{"database":"Cell Collective","file_versions":[],"scores":null,"additional":{"omics_type":["Models"],"submitter":["Tomas Helikar"],"version_name":[""],"full_dataset_link":["https://cellcollective.org/#2172/cholesterol-regulatory-pathway"],"model_score":["8.2"],"default_version":["1"],"ModelFormat":["SBML"],"submitter_affiliation":[""],"submitter_email":[""],"version_id":["1"],"repository":["Cell Collective"],"version_url":["https://cellcollective.org/#2172:1/cholesterol-regulatory-pathway"],"version_description":[""],"pubmed_abstract":["<h4>Background</h4>Qualitative dynamics of small gene regulatory networks have been studied in quite some details both with synchronous and asynchronous analysis. However, both methods have their drawbacks: synchronous analysis leads to spurious attractors and asynchronous analysis lacks computational efficiency, which is a problem to simulate large networks. We addressed this question through the analysis of a major biosynthesis pathway. Indeed the cholesterol synthesis pathway plays a pivotal role in dislypidemia and, ultimately, in cancer through intermediates such as mevalonate, farnesyl pyrophosphate and geranyl geranyl pyrophosphate, but no dynamic model of this pathway has been proposed until now.<h4>Results</h4>We set up a computational framework to dynamically analyze large biological networks. This framework associates a classical and computationally efficient synchronous Boolean analysis with a newly introduced method based on Markov chains, which identifies spurious cycles among the results of the synchronous simulation. Based on this method, we present here the results of the analysis of the cholesterol biosynthesis pathway and its physiological regulation by the Sterol Response Element Binding Proteins (SREBPs), as well as the modeling of the action of statins, inhibitor drugs, on this pathway. The in silico experiments show the blockade of the cholesterol endogenous synthesis by statins and its regulation by SREPBs, in full agreement with the known biochemical features of the pathway.<h4>Conclusion</h4>We believe that the method described here to identify spurious cycles opens new routes to compute large and biologically relevant models, thanks to the computational efficiency of synchronous simulation. Furthermore, to the best of our knowledge, we present here the first dynamic systems biology model of the human cholesterol pathway and several of its key regulatory control elements, hoping it would provide a good basis to perform in silico experiments and confront the resulting properties with published and experimental data. The model of the cholesterol pathway and its regulation, along with Boolean formulae used for simulation are available on our web site http://Bioinformaticsu613.free.fr. Graphical results of the simulation are also shown online. The SBML model is available in the BioModels database http://www.ebi.ac.uk/biomodels/ with submission ID: MODEL0568648427."],"pubmed_title":["Dynamical modeling of the cholesterol regulatory pathway with Boolean networks."],"pubmed_authors":["Kervizic Gwenael G, Corcos Laurent L"],"description_synonyms":["Networks, IPP2A2, dmBest1, Product, determination, Mbp1, Tumor, Hydroxymethylglutaryl CoA Reductase Inhibitors, DmelCG6264, Social Controls, prevention, element, Productivity, 5730420M11Rik, Techniques, Circuit, Roles, Method, Pharmaceutical Product, Transcriptional Networks, Concepts, 17alpha)-cholest-5-en-3-ol, ARB, 3, Inhibitors, myd, prevention and control, Formal Social Controls, 14beta, IKKg, multicellular organismal biosynthetic process, KEY, Key, Transcriptional, DmelCG4063., SET, single-organism biosynthetic