Expression of excess receptors and negative feedback control of signal pathways are required for rapid activation and prompt cessation of signal transduction

Kobayashi, Hiroshi; Azuma, Ryuzo; Yasunaga, Takuo

doi:10.1186/1478-811x-7-3

Cited by 5 publications

(7 citation statements)

References 35 publications

(32 reference statements)

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“…The dissociation probabilities (exp(-E2/RT)) were set to one-tenth of the binding probability in all simulations. The average diffusion coefficients calculated from the moving distances of 1000 proteins as described previously [16] are shown in Table 2. In this calculation, proteins are allowed to move even if the target subspace is occupied.…”

Section: Resultsmentioning

confidence: 99%

“…In the present study, a simplified model in which the cell surface is represented as a 2-dimensional plane was assumed, and the cell surface was divided into subspaces. A single subspace was a cubic box with a volume of 166 (5.5 3 ) nm 3 , as described previously [16]. One molecule per subspace corresponded to a concentration of 10 mM.…”

Section: Methodsmentioning

confidence: 99%

“…In contrast, the latter can simulate both population behavior and single molecule dynamics. Monte Carlo simulation can also evaluate time-dependent fluctuations involving noise as well as cell-to-cell population heterogeneity [16].…”

Section: Introductionmentioning

confidence: 99%

“…Since one cell contains less than 100,000 molecules of a given membrane protein and because there are variations in biological phenomena, the latter method may be more appropriate. Receptor-ligand formation and clustering of membrane proteins have already been simulated with Monte Carlo techniques [16][17][18][19][20][21], and their results revealed the usefulness of this technique for clarification of biological phenomena.…”

Section: Introductionmentioning

confidence: 99%

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Do membrane proteins cluster without binding between molecules?

Wang¹,

Fukamachi²,

Saito³

et al. 2012

OJI

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Clustering is a basic event for the initiation of immune cell responses, and simulation analyses of clustering of membrane proteins have been performed. It was claimed that a cluster is formed by the self-assembly induced by protein dimerization with a high binding speed (Woolf and Linderman, Biophys. Chem. 104, 217-227, 2003). We examined the cluster formation with Monte Carlo simulation using two algorithms. The first was that simulation processes were divided into two substeps. All proteins were subjected to movement in the first substep, followed by reaction in the second substep. The second algorithm was that proteins were first selected to react and proteins which did not react were subjected to movement. The self-assembly induced by dimerization was simulated only with the second algorithm. In this algorithm, monomers dissociated from dimers do not move because these monomers are not selected for movement, and a large proportion of such monomers are selected to form dimers in the next step. The self-assembly was again simulated with the first algorithm containing the conditions that monomers dissociated from dimers did not move in the next movement substep. This algorithm seems to be far removed from natural conditions. Thus, it is inferred that the self-assembly induced by dimerization is unlikely in situ, and that some interaction between proteins is required for cluster formation. In contrast to algorithms in previous simulations, our results suggest that it is more appropriate that proteins move to the same direction for a while and reflect when the collision occurs

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Do membrane proteins cluster without binding between molecules?

Wang¹,

Fukamachi²,

Saito³

et al. 2012

OJI

Self Cite

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“…This needs close collaboration between experimentalists who generate quantitative data sets and applied mathematicians who use deterministic and stochastic approaches to describe those data [25-27]. Fostering those interactions is one goal of SYBILLA.…”

Section: Mathematical Models Of Early T-cell Signallingmentioning

confidence: 99%

Meeting report: Signal transduction meets systems biology

Louis-Dit-Sully

Kubatzky

Lindquist

et al. 2012

Cell Communication and Signaling

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In the 21st century, systems-wide analyses of biological processes are getting more and more realistic. Especially for the in depth analysis of signal transduction pathways and networks, various approaches of systems biology are now successfully used. The EU FP7 large integrated project SYBILLA (Systems Biology of T-cell Activation in Health and Disease) coordinates such an endeavor. By using a combination of experimental data sets and computational modelling, the consortium strives for gaining a detailed and mechanistic understanding of signal transduction processes that govern T-cell activation. In order to foster the interaction between systems biologists and experimentally working groups, SYBILLA co-organized the 15th meeting “Signal Transduction: Receptors, Mediators and Genes” together with the Signal Transduction Society (STS). Thus, the annual STS conference, held from November 7 to 9, 2011 in Weimar, Germany, provided an interdisciplinary forum for research on signal transduction with a major focus on systems biology addressing signalling events in T-cells. Here we report on a selection of ongoing projects of SYBILLA and how they were discussed at this interdisciplinary conference.

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