Dataset Information

Chang2010_Reduced_Kidney_FBA

ABSTRACT: This is the reduced kidney metabolic network described in the article Drug off-target effects predicted using structural analysis in the context of a metabolic network model. Chang RL, Xie L, Xie L, Bourne PE, Palsson BØ. PLoS Comput Biol. 2010 Sep 23;6(9):e1000938. PMID: 20957118 , DOI: 10.1371/journal.pcbi.1000938 Abstract: Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials. Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment. This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine. The methodology introduced herein has important implications for drug development and personalized medicine. This model was downloaded from the supplementary materials to the article. To make this file valid SBML, in some ids brackets had to be replaced, and all parameter units were changed from mmole per gDW per hour to mmole per hour. The model can be used, amongst others, with the COBRA toolbox . This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). 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 for more information. 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.

SUBMITTER: Lukas Endler

PROVIDER: MODEL1011080004 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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	MODEL1011080004?filename=MODEL1011080004-biopax3.owl	Owl
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Publications

Drug off-target effects predicted using structural analysis in the context of a metabolic network model.

Chang Roger L RL Xie Li L Xie Lei L Bourne Philip E PE Palsson Bernhard Ø BØ

PLoS computational biology 20100923 9

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the choleste ...[more]

PMID: 20957118

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