arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1004.1114cond-mat.stat-mechphysics.bio-phq-bio.SC
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人工蛋白质马达的主方程建模方法

A Master equation approach to modeling an artificial protein motor

Nathan J. Kuwada, Gerhard A. Blab, Heiner Linke

摘要:

线性生物分子马达通过协调几个不同的过程(例如燃料(ATP)捕获、水解、构象变化、从轨道结合和解结合以及质心扩散)沿轨道单向移动。更好地理解这些过程之间的相互依赖性,这些过程发生在广泛的不同时间尺度上,将有助于阐明分子马达的一般操作原理。人工分子马达为这样的研究提供了一个独特的机会,因为马达的结构和功能是先验已知的。在这里,我们描述了使用主方程的方法,结合从Langevin和分子动力学建模输入,随机模型的分子马达在许多时间尺度。我们将这种方法应用于一个特定的概念,人工蛋白质马达,风滚草。

英文摘要:

Linear bio-molecular motors move unidirectionally along a track by coordinating several different processes, such as fuel (ATP) capture, hydrolysis, conformational changes, binding and unbinding from a track, and center-of-mass diffusion. A better understanding of the interdependencies between these processes, which take place over a wide range of different time scales, would help elucidate the general operational principles of molecular motors. Artificial molecular motors present a unique opportunity for such a study because motor structure and function are a priori known. Here we describe use of a Master equation approach, integrated with input from Langevin and molecular dynamics modeling, to stochastically model a molecular motor across many time scales. We apply this approach to a specific concept for an artificial protein motor, the Tumbleweed.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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