{"database":"BioModels","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Xml":["https://www.ebi.ac.uk/biomodels/model/download/MODEL1912100004?filename=Nguyen2013_HIF.xml"],"Other":["https://www.ebi.ac.uk/biomodels/model/download/MODEL1912100004?filename=Nguyen2013_HIF.sedml","https://www.ebi.ac.uk/biomodels/model/download/MODEL1912100004?filename=Nguyen2013_HIF.cps"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"submitter":["Krishna Kumar Tiwari"],"curationStatus":["Non-curated"],"modellingApproach":["ordinary differential equation model"],"levelVersion":["L2V4"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/MODEL1912100004"],"publication_pubmed":["23390316"],"isPrivate":["false"],"repository":["BioModels"],"modelFormat":["SBML"],"omics_type":["Models"],"tokenised_name":["Nguyen2013   Dynamic model of HIF regulation in hypoxia"],"publication_year":["2013"],"submissionId":["MODEL1912100004"],"publication_authors":["Lan K Nguyen, Miguel A S Cavadas, Carsten C Scholz, Susan F Fitzpatrick, Ulrike Bruning, Eoin P Cummins, Murtaza M Tambuwala, Mario C Manresa, B N Kholodenko, Cormac T Taylor, Alex Cheong"],"first_author":["Lan K Nguyen"],"publication":["23390316,\n                            Activation of the hypoxia-inducible factor (HIF) pathway is a critical step in the transcriptional response to hypoxia. Although many of the key proteins involved have been characterised, the dynamics of their interactions in generating this response remain unclear. In the present study, we have generated a comprehensive mathematical model of the HIF-1α pathway based on core validated components and dynamic experimental data, and confirm the previously described connections within the predicted network topology. Our model confirms previous work demonstrating that the steps leading to optimal HIF-1α transcriptional activity require sequential inhibition of both prolyl- and asparaginyl-hydroxylases. We predict from our model (and confirm experimentally) that there is residual activity of the asparaginyl-hydroxylase FIH (factor inhibiting HIF) at low oxygen tension. Furthermore, silencing FIH under conditions where prolyl-hydroxylases are inhibited results in increased HIF-1α transcriptional activity, but paradoxically decreases HIF-1α stability. Using a core module of the HIF network and mathematical proof supported by experimental data, we propose that asparaginyl hydroxylation confers a degree of resistance upon HIF-1α to proteosomal degradation. Thus, through in vitro experimental data and in silico predictions, we provide a comprehensive model of the dynamic regulation of HIF-1α transcriptional activity by hydroxylases and use its predictive and adaptive properties to explain counter-intuitive biological observations.. Pt 6, 126.\n                            Systems Biology Ireland, University College Dublin, Dublin 4, Ireland."],"submitter_mail":["ktiwari@ebi.ac.uk"],"submitter_affiliation":["EMBL-EBI"],"pubmed_abstract":["Activation of the hypoxia-inducible factor (HIF) pathway is a critical step in the transcriptional response to hypoxia. Although many of the key proteins involved have been characterised, the dynamics of their interactions in generating this response remain unclear. In the present study, we have generated a comprehensive mathematical model of the HIF-1α pathway based on core validated components and dynamic experimental data, and confirm the previously described connections within the predicted network topology. Our model confirms previous work demonstrating that the steps leading to optimal HIF-1α transcriptional activity require sequential inhibition of both prolyl- and asparaginyl-hydroxylases. We predict from our model (and confirm experimentally) that there is residual activity of the asparaginyl-hydroxylase FIH (factor inhibiting HIF) at low oxygen tension. Furthermore, silencing FIH under conditions where prolyl-hydroxylases are inhibited results in increased HIF-1α transcriptional activity, but paradoxically decreases HIF-1α stability. Using a core module of the HIF network and mathematical proof supported by experimental data, we propose that asparaginyl hydroxylation confers a degree of resistance upon HIF-1α to proteosomal degradation. Thus, through in vitro experimental