process, (3beta, Man (Taxonomy), reference sample, Biology, TAF-I, anabolism, (Z)-isomer, hypoplasia, Cholest-5-en-3beta-ol, Mbp-1, procedures, free, racemic mevalonate, Epicholesterol, (E)-isomer, DmelCG4299, Social, preventive measures, IGAAD, set, lithium salt, Methodological Studies, DmelCG10574, malignant neoplasm, HMG CoA Reductase Inhibitor, medicine, Pharmaceutical, Gene Network, cholesterol anabolism, Role Concepts, Malignancies, Tbl1, TBL1, Tumors, phapii, preventive therapy, CG6264, Process, gyltl1b-b, Modern, StF-IT-1, Procedure, results, Hydroxymethylglutaryl CoA Reductase Inhibitor, Pentanoic acid, DmIKKgamma, Role Concept, Benign, Statin, dIKK, MDDGA6, mKIAA0609, Kenny, Role, atomo, Pharmaceutic, Markov Chain, geranyl pyrophosphate, KIAA0609, atome, TU15B, region, farnesyl pyrophosphate, dBest1, Hydroxymethylglutaryl-Coenzyme A Inhibitors, fg, Acid, Epistemology, Hydroxymethylglutaryl CoA, gyltl1b, Element, Gene Circuit, HLA-DR-associated protein II, CG4063, DI-2, 5-dihydroxy-3-methyl-, I-2Dm, atoms, dbest1, mdc1d, IKK-gamma, expanded, Control, Benign Neoplasms, Methodological, CG4299, Controls, Methodological Study, E-2f, RS-mevalonate, human, E-2g, Statins, Malignant Neoplasms, experimental procedures, I-2PP1, Hydroxymethylglutaryl-CoA Inhibitors, MDC1D, TAF-IBETA, DmelCG16910, enr, Gene Modules, Regulatory Networks, enlarged, HMG-CoA, Markov Processes, TAF-Ibeta, rac-mevalonate, HMG-CoA Reductase Inhibitor, i2pp2a, Regulation, HMG-CoA Reductase Inhibitors, HMG-CoA Statins, humans, Z)-isomer, big, Regulations, Modules, Gene Regulatory, (+-)-mevalonate, human being, bioformation, Procedures, Tb11, experimental, Processes, Neoplasms, Benign Neoplasm, Gene, Mevalonic, Network, biosynthesis, HMG CoA Reductase, anon-WO0118547.380, Malignant, (E, dIKK-gamma, froggy, PHAPII, Gyltl1a, Human, FBXW4, large, method, reduced, Homo sapiens, Cholest-5-en-3-ol (3beta)-, (RS)-mevalonate, 14C-labeled, method used in an experiment, DmIKK-gamma, E)-isomer, Studies, Gene Products, Hydroxymethylglutaryl-CoA, Transcriptional Network, (Z, Mevalonate, neryl pyrophosphate, Gene Regulatory Network, tiny, dmIKKgamma, Hydroxymethylglutaryl-CoA Reductase Inhibitor, IKK[[gamma]], Technique, Man, Module, Drugs, mevalonic acid anion, Chain, Regulatory Network, Circuits, cholesterol synthesis, methods, Malignancy, formation, MDDGB6, VMD2, experimental section, Ebi, EBI, ipp2a2, cholesterol formation, inhibiteur, 2pp2a, LARGE, BMD, CG10574, synthesis, Study, Neoplasias, BPFD#36, Reductase Inhibitor, Reductase Inhibitors, Markov, drugs, 2PP2A, Hydroxymethylglutaryl-CoA Reductase, inhibidor, IKK, taf-ibeta, Hydroxymethylglutaryl-Coenzyme A, great, dSET, dSet, site, farnesylpyrophosphate, Preparation, elements, HMG CoA Reductase Inhibitors, atom, Controlled, Cancer, Pharmaceuticals, RP50, small, inhibitors, Products, Controlling, farnesyl diphosphate, Malignant Neoplasm, Formal Social Control, synthesize, Proteins, igaad, inhibitor, SMAP55, Markov Process, Medications, Gene Circuits, group, Concept, IKKgamma, HMG-CoA reductase inhibitors, MT, I-2PP2A, Social Control, chemical analysis, Dm I-2, Protein, Systems, I2PP2A, Neoplasm, atomus, cholesterol biosynthesis, background, techniques, Cholesterin, Data Base, Dbest, primary cancer, Chains, underdeveloped, Gene Module, ensemble, Pharmaceutic Preparations, best, Dmikkgamma, prophylaxis, Cancers, CG16910, malignant tumor, introduction, l(2)k16213, plan specification, Protein Gene Products, Drug, Gene Proteins, dSET/TAF-Ibeta, Preparations, 2610030F17Rik, HMG-CoA Reductase, HMG CoA, control, Gene Networks, Modern Man, regulation, assay, AA407739, Hydroxymethylglutaryl Coenzyme A, Pharmaceutical Products, SRE