B., Peacock, G., Schieve, L.A., Coronavirus disease among persons with sickle cell disease, United States, March 20–may 21, 2020. Emerg. Infect. Dis. 26 (2020), 2473–2476, 10.3201/eid2610.202792.
Perumal, D., Samal, A., Sakharkar, K.R., Sakharkar, M.K., Targeting multiple targets in Pseudomonas aeruginosa PAO1 using flux balance analysis of a reconstructed genome-scale metabolic network. J. Drug Target. 19 (2011), 1–13, 10.3109/10611861003649753.
Petrilli, C.M., Jones, S.A., Yang, J., Rajagopalan, H., O'Donnell, L.F., Chernyak, Y., Tobin, K., Cerfolio, R.J., Francois, F., Horwitz, L.I., Factors associated with hospitalization and critical illness among 4,103 patients with COVID-19 disease in New York City. medRxiv, 2020, 10.1101/2020.04.08.20057794.
Puntmann, V.O., Carerj, M.L., Wieters, I., Fahim, M., Arendt, C., Hoffmann, J., Shchendrygina, A., Escher, F., Vasa-Nicotera, M., Zeiher, A.M., et al. Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from coronavirus disease 2019 (COVID-19). JAMA Cardiol. 5 (2020), 1265–1273, 10.1001/jamacardio.2020.3557.
Reed, J.L., Palsson, B.Ø., Thirteen years of building constraint-based in silico models of Escherichia coli. J. Bacteriol. 185 (2003), 2692–2699, 10.1128/JB.185.9.2692-2699.2003.
Reed, J.L., Vo, T.D., Schilling, C.H., Palsson, B.O., An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol., 4, 2003, R54.
Renz, A., Widerspick, L., Dräger, A., Genome-scale metabolic model of infection with SARS-CoV-2 mutants confirms guanylate kinase as robust potential antiviral target. Genes, 12, 2021, 796, 10.3390/genes12060796.
Renz, A., Widerspick, L., Dräger, A., FBA reveals guanylate kinase as a potential target for antiviral therapies against SARS-CoV-2. Zenodo, 2020, 10.5281/zenodo.3752641.
Robaina Estévez, S., Nikoloski, Z., Context-specific metabolic model extraction based on regularized least squares optimization. PLoS One, 10, 2015, e0131875, 10.1371/journal.pone.0131875.
Robinson, J.L., Kocabaş, P., Wang, H., Cholley, P.-E., Cook, D., Nilsson, A., Anton, M., Ferreira, R., Domenzain, I., Billa, V., et al. An atlas of human metabolism. Sci. Signal., 13, 2020, eaaz1482, 10.1126/scisignal.aaz1482.
Robinson, M.D., McCarthy, D.J., Smyth, G.K., edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26 (2009), 139–140, 10.1093/bioinformatics/btp616.
Rubino, F., Amiel, S.A., Zimmet, P., Alberti, G., Bornstein, S., Eckel, R.H., Mingrone, G., Boehm, B., Cooper, M.E., Chai, Z., et al. New-onset diabetes in covid-19. N. Engl. J. Med. 383 (2020), 789–791, 10.1056/NEJMc2018688.
Saha, R., Suthers, P.F., Maranas, C.D., Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism. PLoS One, 6, 2011, e21784, 10.1371/journal.pone.0021784.
Schellenberger, J., Que, R., Fleming, R.M.T., Thiele, I., Orth, J.D., Feist, A.M., Zielinski, D.C., Bordbar, A., Lewis, N.E., Rahmanian, S., et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat. Protoc. 6 (2011), 1290–1307, 10.1038/nprot.2011.308.
Schultz, D.C., Johnson, R.M., Ayyanathan, K., Miller, J., Whig, K., Kamalia, B., Dittmar, M., Weston, S., Hammond, H.L., Dillen, C., et al. Pyrimidine biosynthesis inhibitors synergize with nucleoside analogs to block SARS-CoV-2 infection. bioRxiv, 2021, 10.1101/2021.06.24.449811.
Sehm, T., Fan, Z., Ghoochani, A., Rauh, M., Engelhorn, T., Minakaki, G., Dörfler, A., Klucken, J., Buchfelder, M., Eyüpoglu, I.Y., Savaskan, N., Sulfasalazine impacts on ferroptotic cell death and alleviates the tumor microenvironment and glioma-induced brain edema. Oncotarget 7 (2016), 36021–36033, 10.18632/oncotarget.8651.
Sparks, M.A., Crowley, S.D., Gurley, S.B., Mirotsou, M., Coffman, T.M., Classical renin-angiotensin system in kidney physiology. Compr. Physiol. 4 (2014), 1201–1228, 10.1002/cphy.c130040.
Stegmann, K.M., Dickmanns, A., Gerber, S., Nikolova, V., Klemke, L., Manzini, V., Schlösser, D., Bierwirth, C., Freund, J., Sitte, M., et al. The folate antagonist methotrexate diminishes replication of the coronavirus SARS-CoV-2 and enhances the antiviral efficacy of remdesivir in cell culture models. bioRxiv, 2020, 10.1101/2020.07.18.210013.
