Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction.

Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction.
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DOI:
10.1098/rsif.2016.0409
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发表时间:
2016-08
期刊:
Journal of the Royal Society, Interface
影响因子:
--
通讯作者:
Barahona M
Barahona M
中科院分区:
其他
文献类型:
--
作者:
Beguerisse-Díaz M;Desikan R;Barahona M

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细胞信号转导通常涉及激活级联反应,即在接收到输入信号后一系列蛋白质的顺序激活。在这里,我们研究弱激活级联的经典模型,并获得各种输入的解析解。我们表明,在特殊但重要的情况下,最佳增益级联(即当失活率是相同的)的级联的下游输出可以表示为集总的非线性模块包含一个不完整的伽马函数与真实的参数,取决于级联的速率和长度,以及输入信号的参数。当失活率是随机的时,所得到的表达式可以应用于不相同的情况,以捕获级联输出的变化。我们还表明,级联可以重新安排,使块具有类似的速率可以集中,并通过我们的非线性模块表示。我们的结果可以用来表示级联的微分方程的计算模型,并有效地拟合数据,通过减少涉及的方程和参数的数量。特别是,级联的长度表现为实值参数,因此可以以与希尔系数相同的方式拟合。最后,我们展示了如何得到的非线性模块可以用来代替延迟微分方程模型延迟信号转导。
Cellular signal transduction usually involves activation cascades, the sequential activation of a series of proteins following the reception of an input signal. Here, we study the classic model of weakly activated cascades and obtain analytical solutions for a variety of inputs. We show that in the special but important case of optimal gain cascades (i.e. when the deactivation rates are identical) the downstream output of the cascade can be represented exactly as a lumped nonlinear module containing an incomplete gamma function with real parameters that depend on the rates and length of the cascade, as well as parameters of the input signal. The expressions obtained can be applied to the non-identical case when the deactivation rates are random to capture the variability in the cascade outputs. We also show that cascades can be rearranged so that blocks with similar rates can be lumped and represented through our nonlinear modules. Our results can be used both to represent cascades in computational models of differential equations and to fit data efficiently, by reducing the number of equations and parameters involved. In particular, the length of the cascade appears as a real-valued parameter and can thus be fitted in the same manner as Hill coefficients. Finally, we show how the obtained nonlinear modules can be used instead of delay differential equations to model delays in signal transduction.
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