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大分子动力学动力学模型的精确解。

Exact solutions for kinetic models of macromolecular dynamics.

作者信息

Chemla Yann R, Moffitt Jeffrey R, Bustamante Carlos

机构信息

Department of Physics, University of Illinois, Urbana-Champaign, Urbana, Illinois 61801, USA.

出版信息

J Phys Chem B. 2008 May 15;112(19):6025-44. doi: 10.1021/jp076153r. Epub 2008 Mar 29.

Abstract

Dynamic biological processes such as enzyme catalysis, molecular motor translocation, and protein and nucleic acid conformational dynamics are inherently stochastic processes. However, when such processes are studied on a nonsynchronized ensemble, the inherent fluctuations are lost, and only the average rate of the process can be measured. With the recent development of methods of single-molecule manipulation and detection, it is now possible to follow the progress of an individual molecule, measuring not just the average rate but the fluctuations in this rate as well. These fluctuations can provide a great deal of detail about the underlying kinetic cycle that governs the dynamical behavior of the system. However, extracting this information from experiments requires the ability to calculate the general properties of arbitrarily complex theoretical kinetic schemes. We present here a general technique that determines the exact analytical solution for the mean velocity and for measures of the fluctuations. We adopt a formalism based on the master equation and show how the probability density for the position of a molecular motor at a given time can be solved exactly in Fourier-Laplace space. With this analytic solution, we can then calculate the mean velocity and fluctuation-related parameters, such as the randomness parameter (a dimensionless ratio of the diffusion constant and the velocity) and the dwell time distributions, which fully characterize the fluctuations of the system, both commonly used kinetic parameters in single-molecule measurements. Furthermore, we show that this formalism allows calculation of these parameters for a much wider class of general kinetic models than demonstrated with previous methods.

摘要

诸如酶催化、分子马达转运以及蛋白质和核酸构象动力学等动态生物学过程本质上都是随机过程。然而,当在非同步集合上研究此类过程时,固有的涨落就会消失,并且只能测量该过程的平均速率。随着单分子操纵和检测方法的最新发展,现在有可能追踪单个分子的进程,不仅测量平均速率,还能测量该速率的涨落。这些涨落可以提供大量关于支配系统动态行为的潜在动力学循环的细节。然而,从实验中提取这些信息需要能够计算任意复杂理论动力学方案的一般性质。我们在此提出一种通用技术,它能确定平均速度和涨落度量的精确解析解。我们采用基于主方程的形式体系,并展示如何在傅里叶 - 拉普拉斯空间中精确求解给定时间分子马达位置的概率密度。有了这个解析解,我们就能计算平均速度和与涨落相关的参数,比如随机参数(扩散常数与速度的无量纲比值)以及驻留时间分布,这些参数全面表征了系统的涨落,它们都是单分子测量中常用的动力学参数。此外,我们表明这种形式体系能够为比先前方法所展示的更广泛的一类通用动力学模型计算这些参数。

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