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Atomistic Mechano-Chemical Modeling of Kinesins

机译:Kinesins原子的机械化学建模

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This work is concerned with the dynamics of motor proteins. In particular, we discuss the development of computational analysis tools for predicting the dynamics of molecular motors such as certain types of kinesin. The ability to model and predict how these biomolecular machines work forms the critical link to biotechnological device development, including lab-on-a-chip applications and many others. The focus of this research is on the identification and modeling of nonlinear dynamic phenomena caused by coupled thermal, chemical, and mechanical fields. A mechanistic model of kinesin has been developed recently at the University of Michigan. This model accounts for transient dynamics and uses parameters which have to be identified from experimental data and/or from first principles. In this work, accurate atomistic simulations using a monomeric human kinesin structure (PDB ID: 1MKJ, 2.70 Angstroms resolution) is used instead of experimental data to obtain key nano-scale properties of the motor protein. The approach allows an accurate bridging between nano-scale processes occurring over pico seconds and micron- or millimeter-scale processes occurring over seconds.
机译:这项工作涉及电机蛋白的动态。特别是,我们讨论了计算分析工具的开发,以预测分子电机的动态,例如某些类型的kinesin。模拟和预测这些生物分子机械的能力是如何形成生物技术设备开发的关键链接,包括芯片应用和许多其他芯片应用。该研究的重点是由耦合热,化学和机械领域引起的非线性动态现象的识别和建模。最近在密歇根大学开发了Kinesin的机械模式。该模型用于瞬态动态,并使用必须从实验数据和/或第一原理中识别的参数。在这项工作中,使用使用单体人类kinesin结构(PDB ID:1MKJ,2.70埃分辨率)的准确原子模拟代替实验数据以获得电机蛋白的关键纳米级特性。该方法允许在微微秒和微米或毫米或毫米刻度过程之间进行准确的桥接在几秒钟内发生的纳米级过程。

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