Modeling conformational ensembles of slow functional motions in Pin1-WW.
Modeling conformational ensembles of slow functional motions in Pin1-WW.
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DOI：
10.1371/journal.pcbi.1001015
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发表时间：
2010-12-02
影响因子：
4.3
通讯作者：
Izaguirre JA
中科院分区：
文献类型：
--
作者：
Morcos F;Chatterjee S;McClendon CL;Brenner PR;López-Rendón R;Zintsmaster J;Ercsey-Ravasz M;Sweet CR;Jacobson MP;Peng JW;Izaguirre JA
蛋白质之间的相互作用通常是由在微秒到毫秒时间尺度上经历构象动力学的柔性环介导的。核磁共振弛豫研究可以绘制出这些动态。然而，定义作为松弛数据基础的互转换构象网络仍然具有挑战性。在这里，我们将核磁共振弛豫实验与模拟相结合，以可视化相互转换的构象网络。我们用载子Pin1-WW结构域证明了我们的方法，其中NMR已经揭示了毫秒范围内柔性环路的构象动力学。我们使用马尔可夫状态模型（MSM）对自由能景观进行采样和聚类，其中主要交换态和次要交换态与核磁共振弛化数据高度相关，NOE违规率低。这些MSM是缓慢相互转换，亚稳态的宏观状态和快速相互转换的微观状态的分层集成。我们发现了一个低人口状态，主要由全息构象组成，是宏观状态之间大多数路径访问的“枢纽”。这些结果表明，在载脂蛋白Pin1-WW的内在动力学中，全息和替代构象之间的构象平衡预先存在。利用互信息方法MutInf对相关运动进行量化分析，发现WW动力学不仅在底物识别中发挥作用，而且可能有助于将WW结构域上的底物结合位点与催化结构域上的结合位点偶联。我们的工作代表了构建相互转换构象状态网络的重要一步，并且是普遍适用的。天然状态下的蛋白质可以有多种形状或构象；这种构象可塑性对许多系统的调节和功能至关重要。然而，要确定这些不同的构象在原子水平上是什么样子仍然很困难。我们提出了一种使用核磁共振、分子动力学模拟和马尔可夫状态模型的新方法，以揭示与现有数据一致的过多构象的地图。我们应用该方法研究了Pin1脯氨酸顺反异构酶的WW结构域在底物结合过程中使用的内在动力学，发现核磁共振数据最好地解释为两个缓慢相互转换的许多亚稳构象集，而不是两个不同的宏观状态。我们的方法为核磁共振数据增加了实质性的价值，因为它提供了与观测到的弛豫数据一致的构象变化的动力学“图”。这种方法与信息论相结合，帮助我们确定了可能将Pin1 WW结构域的底物结合与催化亚基结合的特定构象变化。
Protein-protein interactions are often mediated by flexible loops that experience conformational dynamics on the microsecond to millisecond time scales. NMR relaxation studies can map these dynamics. However, defining the network of inter-converting conformers that underlie the relaxation data remains generally challenging. Here, we combine NMR relaxation experiments with simulation to visualize networks of inter-converting conformers. We demonstrate our approach with the apo Pin1-WW domain, for which NMR has revealed conformational dynamics of a flexible loop in the millisecond range. We sample and cluster the free energy landscape using Markov State Models (MSM) with major and minor exchange states with high correlation with the NMR relaxation data and low NOE violations. These MSM are hierarchical ensembles of slowly interconverting, metastable macrostates and rapidly interconverting microstates. We found a low population state that consists primarily of holo-like conformations and is a “hub” visited by most pathways between macrostates. These results suggest that conformational equilibria between holo-like and alternative conformers pre-exist in the intrinsic dynamics of apo Pin1-WW. Analysis using MutInf, a mutual information method for quantifying correlated motions, reveals that WW dynamics not only play a role in substrate recognition, but also may help couple the substrate binding site on the WW domain to the one on the catalytic domain. Our work represents an important step towards building networks of inter-converting conformational states and is generally applicable. Proteins in their native state can adopt a plethora of shapes, or conformations; this conformational plasticity is critical for regulation and function in many systems. However, it has remained difficult to determine what these different conformations look like at the atomic level. We present a novel way to use Nuclear Magnetic Resonance, Molecular Dynamics Simulations, and Markov State Models to uncover a map of this plethora of conformations that is consistent with the available data. We applied this method to study the intrinsic dynamics used in substrate binding by the WW domain of the Pin1 proline cis-trans isomerase and found that the NMR data were best explained by two slowly-interconverting sets of many metastable conformations rather than two distinct macrostates. Substantial value is added to the NMR data by our method since it provides a kinetic “map” of conformational changes consistent with the observed relaxation data. Such an approach, in combination with information theory, helped us to identify specific conformational changes that might couple substrate binding at the Pin1 WW domain to the catalytic subunit.
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影响因子：
4.8
作者：
Jacobs, DM;Saxena, K;Fiebig, KM
通讯作者：
Fiebig, KM
影响因子：
2.9
作者：
BLACKLEDGE, MJ;BRUSCHWEILER, R;ERNST, RR
通讯作者：
ERNST, RR
影响因子：
15
作者：
Akke, M;Palmer, AG
通讯作者：
Palmer, AG
DOI：
10.1073/pnas.0408970102
发表时间：
2005-05-10
影响因子：
11.1
作者：
Andrec, M;Felts, AK;Levy, RM
通讯作者：
Levy, RM
DOI：
10.1073/pnas.182542699
发表时间：
2002-10-29
影响因子：
11.1
作者：
Fersht, AR
通讯作者：
Fersht, AR