A Spatially Detailed Model of Isometric Contraction Based on Competitive Binding of Troponin I Explains Cooperative Interactions between Tropomyosin and Crossbridges.
A Spatially Detailed Model of Isometric Contraction Based on Competitive Binding of Troponin I Explains Cooperative Interactions between Tropomyosin and Crossbridges.
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DOI：
10.1371/journal.pcbi.1004376
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发表时间：
2015-08
影响因子：
4.3
通讯作者：
Niederer SA
中科院分区：
文献类型：
--
作者：
Land S;Niederer SA
心脏张力发展的生物物理模型提供了我们对心脏力产生的理解的简洁表示。蛋白质动力学和产生高协同性的相互作用之间的联系尚未从实验或以前的生物物理模型中得到充分解释。我们提出了一种基于生物物理ode的交叉桥（XB）、原肌球蛋白和肌钙蛋白在收缩调节单元（RU）内的表达，以研究协同激活背后的机制，以及协同在不同物种动态张力产生中的作用。该模型包括监管单元之间（RU-RU）、交叉桥之间（XB-XB）以及更复杂的交叉桥与监管单元之间的相互作用（XB-RU相互作用）。对于稳态力钙关系，我们的框架预测：(1)XB-RU效应是将力钙关系的半活化值向较低[Ca2+]移动的关键，但对协同性的影响很小。(2) XB-XB效应约使肌球蛋白的占空比增加一倍，但对协同性没有显著影响。(3)原肌球蛋白的远程作用产生的RU-RU效应是协同激活的主要因素，每增加一个未阻断的RU，就会增加额外RU的解封率。(4)肌凝蛋白对肌动蛋白的短（1-4 RU）未阻断延伸的亲和力非常低，因此在低[Ca2+]下产生的力抑制是双相力-钙关系的主要贡献者。我们还重现了小鼠、大鼠和人类在生理温度和起搏速率下的等长张力发展，并得出结论，物种差异只需要肌球蛋白亲和力和肌钙蛋白I/肌钙蛋白C亲和力的变化。此外，我们发现张力重建速率ktr的钙依赖性可以通过XB-RU效应的暂时降低来解释RU的短暂阻断。心肌细胞的力产生是由钙浓度的变化驱动的。在心脏跳动的过程中，钙浓度的相对较小的变化会导致心脏完全收缩和放松所需的力量的巨大变化。这被称为“协同激活”，涉及到参与收缩的几种蛋白质的复杂相互作用。目前再现力产生的计算机模型通常不能明确地表示这些过程，而随机方法往往需要大量的计算能力来解决，这限制了它们可以使用的研究范围。我们已经创建了一种新的计算模型，可以更详细地捕捉潜在的生理过程，并且比随机方法更有效，同时仍然能够运行大范围的模拟。该模型能够解释导致肌肉协同激活的生物过程。此外，该模型重现了这种合作激活如何转化为正常的肌肉功能，从而通过三种不同物种的钙变化产生力量。
Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB), tropomyosin and troponin within a contractile regulatory unit (RU) to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU), between crossbridges (XB-XB), as well more complex interactions between crossbridges and regulatory units (XB-RU interactions). For the steady-state force-calcium relationship, our framework predicts that: (1) XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca2+], but have only small effects on cooperativity. (2) XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3) RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RU’s unblocking. (4) Myosin affinity for short (1–4 RU) unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca2+] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment ktr is explained by transient blocking of RU’s by a temporary decrease in XB-RU effects. Force generation in cardiac muscle cells is driven by changes in calcium concentration. Relatively small changes in the calcium concentration over the course of a heart beat lead to the large changes in force required to fully contract and relax the heart. This is known as ‘cooperative activation’, and involves a complex interaction of several proteins involved in contraction. Current computer models which reproduce force generation often do not represent these processes explicitly, and stochastic approaches that do tend to require large amounts of computational power to solve, which limit the range of investigations in which they can be used. We have created an new computational model that captures the underlying physiological processes in more detail, and is more efficient than stochastic approaches, while still being able to run a large range of simulations. The model is able to explain the biological processes leading to the cooperative activation of muscle. In addition, the model reproduces how this cooperative activation translates to normal muscle function to generate force from changes in calcium across three different species.