Non-equilibrium Fluctuations and Cooperativity in Single-Molecule Dynamics: Going Beyond FluctuationTheorems and Large Deviation Theory: Thermodynamically consistent renewal networks for driven single-molecule dynamics with memory

单分子动力学中的非平衡涨落和协同性:超越涨落定理和大偏差理论:具有记忆驱动的单分子动力学的热力学一致更新网络

基本信息

项目摘要

Conformational changes are essential for the function of proteins, nucleic acids, and larger molecular nanomachines. The so-called large-amplitude collective motions can beunderstood as transitions between transient ensembles of characteristic geometrical large-scale structures persisting over longer periods of time, which correspond to attractors in a high-dimensional potential. While approaching a hopping process on the longest time-scales conformational transitions generally display a temporally complex multi-scale structure. Understanding conformational transitions remains a grand challenge, as they involve many degrees of freedom and span ten to fifteen orders in time and typically also evolve via various pathways with many intermediates. Biomacromolecular systems, in particular biological nanomachines, driven irreversibly by an external force are even more challenging, especially from the point of view of the thermodynamics that requires to correctly account for the dissipation.Atomistic molecular dynamics (MD) simulations could in principle provide a detailed insightinto conformational dynamics but cannot overcome the broad time-scale problem. As a result transition-network approaches emerged as alternatives, which aim at a Markov jump process description on a reduced state-space that on the longest time-scales agrees with the exact dynamics. This always introduces constraints on the spatio-temporal resolution in order to ensure that the resulting dynamics is still Markovian. In addition, the Markov-jump restriction is doomed to fail for potentials with extended diffusive transition regions, which require too many states to be practically useful. The latter are in fact typical for intrinsically disordered proteins (IDPs) and were also associated with protein mis-folding. Transition regions between metastable states are often flat even in the case of structured proteins. Similar effects arise in the presence of strong external driving that may destabilize metastable states. This poses an obvious need for relaxing the Markov-jump assumption.Our overreaching goal is therefore to shift the paradigm from Markov towards the weakerrenewal assumption, and to rigorously formulate and implement a thermodynamically consistent renewal network approach for modeling driven conformational dynamics of biopolymers. This will relax the unnecessarily stringent assumption on Markovian jumps and will hence allow for multi-scale dynamics on the reduced state-space with a much higher temporal resolution thus enabling the study of strongly driven systems as well as systems whose underlying potential is characterized by extended diffusive transition regions.
构象变化对于蛋白质、核酸和更大的分子纳米机器的功能是必不可少的。所谓的大振幅集体运动可以理解为持续较长时间的特征几何大尺度结构的瞬态集合之间的转换,这对应于高维势中的吸引子。构象跃迁在最长时间尺度上接近跳跃过程,一般表现为时间上复杂的多尺度结构。理解构象转变仍然是一个巨大的挑战,因为它们涉及许多自由度,在时间上跨越10到15个数量级,并且通常也通过许多中间产物的各种途径进化。生物大分子系统,特别是生物纳米机器,受到外力的不可逆驱动更具挑战性,特别是从热力学的角度来看,需要正确地考虑耗散。原子分子动力学(MD)模拟原则上可以提供对构象动力学的详细见解,但不能克服广泛的时间尺度问题。因此,过渡网络方法作为替代方案出现,其目标是在最长时间尺度上与确切动态一致的简化状态空间上的马尔可夫跳跃过程描述。这总是在时空分辨率上引入约束,以确保最终的动态仍然是马尔可夫的。此外,马尔可夫跃迁限制对于具有扩展扩散过渡区域的势是注定要失败的,因为它需要太多的状态而无法实际使用。后者实际上是典型的内在无序蛋白(IDPs),也与蛋白质错误折叠有关。亚稳态之间的过渡区通常是平坦的,即使在结构蛋白的情况下也是如此。类似的效应出现在强大的外部驱动,可能破坏亚稳态的存在。这显然需要放松马尔可夫跳变假设。因此,我们的超额目标是将范式从马尔可夫转移到弱更新假设,并严格制定和实施一个热力学一致的更新网络方法来建模驱动的生物聚合物构象动力学。这将放宽对马尔可夫跳跃的不必要的严格假设,从而允许在简化的状态空间上以更高的时间分辨率进行多尺度动力学,从而使强驱动系统以及潜在势以扩展扩散过渡区为特征的系统的研究成为可能。

项目成果

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Dr. Aljaz Godec其他文献

Dr. Aljaz Godec的其他文献

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{{ truncateString('Dr. Aljaz Godec', 18)}}的其他基金

Thermodynamically consistent approach to structure formation from first principles
从第一原理出发的结构形成的热力学一致方法
  • 批准号:
    519908559
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Hidden dynamics and collective phenomena in and out of equilibrium
平衡状态和非平衡状态的隐藏动态和集体现象
  • 批准号:
    519908342
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Heisenberg Grants

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    2008
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    27.0 万元
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    面上项目

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