binding, BEST, Neoplasia, methodology, Pharmaceutical Preparation"],"pubmed_title_synonyms":["17alpha)-cholest-5-en-3-ol, Cholest-5-en-3beta-ol, (3beta, Cholesterin, Epicholesterol., Cholest-5-en-3-ol (3beta)-, 14beta"],"name_synonyms":["17alpha)-cholest-5-en-3-ol, Cholest-5-en-3beta-ol, (3beta, Cholesterin, Epicholesterol., Cholest-5-en-3-ol (3beta)-, 14beta"],"pubmed_abstract_synonyms":["Networks, IPP2A2, dmBest1, Product, determination, Feature, Mbp1, Tumor, Hydroxymethylglutaryl CoA Reductase Inhibitors, DmelCG6264, Social Controls, prevention, element, Productivity, 5730420M11Rik, Techniques, Generic Action, Circuit, Roles, Method, Pharmaceutical Product, Transcriptional Networks, Concepts, 17alpha)-cholest-5-en-3-ol, ARB, 3, Inhibitors, myd, prevention and control, Formal Social Controls, 14beta, IKKg, multicellular organismal biosynthetic process, KEY, Key, Transcriptional, DmelCG4063., SET, single-organism biosynthetic process, (3beta, Man (Taxonomy), reference sample, Biology, TAF-I, anabolism, (Z)-isomer, hypoplasia, Cholest-5-en-3beta-ol, Mbp-1, procedures, free, racemic mevalonate, Epicholesterol, (E)-isomer, DmelCG4299, Social, preventive measures, IGAAD, set, lithium salt, Methodological Studies, DmelCG10574, malignant neoplasm, HMG CoA Reductase Inhibitor, medicine, Pharmaceutical, Gene Network, cholesterol anabolism, Role Concepts, Malignancies, Tbl1, TBL1, Tumors, phapii, preventive therapy, CG6264, Process, gyltl1b-b, Modern, StF-IT-1, Procedure, results, Hydroxymethylglutaryl CoA Reductase Inhibitor, Pentanoic acid, DmIKKgamma, Role Concept, Benign, Statin, dIKK, MDDGA6, mKIAA0609, Kenny, Role, atomo, Pharmaceutic, Markov Chain, geranyl pyrophosphate, KIAA0609, atome, TU15B, region, farnesyl pyrophosphate, dBest1, Hydroxymethylglutaryl-Coenzyme A Inhibitors, fg, Acid, Action, Epistemology, Hydroxymethylglutaryl CoA, gyltl1b, Element, Gene Circuit, HLA-DR-associated protein II, CG4063, DI-2, 5-dihydroxy-3-methyl-, I-2Dm, atoms, dbest1, mdc1d, IKK-gamma, expanded, Control, Benign Neoplasms, Methodological, CG4299, Controls, Features, Methodological Study, E-2f, RS-mevalonate, human, E-2g, Statins, Malignant Neoplasms, I-2PP1, Hydroxymethylglutaryl-CoA Inhibitors, MDC1D, TAF-IBETA, DmelCG16910, enr, Gene Modules, Regulatory Networks, enlarged, HMG-CoA, Markov Processes, TAF-Ibeta, rac-mevalonate, HMG-CoA Reductase Inhibitor, i2pp2a, Regulation, HMG-CoA Reductase Inhibitors, HMG-CoA Statins, humans, Z)-isomer, big, Regulations, Modules, Gene Regulatory, (+-)-mevalonate, human being, bioformation, Procedures, Tb11, Processes, Neoplasms, Benign Neoplasm, Gene, Mevalonic, Network, biosynthesis, HMG CoA Reductase, anon-WO0118547.380, Malignant, (E, dIKK-gamma, froggy, PHAPII, Gyltl1a, Human, FBXW4, large, method, reduced, Homo sapiens, Cholest-5-en-3-ol (3beta)-, (RS)-mevalonate, 14C-labeled, method used in an experiment, DmIKK-gamma, E)-isomer, Studies, Gene Products, Hydroxymethylglutaryl-CoA, Transcriptional Network, (Z, Mevalonate, neryl pyrophosphate, Gene Regulatory Network, tiny, dmIKKgamma, Hydroxymethylglutaryl-CoA Reductase Inhibitor, IKK[[gamma]], Technique, Man, Module, Drugs, mevalonic acid anion, Chain, Regulatory Network, Circuits, cholesterol synthesis, Malignancy, formation, MDDGB6, VMD2, Ebi, EBI, ipp2a2, cholesterol formation, inhibiteur, 2pp2a, LARGE, BMD, CG10574, synthesis, Study, Neoplasias, BPFD#36, Reductase Inhibitor, Reductase Inhibitors, Markov, drugs, 2PP2A, Hydroxymethylglutaryl-CoA Reductase, inhibidor, IKK, taf-ibeta, Hydroxymethylglutaryl-Coenzyme A, great, dSET, dSet, site, farnesylpyrophosphate, Characteristics, Preparation, elements, HMG CoA Reductase