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Yugi2014 - Insulin induced signalling (PFKL phosphorylation) - model 2

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Yugi2014 - Insulin induced signalling (PFKL phosphorylation) - model 2 Insulin induces phosphorylation and activation of liver-type phosphofructokinase 1, which thereby controls a key reaction in glycolysis. This mechanism is revealed using the mathematical model. In this model, the PFKL phosphorylation time courses are calculation from the signalling pathway model developed by Kubata et al. (2012) ( MODEL1204060000 - Kubota2012_InsulinAction_AKTpathway). Author's Note: Katsuyuki Yugi thank Akira Funahashi (Keio University, Japan) for his kind advice in converting the model from MATLAB to SBML. This model is described in the article: Reconstruction of insulin signal flow from phosphoproteome and metabolome data. Yugi K, Kubota H, Toyoshima Y, Noguchi R, Kawata K, Komori Y, Uda S, Kunida K, Tomizawa Y, Funato Y, Miki H, Matsumoto M, Nakayama KI, Kashikura K, Endo K, Ikeda K, Soga T, Kuroda S. Cell Rep 2014 Aug; 8(4): 1171-1183 Abstract: Cellular homeostasis is regulated by signals through multiple molecular networks that include protein phosphorylation and metabolites. However, where and when the signal flows through a network and regulates homeostasis has not been explored. We have developed a reconstruction method for the signal flow based on time-course phosphoproteome and metabolome data, using multiple databases, and have applied it to acute action of insulin, an important hormone for metabolic homeostasis. An insulin signal flows through a network, through signaling pathways that involve 13 protein kinases, 26 phosphorylated metabolic enzymes, and 35 allosteric effectors, resulting in quantitative changes in 44 metabolites. Analysis of the network reveals that insulin induces phosphorylation and activation of liver-type phosphofructokinase 1, thereby controlling a key reaction in glycolysis. We thus provide a versatile method of reconstruction of signal flow through the network using phosphoproteome and metabolome data. This model is hosted on BioModels Database and identified by: BIOMD0000000541. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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.
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2024-09-02
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