Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.
Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.
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DOI：
10.1038/s41598-017-03966-5
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发表时间：
2017-06-16
影响因子：
4.6
通讯作者：
Moosavi-Movahedi AA
中科院分区：
文献类型：
--
作者：
Karamzadeh R;Karimi-Jafari MH;Sharifi-Zarchi A;Chitsaz H;Salekdeh GH;Moosavi-Movahedi AA
人蛋白二硫键异构酶(HPDI)是一种必需的四结构域多功能酶。由于其末端区域的二硫键洗牌，hPDI以两种不同构象偏好的氧化状态存在，这两种状态对底物结合和功能活性都是重要的。在这里，我们通过分子动力学(MD)模拟来研究hPDI的氧化还原依赖的构象动力学。通过MD轨迹的主成分分析识别集体结构域运动，并在投影的自由能景观上突出与氧化还原相关的开合结构变化。然后，利用统计机器学习方法提取氧化还原态动力学差异较大的重要结构特征。将结构变化映射到残基相互作用网络的时间序列也提供了动态氧化还原差异的整体表示。在强调持续的长时间相互作用的基础上，提出了一种将这些时间序列网络编译成单个动态残基相互作用网络的方法。氧化和还原状态下drin的差异比较揭示了残基相互作用链，这些链代表了hPDI的催化和配体结合位置之间的潜在变构路径。
The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are important for substrate binding and functional activities. Here, we address the redox-dependent conformational dynamics of hPDI through molecular dynamics (MD) simulations. Collective domain motions are identified by the principal component analysis of MD trajectories and redox-dependent opening-closing structure variations are highlighted on projected free energy landscapes. Then, important structural features that exhibit considerable differences in dynamics of redox states are extracted by statistical machine learning methods. Mapping the structural variations to time series of residue interaction networks also provides a holistic representation of the dynamical redox differences. With emphasizing on persistent long-lasting interactions, an approach is proposed that compiled these time series networks to a single dynamic residue interaction network (DRIN). Differential comparison of DRIN in oxidized and reduced states reveals chains of residue interactions that represent potential allosteric paths between catalytic and ligand binding sites of hPDI.