Inhibitors, atom, Controlled, Cancer, Pharmaceuticals, RP50, small, inhibitors, Products, Controlling, farnesyl diphosphate, Malignant Neoplasm, Formal Social Control, synthesize, Proteins, igaad, inhibitor, SMAP55, Markov Process, Medications, Gene Circuits, group, Concept, IKKgamma, HMG-CoA reductase inhibitors, MT, Characteristic, I-2PP2A, Social Control, chemical analysis, Dm I-2, Protein, Systems, I2PP2A, Neoplasm, atomus, cholesterol biosynthesis, background, techniques, Cholesterin, Data Base, Dbest, primary cancer, Chains, underdeveloped, Gene Module, ensemble, Pharmaceutic Preparations, best, Dmikkgamma, prophylaxis, Cancers, CG16910, malignant tumor, introduction, l(2)k16213, plan specification, Protein Gene Products, Drug, Gene Proteins, dSET/TAF-Ibeta, Preparations, 2610030F17Rik, HMG-CoA Reductase, HMG CoA, control, Gene Networks, Modern Man, regulation, assay, AA407739, Hydroxymethylglutaryl Coenzyme A, Pharmaceutical Products, SRE binding, BEST, Neoplasia, methodology, Pharmaceutical Preparation"],"additional_accession":[]},"is_claimable":false,"name":"Cholesterol Regulatory Pathway","description":"BACKGROUND: Qualitative dynamics of small gene regulatory networks have been studied in quite some details both with synchronous and asynchronous analysis. However, both methods have their drawbacks: synchronous analysis leads to spurious attractors and asynchronous analysis lacks computational efficiency, which is a problem to simulate large networks. We addressed this question through the analysis of a major biosynthesis pathway. Indeed the cholesterol synthesis pathway plays a pivotal role in dislypidemia and, ultimately, in cancer through intermediates such as mevalonate, farnesyl pyrophosphate and geranyl geranyl pyrophosphate, but no dynamic model of this pathway has been proposed until now. RESULTS: We set up a computational framework to dynamically analyze large biological networks. This framework associates a classical and computationally efficient synchronous Boolean analysis with a newly introduced method based on Markov chains, which identifies spurious cycles among the results of the synchronous simulation. Based on this method, we present here the results of the analysis of the cholesterol biosynthesis pathway and its physiological regulation by the Sterol Response Element Binding Proteins (SREBPs), as well as the modeling of the action of statins, inhibitor drugs, on this pathway. The in silico experiments show the blockade of the cholesterol endogenous synthesis by statins and its regulation by SREPBs, in full agreement with the known biochemical features of the pathway. CONCLUSION: We believe that the method described here to identify spurious cycles opens new routes to compute large and biologically relevant models, thanks to the computational efficiency of synchronous simulation. Furthermore, to the best of our knowledge, we present here the first dynamic systems biology model of the human cholesterol pathway and several of its key regulatory control elements, hoping it would provide a good basis to perform in silico experiments and confront the resulting properties with published and experimental data. The model of the cholesterol pathway and its regulation, along with Boolean formulae used for simulation are available on our web site http://Bioinformaticsu613.free.fr. Graphical results of the simulation are also shown online. The SBML model is available in the BioModels database http://www.ebi.ac.uk/biomodels/ with submission ID: MODEL0568648427.","dates":{"created":"2013-06-24","publication":"","submission":"2016-01-23","last_modified":"2016-01-23"},"accession":"2172","cross_references":{"pubmed":["19025648"]}}