data and in silico predictions, we provide a comprehensive model of the dynamic regulation of HIF-1α transcriptional activity by hydroxylases and use its predictive and adaptive properties to explain counter-intuitive biological observations."],"pubmed_title":["A dynamic model of the hypoxia-inducible factor 1α (HIF-1α) network."],"pubmed_authors":["Nguyen Lan K LK, Cavadas Miguel A S MA, Scholz Carsten C CC, Fitzpatrick Susan F SF, Bruning Ulrike U, Cummins Eoin P EP, Tambuwala Murtaza M MM, Manresa Mario C MC, Kholodenko Boris N BN, Taylor Cormac T CT, Cheong Alex A"],"description_synonyms":["Regulations, Oxygen 16, experimental, Formal Social Control, familial, hypoparathyroidism familial isolated, E-948, NSHPT, 8O, autosomal dominant, GPRC2A, oxygen, Social Controls, dioxygene, Social Control, hypoparathyroidism, Sauerstoff, oxigeno, 2310046M24Rik, CAR, oxygene, E948, Formal Social Controls, OXYGEN MOLECULE, autosomal recessive, familial isolated hypoparathyroidism, HHC, O2, Disauerstoff, dioxygen, methods, FHH, PCAR1, FIH1, experimental section, O, Oxygen-16, hypothesis., Control, EIG8, A830014H24Rik, Controls, experimental procedures, Social, Familial Isolated Hypoparathyroidism, Oxygen, familial isolated, FIH, [OO], HHC1, regulation, HYPOC1, E 948, Regulation, molecular oxygen, Dioxygen"],"name_synonyms":["Social, Regulations, Oxygen Deficiency, Oxygen Deficiencies, Oxygen, Anoxia, Deficiency, Social Control, Formal Social Control, Deficiencies, Control, Hypoxemia, regulation, Hypoxia., Anoxemia, Controls, Regulation, Formal Social Controls, Social Controls"],"pubmed_abstract_synonyms":["biochemical pathways, Regulations, GRP1/cytohesin 1, degree (angle), Activity, Experimental Models, Theoretical Model, Deficiencies, Gene, NSHPT, autosomal dominant, GPRC2A, supernumerary, dIKK-gamma, cellular catabolism, Theoretical, Social Controls, Mathematical Models, Oxygen Deficiency, Oxygen Deficiencies, CG11633, cytohesin/GRP1, hydroxylation, GRP1, DmIKK-gamma, responsivity, Grp1, resistance, Gene Products, Studies, Experimental Model, cellular degradation, Low, dmIKKgamma, IKK[[gamma]], Hypoxia, response to intermittent hypoxia, Models, Formal Social Controls, IKKg, KEY, Key, reactivity, study, HHC, increased, me75, Theoretical Study, breakdown of chemical, catabolism, PTPSTEP, General activity., l(2)SH2 0323, EIG8, Theoretic, D17Mit170, T1, Familial Isolated Hypoparathyroidism, Social, Study, Oxygen, familial isolated, Neural-specific protein-tyrosine phosphatase, IKK, Mathematical, l(2)k08110, HHC1, response to sustained hypoxia, biotransformation, Model, GPH, cellular breakdown, cou, degradation, Formal Social Control, Proteins, familial, hypoparathyroidism familial isolated, stepk, Model (Theoretical), Tl3, Tl2, results, predicted, Anoxia, IKKgamma, DmIKKgamma, Experimental, Lr, hypoparathyroidism, Social Control, dIKK, Protein, Theoretical Studies, 3.1.3.48, Kenny, 2310046M24Rik, core, PaO2, secretion, CAR, Hydroxylations, l(2)SH0323, activation, autosomal recessive, familial isolated hypoparathyroidism, breakdown of molecule, CYH1, FHH, biodegradation, Step, CG11628, PCAR1, Dmikkgamma, FIH1, increased number, IKK-gamma, Control, Hypoxemia, oxygen tension, Striatum-enriched protein-tyrosine phosphatase, A830014H24Rik, arc degree, Controls, CG16910, DmelCG11628, Theoretical Models, Protein Gene Products, Gene Proteins, present in greater numbers in organism, Models (Theoretical), FIH, breakdown of substance, Deficiency, DmelCG16910, STEP, Bra, regulation, response, HYPOC1, Anoxemia, Regulation, Mathematical Model, General activity, accessory"],"pubmed_title_synonyms":["Deficiencies, Oxygen Deficiency, Oxygen Deficiencies, Oxygen, Hypoxemia, Anoxia, Deficiency, Hypoxia., Anoxemia"],"additional_accession":[]},"is_claimable":false,"name":"Nguyen2013 - Dynamic model of HIF regulation in hypoxia","description":"\n      \n        Its a mathematcial model explaining regulation of HIF via FIH and oxygen. Model is further validated by Experimental data and various hypothesis has been tested on the same.\n      \n    ","dates":{"last_modification":"2019-12-10","publication":"2019-12-10","submission":"2019-12-10"},"accession":"MODEL1912100004","cross_references":{"pubmed":["23390316"],"taxonomy":["9606"]}}