Classification of projection images of proteins with structural polymorphism by manifold: A simulation study for X-ray free-electron laser diffraction imaging
Classification of projection images of proteins with structural polymorphism by manifold: A simulation study for X-ray free-electron laser diffraction imaging
复制标题
结构多态性蛋白质投影图像的流形分类：X射线自由电子激光衍射成像的模拟研究
DOI：
10.1103/physreve.92.032710
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发表时间：
2015
影响因子：
2.4
通讯作者：
M. Nakasako and M. Ikeguchi
中科院分区：
文献类型：
--
作者：
T. Yoshidome;T. Oroguchi;M. Nakasako and M. Ikeguchi
相干X射线衍射成像（CXDI）使我们能够可视化微米至亚微米尺寸的非晶样品颗粒。使用X射线自由电子激光（XFEL）源，二维衍射图案收集从新鲜的样品提供给照射区域中的“衍射前破坏”计划。最近XFEL脉冲强度的显着增加是有希望的，并将使我们能够在未来使用XFEL-CXDI可视化蛋白质的三维结构。对于使用未来XFEL-CXDI [T. Oroguchi和M. Nakasako，Phys.Rev.E87，022712（2013）10.1103/PhysRevE.87.022712]，我们需要一种算法，该算法可以根据由蛋白质的构象动力学引起的蛋白质的结构多态性对数据进行分类。然而，大多数算法提出的主要要求的构象类的数量，然后结果是由数量偏置。为了改善这一点，在这里，我们研究是否基于流形概念的方法可以分类模拟XFEL-CXDI数据相对于主要采用两种状态的蛋白质的结构多态性。在从分子动力学模拟的轨迹对两个状态和中间状态的构象进行随机采样之后，从每个构象计算衍射图案。分类进行了使用我们定制的程序套件namedenma，在其中的扩散图（DM）的方法开发的基础上的流形的概念实施。我们成功地分类大多数的投影电子密度图相位从衍射图案检索到的两个状态和之间的构象，而不知道的构象类的数量。我们还研究了分类的投影电子密度图的三个国家相对于欧拉角。本研究结果表明，DM方法是必要的，为未来的应用XFEL-CXDI实验的蛋白质，并澄清在未来的应用中应注意的问题。
Coherent x-ray diffraction imaging (CXDI) enables us to visualize noncrystalline sample particles with micrometer to submicrometer dimensions. Using x-ray free-electron laser (XFEL) sources, two-dimensional diffraction patterns are collected from fresh samples supplied to the irradiation area in the “diffraction-before-destruction” scheme. A recent significant increase in the intensity of the XFEL pulse is promising and will allow us to visualize the three-dimensional structures of proteins using XFEL-CXDI in the future. For the protocol proposed for molecular structure determination using future XFEL-CXDI [T. Oroguchi and M. Nakasako, Phys. Rev. E 87, 022712 (2013)10.1103/PhysRevE.87.022712], we require an algorithm that can classify the data in accordance with the structural polymorphism of proteins arising from their conformational dynamics. However, most of the algorithms proposed primarily require the numbers of conformational classes, and then the results are biased by the numbers. To improve this point, here we examine whether a method based on the manifold concept can classify simulated XFEL-CXDI data with respect to the structural polymorphism of a protein that predominantly adopts two states. After random sampling of the conformations of the two states and in-between states from the trajectories of molecular dynamics simulations, a diffraction pattern is calculated from each conformation. Classification was performed by using our custom-made program suite namedenma, in which the diffusion map (DM) method developed based on the manifold concept was implemented. We successfully classify most of the projection electron density maps phase retrieved from diffraction patterns into each of the two states and in-between conformations without the knowledge of the number of conformational classes. We also examined the classification of the projection electron density maps of each of the three states with respect to the Euler angle. The present results suggest that the DM method is imperative for future applications of XFEL-CXDI experiments for proteins, and clarify issues to be taken care of in the future application.