<HashMap><database>BioModels</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Pdf>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.pdf</Pdf><Owl>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644-biopax2.owl</Owl><Owl>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644-biopax3.owl</Owl><Svg>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.svg</Svg><Xml>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644_url.xml</Xml><Xml>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644_urn.xml</Xml><Other>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.vcml</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.m</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.xpp</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.sci</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/MODEL0995500644?filename=MODEL0995500644.png</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><submitter>Harish Dharuri</submitter><curationStatus>Non-curated</curationStatus><modellingApproach>ordinary differential equation model</modellingApproach><levelVersion>L2V1</levelVersion><full_dataset_link>https://www.ebi.ac.uk/biomodels/MODEL0995500644</full_dataset_link><publication_pubmed>15784266</publication_pubmed><isPrivate>false</isPrivate><repository>BioModels</repository><modelFormat>SBML</modelFormat><omics_type>Models</omics_type><tokenised_name>Rodriguez2005 denovo pyrimidine biosynthesis</tokenised_name><publication_year>2005</publication_year><submissionId>MODEL0995500644</submissionId><modelFlag>Non Miriam</modelFlag><publication_authors>Mauricio Rodríguez, Theresa A Good, Melinda E Wales, Jean P Hua, James R Wild</publication_authors><first_author>Mauricio Rodríguez</first_author><publication>15784266,
                            With the emergence of multifaceted bioinformatics-derived data, it is becoming possible to merge biochemical and physiological information to develop a new level of understanding of the metabolic complexity of the cell. The biosynthetic pathway of de novo pyrimidine nucleotide metabolism is an essential capability of all free-living cells, and it occupies a pivotal position relative to metabolic processes that are involved in the macromolecular synthesis of DNA, RNA and proteins, as well as energy production and cell division. This regulatory network in all enteric bacteria involves genetic, allosteric, and physiological control systems that need to be integrated into a coordinated set of metabolic checks and balances. Allosterically regulated pathways constitute an exciting and challenging biosynthetic system to be approached from a mathematical perspective. However, to date, a mathematical model quantifying the contribution of allostery in controlling the dynamics of metabolic pathways has not been proposed. In this study, a direct, rigorous mathematical model of the de novo biosynthesis of pyrimidine nucleotides is presented. We corroborate the simulations with experimental data available in the literature and validate it with derepression experiments done in our laboratory. The model is able to faithfully represent the dynamic changes in the intracellular nucleotide pools that occur during metabolic transitions of the de novo pyrimidine biosynthetic pathway and represents a step forward in understanding the role of allosteric regulation in metabolic control.. 3, 234.
                            Department of Biochemistry and Biophysics, Texas A&amp;M University, 2128 TAMU, College Station, TX 77843-2128, USA.</publication><submitter_mail>hdharuri@cds.caltech.edu</submitter_mail><submitter_affiliation>California Institute of Technology</submitter_affiliation><pubmed_abstract>With the emergence of multifaceted bioinformatics-derived data, it is becoming possible to merge biochemical and physiological information to develop a new level of understanding of the metabolic complexity of the cell. The biosynthetic pathway of de novo pyrimidine nucleotide metabolism is an essential capability of all free-living cells, and it occupies a pivotal position relative to metabolic processes that are involved in the macromolecular synthesis of DNA, RNA and proteins, as well as energy production and cell division. This regulatory network in all enteric bacteria involves genetic, allosteric, and physiological control systems that need to be integrated into a coordinated set of metabolic checks and balances. Allosterically regulated pathways constitute an exciting and challenging biosynthetic system to be approached from a mathematical perspective. However, to date, a mathematical model quantifying the contribution of allostery in controlling the dynamics of metabolic pathways has not been proposed. In this study, a direct, rigorous mathematical model of the de novo biosynthesis of pyrimidine nucleotides is presented. We corroborate the simulations with experimental data available in the literature and validate it with derepression experiments done in our laboratory. The model is able to faithfully represent the dynamic changes in the intracellular nucleotide pools that occur during metabolic transitions of the de novo pyrimidine biosynthetic pathway and represents a step forward in understanding the role of allosteric regulation in metabolic control.</pubmed_abstract><pubmed_title>Modeling allosteric regulation of de novo pyrimidine biosynthesis in Escherichia coli.</pubmed_title><pubmed_authors>Rodríguez Mauricio M, Good Theresa A TA, Wales Melinda E ME, Hua Jean P JP, Wild James R JR</pubmed_authors></additional><is_claimable>false</is_claimable><name>Rodriguez2005_denovo_pyrimidine_biosynthesis</name><description>
      
        This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2011 The BioModels.net Team.      
          To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to      CC0 Public Domain Dedication
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      In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..      
      
          To cite BioModels Database, please use:      Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
  

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