<HashMap><database>biostudies-other</database><scores/><additional><omics_type>Unknown</omics_type><volume>9</volume><submitter>Lucian Smith</submitter><journal>PLoS computational biology</journal><pagination>e1003186</pagination><species>Rattus</species><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/MODEL1312040000</full_dataset_link><repository>biostudies-other</repository><additional_accession>23966849</additional_accession><pubmed_authors>Lucian Smith</pubmed_authors><pubmed_authors>Kieran Smallbone</pubmed_authors></additional><is_claimable>false</is_claimable><name>vanEunen2013 - Network dynamics of fatty acid β-oxidation (steady-state model)</name><description>&lt;notes xmlns="http://www.sbml.org/sbml/level2/version4">      &lt;body xmlns="http://www.w3.org/1999/xhtml">        &lt;div class="dc:title">vanEunen2013 - Network dynamics of fatty acid β-oxidation (steady-state model)&lt;/div>            &lt;div class="dc:description">      &lt;p>Lipid metabolism plays an important role in the development of metabolic syndrome, a major risk factor for cardiovascular disease and diabetes. This model gives insights into the response of lipid oxidation to dietart and medical interventions. The model predicts the rate of lipid oxidation and the time course of most acyl carnitines. There are two models described in the paper, (i) steady-state model [        &lt;a href="http://identifiers.org/biomodels.db/BIOMD0000000505">BIOMD0000000505&lt;/a>            ], (ii) time-course model [        &lt;a href="http://identifiers.org/biomodels.db/BIOMD0000000506">BIOMD0000000506&lt;/a>            ]. This model corresponds to the steady-state model.        &lt;/p>                &lt;/div>            &lt;div class="dc:bibliographicCitation">      &lt;p>This model is described in the article:&lt;/p>                &lt;div class="bibo:title">        &lt;a href="http://identifiers.org/pubmed/23966849" title="Access to this publication">Biochemical competition makes fatty-acid β-oxidation vulnerable to substrate overload.&lt;/a>                    &lt;/div>                &lt;div class="bibo:authorList">van Eunen K, Simons SM, Gerding A, Bleeker A, den Besten G, Touw CM, Houten SM, Groen BK, Krab K, Reijngoud DJ, Bakker BM.&lt;/div>                &lt;div class="bibo:Journal">PLoS Comput Biol. 2013;9(8):e1003186.&lt;/div>                &lt;p>Abstract:&lt;/p>                &lt;div class="bibo:abstract">        &lt;p>Fatty-acid metabolism plays a key role in acquired and inborn metabolic diseases. To obtain insight into the network dynamics of fatty-acid β-oxidation, we constructed a detailed computational model of the pathway and subjected it to a fat overload condition. The model contains reversible and saturable enzyme-kinetic equations and experimentally determined parameters for rat-liver enzymes. It was validated by adding palmitoyl CoA or palmitoyl carnitine to isolated rat-liver mitochondria: without refitting of measured parameters, the model correctly predicted the β-oxidation flux as well as the time profiles of most acyl-carnitine concentrations. Subsequently, we simulated the condition of obesity by increasing the palmitoyl-CoA concentration. At a high concentration of palmitoyl CoA the β-oxidation became overloaded: the flux dropped and metabolites accumulated. This behavior originated from the competition between acyl CoAs of different chain lengths for a set of acyl-CoA dehydrogenases with overlapping substrate specificity. This effectively induced competitive feedforward inhibition and thereby led to accumulation of CoA-ester intermediates and depletion of free CoA (CoASH). The mitochondrial [NAD⁺]/[NADH] ratio modulated the sensitivity to substrate overload, revealing a tight interplay between regulation of β-oxidation and mitochondrial respiration.&lt;/p>                    &lt;/div>                &lt;/div>            &lt;div class="dc:publisher">      &lt;p>This model is hosted on        &lt;a href="http://www.ebi.ac.uk/biomodels/">BioModels Database&lt;/a>            and identifiedby:        &lt;a href="http://identifiers.org/biomodels.db/BIOMD0000000505">BIOMD0000000505&lt;/a>            .        &lt;/p>                &lt;p>To cite BioModels Database, please use:        &lt;a href="http://identifiers.org/pubmed/20587024" title="Latest BioModels Database publication">BioModels Database: An enhanced, curated and annotated resourcefor published quantitative kinetic models&lt;/a>            .        &lt;/p>                &lt;/div>            &lt;div class="dc:license">      &lt;p>To the extent possible under law, all copyright and related orneighbouring rights to this encoded model have been dedicated to the publicdomain worldwide. Please refer to        &lt;a href="http://creativecommons.org/publicdomain/zero/1.0/" title="Access to: CC0 1.0 Universal (CC0 1.0), Public Domain Dedication">CC0 Public DomainDedication&lt;/a>            for more information.        &lt;/p>                &lt;/div>            &lt;/body>          &lt;/notes></description><dates><release>2013-12-04T00:00:00Z</release><modification>2025-07-15T10:02:42.833Z</modification><creation>2025-03-29T13:22:24.174Z</creation></dates><accession>MODEL1312040000</accession><cross_references><biomodels___db>BIOMD0000000505</biomodels___db><pubmed>23966849</pubmed><chebi>CHEBI:30788</chebi><chebi>CHEBI:16908</chebi><chebi>CHEBI:15525</chebi><chebi>CHEBI:15345</chebi><chebi>CHEBI:15531</chebi><chebi>CHEBI:17126</chebi><chebi>CHEBI:16238</chebi><chebi>CHEBI:15346</chebi><chebi>CHEBI:13389</chebi><chebi>CHEBI:15351</chebi><chebi>CHEBI:17387</chebi><chebi>CHEBI:37554</chebi><chebi>CHEBI:27803</chebi><chebi>CHEBI:61902</chebi><mamo>MAMO_0000046</mamo><go>GO:0019395</go><go>GO:0005737</go><go>GO:0005739</go><taxonomy>10114</taxonomy><bto>BTO:0000759</bto></cross_references></HashMap>