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Mechanochemical models of processive molecular motors

机译:加工分子马达的机械化学模型

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Motor proteins are the molecular engines powering the living cell. These nanometre-sized molecules convert chemical energy, both enthalpic and entropic, into useful mechanical work. High resolution single molecule experiments can now observe motor protein movement with increasing precision. The emerging data must be combined with structural and kinetic measurements to develop a quantitative mechanism. This article describes a modelling framework where quantitative understanding of motor behaviour can be developed based on the protein structure. The framework is applied to myosin motors, with emphasis on how synchrony between motor domains give rise to processive unidirectional movement. The modelling approach shows that the elasticity of protein domains are important in regulating motor function. Simple models of protein domain elasticity are presented. The framework can be generalized to other motor systems, or an ensemble of motors such as muscle contraction. Indeed, for hundreds of myosins, our framework can be reduced to the Huxely-Simmons description of muscle movement in the mean-field limit.View full textDownload full textKeywordsmolecular motors, myosin movement, stochastic models, coarse-grained modellingRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/00268976.2012.677863
机译:运动蛋白是为活细胞提供动力的分子引擎。这些纳米级分子将焓和熵的化学能转化为有用的机械功。高分辨率单分子实验现在可以以更高的精度观察运动蛋白的运动。新出现的数据必须与结构和动力学测量相结合以建立定量机制。本文介绍了一种建模框架,在该框架中可以基于蛋白质结构对运动行为进行定量理解。该框架适用于肌球蛋白电机,重点在于电机域之间的同步如何引起进行性单向运动。建模方法表明,蛋白质结构域的弹性在调节运动功能中很重要。介绍了蛋白质结构域弹性的简单模型。该框架可以推广到其他运动系统,或诸如肌肉收缩之类的运动集合。的确,对于数百个肌球蛋白,我们的框架可以简化为在均值范围内的肌肉运动的Huxely-Simmons描述。查看全文下载全文关键词分子运动,肌球蛋白运动,随机模型,粗粒度建模相关var addthis_config = {ui_cobrand :“ Taylor&Francis Online”,services_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more”,pubid:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/00268976.2012.677863

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