Modeling Biomolecular Transport Processes

埃尔斯顿0075821 这个项目的主要目标是获得生物分子运输过程中能量转换的机械理解。 该项目集中在三个特定的系统：细菌鞭毛马达，马达蛋白动力蛋白，以及在内质网和线粒体膜中发现的蛋白质易位系统。 虽然这些系统所涉及的生物学是非常不同的，但同样的数学技术适用于分析所有三个系统的理论模型。 对这些系统建模需要使用朗之万或随机微分方程。 这些方程中的随机性来自两个来源，热扩散和化学动力学。热波动的特征在于扩散系数，这可以通过实验测量，许多重要的反应速率是已知的从生化研究。除了分子碰撞，静电相互作用是参与这些运输系统的其他主导力量。 如果有，结构数据被用来确定相关的静电势。 一旦这些系统的模型方程已经开发出来，数值和分析techniquesare用来比较它们的行为与实验数据。 分析的最后阶段是使用数学模型来产生实验可检验的预测。 生物分子发动机是一种纳米级的发动机，它利用化学能产生动力。 一种众所周知的分子马达是肌球蛋白，它是负责肌肉收缩的蛋白质。 其他的例子包括鞭毛马达，它被细菌用来游泳，动力蛋白，它产生纤毛运动所必需的力量。 这个项目的广泛目标是获得这两个系统中力生成的机械理解。 目前的实验技术使生物药理学家能够在单分子水平上研究分子马达，从而可以测量马达蛋白的机械特性。 这些新的物理数据与结构数据相结合，为重新开展分子马达功能的理论研究提供了动力。 对力的产生进行数学分析的一个重要原因是，它允许在实验数据和模型行为之间进行定量比较。 这样的计算结果不仅对模型验证很重要，而且可以用来发现模型假设中的错误。 然而，数学建模的意义超越了模型验证，而在于其预测能力。 一旦一个理论模型被开发出来，与当前的实验数据相一致，就可以直接扩展分析，包括尚未在实验室中研究的情况。 如果模型的预测被实验所证实，那么模型的真实性就得到了进一步的证实。 对于本项目中考虑的系统，这意味着已经实现了对力生成的机械理解。 从技术的角度来看，这些研究的结果应该与设计和制造人造纳米机器有关。

Elston0075821 The broad goal of this project is to gain a mechanisticunderstanding of energy transduction in biomolecular transportprocesses. The project focuses on three specific systems: thebacterial flagellar motor, the motor protein dynein, and proteintranslocation systems found in membranes of the endoplasmicreticulum and mitochondria. While the biology involved in thesesystems is very different, the same mathematical techniques areapplicable for analyzing theoretical models of all three. Tomodel these systems requires the use of Langevin or stochasticdifferential equations. The randomness in these equations comesfrom two sources, thermal diffusion and chemical kinetics.Thermal fluctuations are characterized by the diffusioncoefficient, which can be measured experimentally, and many ofthe important reaction rates are known from biochemical studies.In addition to molecular collisions, electrostatic interactionsare the other dominant forces involved in these transportsystems. If available, structural data are used to determine therelevant electrostatic potentials. Once model equations for thesystems have been developed, numerical and analytical techniquesare used to compare their behavior with experimental data. Thefinal phase of the analysis is to use the mathematical models toproduce experimentally testable predictions. Biological molecular motors are nanometer-sized engines thatuse chemical energy to generate force. A well known molecularmotor is myosin, which is the protein responsible for musclecontraction. Other examples include the flagellar motor, which isused by bacteria for swimming, and dynein, which produces theforce necessary for cilia motion. The broad goal of this projectis to gain a mechanistic understanding of force generation inboth these systems. Current experimental techniques are allowingbiophysicists to study molecular motors at the single moleculelevel, thereby allowing the mechanical properties of motorproteins to be measured. These new physical data in conjunctionwith structural data provide the impetus for renewed theoreticalinvestigations into molecular motor function. An important reasonfor performing a mathematical analysis of force generation isthat it allows a quantitative comparison between experimentaldata and model behavior to be made. The results of such acomparison not only are important for model validation, but alsocan be used to uncover errors in the assumptions underlying themodel. However, the significance of mathematical modeling goesbeyond model validation and lies in its predictive power. Once atheoretical model has been developed that is consistent withcurrent experimental data, it is straightforward to extend theanalysis to include situations that have not yet beeninvestigated in the laboratory. If model predictions are borneout by experiment, further confidence in the reality of the modelis gained. For the systems under consideration in this project,this means a mechanistic understanding of force generation hasbeen achieved. From a technological standpoint, the results ofthese investigations should be relevant for designing andfabricating manmade nanomachines.