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- 2018
Cav1？？2离子通道马尔科夫随机过程模型 的建立与应用
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Abstract:
针对Cav1？？2离子通道在功能细胞的Ca2+代谢循环中起着关键作用,并且在细胞交互环境下受到多种因素的调控从而表现出的复杂门控行为,基于现有的Cav1？？2结构信息,提出了改进的连续时间7态马尔科夫随机过程模型。首先抽象出7个通道状态来表征Cav1？？2离子通道的有限构象变化,包括电压相关失活(VDI)和Ca2+相关失活(CDI);其次应用相关实验数据求解7个状态间迁移速率函数的参数,即在贝叶斯框架下利用JAGS软件包,实现蒙特卡洛马尔可夫链(MCMC)算法对参数的后验分布进行Gibbs抽样。最后,将通道随机模型分别应用于描述小空间中Ca2+瞬态行为的随机偏微分方程和Cav1？？2离子通道G406R/G432N突变引发的电生理变化。计算结果表明:改进的Cav1？？2马尔科夫模型不仅在宏观水平上与广泛的电生理实验结果有较好的吻合,而且在心肌细胞微结构以及通道基因的病理研究领域中具有较好的预测性。
An improved seven states Markov stochastic process model based on current channel structure information is proposed to elucidate and forecast Cav1？？2complex gating kinetic in the interactive cell environment regulated by multiple factors which plays a key role in the Ca2+ metabolic cycle in functioning cells. Seven states are abstracted to present the limited conformational changes of Cav1？？2channel including VDI and CDI. Based on the Bayesian framework, the experiment data are then used to estimate the parameters of rate function between seven states via JAGS, which implements MCMC algorithm Gibbs sampler to sample the posterior distribution. The stochastic model is applied separately to stochastic PDEs profiling the Ca2+ transient in the subspace and the changed electrophysiological behavior induced by the channel mutations G406R/G432N. The computational results show that the improved Cav1？？2 Markov framework coincides well with the broad electrophysiological observations at the macroscopic level, and it also has a better predictability in the field of cardiomyocytes microstructure and channel genes pathology
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