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通过时间序列分析重新审视蛋白质能量景观的层次结构。II. 明确溶剂效应的研究。

Hierarchical structure of the energy landscape of proteins revisited by time series analysis. II. Investigation of explicit solvent effects.

作者信息

Alakent Burak, Camurdan Mehmet C, Doruker Pemra

机构信息

Department of Chemical Engineering, Bogazici University, Bebek, Istanbul 34342, Turkey.

出版信息

J Chem Phys. 2005 Oct 8;123(14):144911. doi: 10.1063/1.2042408.

Abstract

Time series analysis tools are employed on the principal modes obtained from the C(alpha) trajectories from two independent molecular-dynamics simulations of alpha-amylase inhibitor (tendamistat). Fluctuations inside an energy minimum (intraminimum motions), transitions between minima (interminimum motions), and relaxations in different hierarchical energy levels are investigated and compared with those encountered in vacuum by using different sampling window sizes and intervals. The low-frequency low-indexed mode relationship, established in vacuum, is also encountered in water, which shows the reliability of the important dynamics information offered by principal components analysis in water. It has been shown that examining a short data collection period (100 ps) may result in a high population of overdamped modes, while some of the low-frequency oscillations (<10 cm(-1)) can be captured in water by using a longer data collection period (1200 ps). Simultaneous analysis of short and long sampling window sizes gives the following picture of the effect of water on protein dynamics. Water makes the protein lose its memory: future conformations are less dependent on previous conformations due to the lowering of energy barriers in hierarchical levels of the energy landscape. In short-time dynamics (<10 ps), damping factors extracted from time series model parameters are lowered. For tendamistat, the friction coefficient in the Langevin equation is found to be around 40-60 cm(-1) for the low-indexed modes, compatible with literature. The fact that water has increased the friction and that on the other hand has lubrication effect at first sight contradicts. However, this comes about because water enhances the transitions between minima and forces the protein to reduce its already inherent inability to maintain oscillations observed in vacuum. Some of the frequencies lower than 10 cm(-1) are found to be overdamped, while those higher than 20 cm(-1) are slightly increased. As for the long-time dynamics in water, it is found that random-walk motion is maintained for approximately 200 ps (about five times of that in vacuum) in the low-indexed modes, showing the lowering of energy barriers between the higher-level minima.

摘要

时间序列分析工具应用于从α-淀粉酶抑制剂(腱糖胺)的两个独立分子动力学模拟的C(α)轨迹获得的主要模式。研究了能量最小值内的波动(最小值内运动)、最小值之间的转变(最小值间运动)以及不同层次能量水平的弛豫,并通过使用不同的采样窗口大小和间隔与在真空中遇到的情况进行比较。在真空中建立的低频低索引模式关系在水中也能遇到,这表明主成分分析在水中提供的重要动力学信息的可靠性。研究表明,检查较短的数据收集期(100皮秒)可能会导致大量过阻尼模式,而通过使用较长的数据收集期(1200皮秒),一些低频振荡(<10厘米⁻¹)可以在水中被捕获。对短和长采样窗口大小的同时分析给出了水对蛋白质动力学影响的如下情况。水使蛋白质失去其记忆:由于能量景观层次水平上的能垒降低,未来构象对先前构象的依赖性降低。在短时间动力学(<10皮秒)中,从时间序列模型参数中提取的阻尼因子降低。对于腱糖胺,朗之万方程中的摩擦系数对于低索引模式约为40 - 60厘米⁻¹,与文献一致。水增加了摩擦力,而另一方面又有润滑作用,这一事实乍一看相互矛盾。然而,这是因为水增强了最小值之间的转变,并迫使蛋白质减少其在真空中已有的维持振荡的固有无能。发现一些低于10厘米⁻¹的频率是过阻尼的,而高于20厘米⁻¹的频率略有增加。至于水中的长时间动力学,发现在低索引模式下随机游走运动在大约200皮秒内(约为真空中的五倍)得以维持,这表明较高层次最小值之间的能垒降低。

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