Subir, R., Jagat J, M., Kalyan K, G., Pros and cons for use of statins in people with coronavirus disease-19 (COVID-19). Diabetes Metab. Syndr. Clin. Res. Rev. 14 (2020), 1225–1229, 10.1016/j.dsx.2020.07.011.
Swainston, N., Smallbone, K., Hefzi, H., Dobson, P.D., Brewer, J., Hanscho, M., Zielinski, D.C., Ang, K.S., Gardiner, N.J., Gutierrez, J.M., et al. Recon 2.2: from reconstruction to model of human metabolism. Metabolomics, 12, 2016, 109, 10.1007/s11306-016-1051-4.
Tandon, R., Sharp, J.S., Zhang, F., Pomin, V.H., Ashpole, N.M., Mitra, D., Jin, W., Liu, H., Sharma, P., Linhardt, R.J., Effective inhibition of SARS-CoV-2 entry by heparin and enoxaparin derivatives. bioRxiv, 2020, 10.1101/2020.06.08.140236.
Thiele, I., Swainston, N., Fleming, R.M.T., Hoppe, A., Sahoo, S., Aurich, M.K., Haraldsdottir, H., Mo, M.L., Rolfsson, O., Stobbe, M.D., et al. A community-driven global reconstruction of human metabolism. Nat. Biotechnol. 31 (2013), 419–425, 10.1038/nbt.2488.
Thomas, T., Stefanoni, D., Reisz, J.A., Nemkov, T., Bertolone, L., Francis, R.O., Hudson, K.E., Zimring, J.C., Hansen, K.C., Hod, E.A., et al. COVID-19 infection alters kynurenine and fatty acid metabolism, correlating with IL-6 levels and renal status. JCI Insight, 5, 2020, e140327, 10.1172/jci.insight.140327.
Toelzer, C., Gupta, K., Yadav, S.K.N., Borucu, U., Davidson, A.D., Kavanagh Williamson, M., Shoemark, D.K., Garzoni, F., Staufer, O., Milligan, R., et al. Free fatty acid binding pocket in the locked structure of SARS-CoV-2 spike protein. Science 370 (2020), 725–730, 10.1126/science.abd3255.
Tschopp, J., L'Huillier, A., Mombelli, M., Mueller, N., Khanna, N., Garzoni, C., Meloni, D., Papadimitriou-Olivgeris, M., Neofytos, D., Hirsch, H., et al. First experience of SARS-CoV-2 infections in solid organ transplant recipients in the Swiss Transplant Cohort Study. Am. J. Transpl. 20 (2020), 2876–2882, 10.1111/ajt.16062.
Varrette, S., Bouvry, P., Cartiaux, H., Georgatos, F., Management of an academic HPC cluster: the UL experience. 2014 International Conference on High Performance Computing Simulation (HPCS). Presented at the 2014 International Conference on High Performance Computing Simulation (HPCS), 2014, 959–967, 10.1109/HPCSim.2014.6903792.
Wishart, D.S., Feunang, Y.D., Guo, A.C., Lo, E.J., Marcu, A., Grant, J.R., Sajed, T., Johnson, D., Li, C., Sayeeda, Z., et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 46 (2018), D1074–D1082, 10.1093/nar/gkx1037.
Wu, T., Zuo, Z., Kang, S., Jiang, L., Luo, X., Xia, Z., Liu, J., Xiao, X., Ye, M., Deng, M., Multi-organ dysfunction in patients with COVID-19: a systematic review and meta-analysis. Aging Dis. 11 (2020), 874–894, 10.14336/AD.2020.0520.
Xiong, R., Zhang, L., Li, S., Sun, Y., Ding, M., Wang, Y., Zhao, Y., Wu, Y., Shang, W., Jiang, X., et al. Novel and potent inhibitors targeting DHODH are broad-spectrum antivirals against RNA viruses including newly-emerged coronavirus SARS-CoV-2. Protein Cell 11 (2020), 723–739, 10.1007/s13238-020-00768-w.
Yang, J., Zheng, Y., Gou, X., Pu, K., Chen, Z., Guo, Q., Ji, R., Wang, H., Wang, Y., Zhou, Y., Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int. J. Infect. Dis. 94 (2020), 91–95, 10.1016/j.ijid.2020.03.017.
Yizhak, K., Chaneton, B., Gottlieb, E., Ruppin, E., Modeling cancer metabolism on a genome scale. Mol. Syst. Biol., 11, 2015, 817, 10.15252/msb.20145307.
Zhang, J., Taylor, E.W., Bennett, K., Saad, R., Rayman, M.P., Association between regional selenium status and reported outcome of COVID-19 cases in China. Am. J. Clin. Nutr. 111 (2020), 1297–1299, 10.1093/ajcn/nqaa095.
Zhou, N., Bao, J., FerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis-disease associations. Database, 2020, 2020, 10.1093/database/baaa021.
Zimmerman, M.C., Lazartigues, E., Sharma, R.V., Davisson, R.L., Hypertension caused by angiotensin II infusion involves increased superoxide production in the central nervous system. Circ. Res. 95 (2004), 210–216, 10.1161/01.RES.0000135483.12297.e4.
