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基于分子动力学轨迹的主成分分析估算小分子球状蛋白自由能景观的崎岖度。

Estimating ruggedness of free-energy landscapes of small globular proteins from principal component analysis of molecular dynamics trajectories.

机构信息

Max Planck Institute for Multidisciplinary Sciences, Theoretical and Computational Biophysics Department, Am Fassberg 11, 37077 Göttingen, Germany.

出版信息

Phys Rev E. 2022 Apr;105(4-1):044404. doi: 10.1103/PhysRevE.105.044404.

Abstract

The internal dynamics of biomolecules, and hence their function, is governed by the structure of their free-energy landscape. Early flash-photolysis experiments on myoglobin suggested that the free-energy landscapes of proteins are hierarchically structured, with a characteristic distribution of free-energy barriers which gives rise to anomalous diffusion. Analytical results have been derived for one-dimensional or high-dimensional hierarchical free-energy landscapes. Recent improvements in methods and computer performance enable generating sufficiently long molecular dynamics (MD) trajectories to extract dynamics information covering many orders of magnitude, such that the broad distributions of energy barriers of proteins become accessible to quantitative studies of intermediate dimensions. In this work, we present a nonequilibrium method to estimate barrier height distributions from microsecond-long MD simulations. It infers barrier height distributions from anomalous diffusion exponents derived from principal component analysis and by comparison to simple hierarchical lattice models. These models are d-dimensional lattices of states separated by free-energy barriers, the heights of which are distributed as p(ΔG)=1/γexp(-ΔG/γ). The parameter γ quantifies the "ruggedness" of the free-energy landscape in such models. We show that both parameters, i.e., ruggedness and effective dimensionality d, can be inferred from anomalous diffusion exponents. Assuming a similar dependency of anomalous diffusion exponents on γ and d for proteins, we estimate the ruggedness of the free-energy landscapes of 500 small, single-domain globular proteins between 15 and 20 kT per dimension with an estimated accuracy of 4.2 kT and dimensionality between 40 and 60 with an estimated accuracy of 10 dimensions. Remarkably, neither effective dimensionality nor the ruggedness correlates with protein size and both ruggedness and effective dimensionality are much smaller than the scatter of protein sizes. From this finding, we conclude that these two properties of the free-energy landscape of a protein are rather adapted to the particular function of each single protein and that, quite generally, are functionally relevant for globular proteins.

摘要

生物分子的内部动力学,进而其功能,由其自由能景观的结构决定。早期关于肌红蛋白的光解实验表明,蛋白质的自由能景观是分层结构的,具有特征分布的自由能势垒,从而导致异常扩散。已经为一维或高维分层自由能景观推导了分析结果。方法和计算机性能的最新改进使得能够生成足够长的分子动力学 (MD) 轨迹,以提取涵盖多个数量级的动力学信息,从而使蛋白质的广泛分布的能量势垒能够进行中间维度的定量研究。在这项工作中,我们提出了一种从微秒长的 MD 模拟中估计势垒高度分布的非平衡方法。它从主成分分析得出的异常扩散指数推断势垒高度分布,并与简单的分层晶格模型进行比较。这些模型是由自由能势垒隔开的状态的 d 维晶格,其高度分布为 p(ΔG)=1/γexp(-ΔG/γ)。参数 γ 量化了这些模型中自由能景观的“崎岖度”。我们表明,两个参数,即崎岖度和有效维度 d,可以从异常扩散指数推断出来。假设蛋白质的异常扩散指数对 γ 和 d 具有类似的依赖性,我们估计了 500 个小的、单域球状蛋白质的自由能景观的崎岖度在 15 到 20 kT 之间,每个维度的估计精度为 4.2 kT,有效维度在 40 到 60 之间,估计精度为 10 个维度。值得注意的是,有效维度和崎岖度都与蛋白质大小无关,而且两者的崎岖度和有效维度都远小于蛋白质大小的分散度。从这一发现中,我们得出结论,蛋白质自由能景观的这两个特性相当适应每个单个蛋白质的特定功能,并且在相当普遍的情况下,对于球状蛋白质具有功能相关性。

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