A computational model on the modulation of mitogen-activated protein kinase (MAPK) and Akt pathways in heregulin-induced ErbB signalling

Hatakeyama, Mariko; Kimura, Shiushichi; Naka, Takashi; Kawasaki, Takuji; Yumoto, Noriko; Ichikawa, Mio; Kim, Jae-Hoon; Saito, Kazuki; Saeki, Mihoro; Shirouzu, Mikako; Yokoyama, Shigeyuki; Konagaya, Akihiko

doi:10.1042/bj20021824

Cited by 211 publications

(188 citation statements)

References 62 publications

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“…Nevertheless, the parameters used therein are sometimes astonishingly different from each other (14). One apparent reason for this discrepancy is that these studies often use different algorithms to fit the parameters to the experimental data (15)(16)(17). Another reason may be that some parameters are derived from in vitro experiments, which may not reflect in vivo conditions.…”

mentioning

confidence: 89%

Multiple Decisive Phosphorylation Sites for the Negative Feedback Regulation of SOS1 via ERK*

Kamioka

Yasuda²,

Fujita

et al. 2010

Journal of Biological Chemistry

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EGF-induced activation of ERK has been extensively studied by both experimental and theoretical approaches. Here, we used a simulation model based mostly on experimentally determined parameters to study the ERK-mediated negative feedback regulation of the Ras guanine nucleotide exchange factor, son of sevenless (SOS). Because SOS1 is phosphorylated at multiple serine residues upon stimulation, we evaluated the role of the multiplicity by building two simulation models, which we termed the decisive and cooperative phosphorylation models. The two models were constrained by the duration of Ras activation and basal phosphorylation level of SOS1. Possible solutions were found only in the decisive model wherein at least three, and probably more than four, phosphorylation sites decisively suppress the SOS activity. Thus, the combination of experimental approaches and the model analysis has suggested an unexpected role of multiple phosphorylations of SOS1 in the negative regulation.

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mentioning

confidence: 89%

Multiple Decisive Phosphorylation Sites for the Negative Feedback Regulation of SOS1 via ERK*

Kamioka

Yasuda²,

Fujita

et al. 2010

Journal of Biological Chemistry

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“…Besides the 'implicit feedback', see also [41], the enzyme involved in the (de)activation leads to an 'implicit inhibition' [42,43]. For instance, the single-phosphorylated protein X P inhibits the phosphorylation of X and X inhibits the phosphorylation of X P through the competition for W…”

Section: Signalling Cascadesmentioning

confidence: 99%

Approximations and their consequences for dynamic modelling of signal transduction pathways

Millat

Bullinger

Rohwer

et al. 2007

Mathematical Biosciences

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This version is available at https://strathprints.strath.ac.uk/11996/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Signal transduction is the process by which the cell converts one kind of signal or stimulus into another. This involves a sequence of biochemical reactions, carried out by proteins. The dynamic response of complex cell signalling networks can be modelled and simulated in the framework of chemical kinetics. The mathematical formulation of chemical kinetics results in a system of coupled differential equations. Simplifications can arise through assumptions and approximations. The paper provides a critical discussion of frequently employed approximations in dynamic modelling of signal transduction pathways. We discuss the requirements for conservation laws, steady state approximations, and the neglect of components. We show how these approximations simplify the mathematical treatment of biochemical networks but we also demonstrate differences between the complete system and its approximations with respect to the transient and steady state behavior. Approximations and their Consequences for Dynamic Modelling of Signal Transduction Pathways

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“…Over the past several years there has been a proliferation of mechanistic models of signaling pathways (1)(2)(3)(4)(5)(6)(7)(8)(9). These models consist of ordinary differential equations and generally describe the time evolution of intracellular species (ligand-receptor complexes, phosphorylated proteins, cleaved proteins, nuclear translocation, etc.)…”

Section: Introductionmentioning

confidence: 99%

Analysis of Mechanistic Pathway Models in Drug Discovery: p38 Pathway

2008

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Mechanistic models of signal transduction have emerged as valuable tools for untangling complex signaling networks and gaining detailed insight into pathway dynamics. The natural extension of these tools is for the design of therapeutic strategies. We have generated a novel computational model of lipopolysaccharide-induced p38 signaling in the context of TNF-R production in inflammatory disease. Using experimental measurement of protein levels and phospho-protein time courses, populations of model parameters were estimated. With a collection of parameter sets, reflecting virtual diversity, we step through analysis of the p38 signaling pathway model to answer specific drug discovery questions regarding target prioritization, inhibitor simulation, model robustness and co-drugging. We demonstrate that target selection cannot be assessed independently from inhibitor mechanism of action and is also linked with robustness to cellular variability. Finally, we assert that in the face of parameter uncertainty one can still uncover consistent findings that can guide drug discovery efforts.

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A computational model on the modulation of mitogen-activated protein kinase (MAPK) and Akt pathways in heregulin-induced ErbB signalling

Cited by 211 publications

References 62 publications

Multiple Decisive Phosphorylation Sites for the Negative Feedback Regulation of SOS1 via ERK*

Multiple Decisive Phosphorylation Sites for the Negative Feedback Regulation of SOS1 via ERK*

Approximations and their consequences for dynamic modelling of signal transduction pathways

Analysis of Mechanistic Pathway Models in Drug Discovery: p38 Pathway

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