School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, 730000, China.
School of Life Sciences, Lanzhou University, Lanzhou, Gansu, 730000, China.
Commun Biol. 2022 Apr 4;5(1):304. doi: 10.1038/s42003-022-03255-6.
Single-particle analysis (SPA) in cryo-electron microscopy has become a powerful tool for determining and studying the macromolecular structure at an atomic level. However, since the SPA problem is a non-convex optimization problem with enormous search space and there is high level of noise in the input images, the existing methods may produce biased or even wrong final models. In this work, to deal with the problem, consistent constraints from the input data are explored in an embedding space, a 3D spherical surface. More specifically, the orientation of a projection image is represented by two intersection points of the normal vector and the local X-axis vector of the projection image on the unit spherical surface. To determine the orientations of the projection images, the global consistency constraints of the relative orientations of all the projection images are satisfied by two spherical embeddings which estimate the normal vectors and the local X-axis vectors of the projection images respectively. Compared to the traditional methods, the proposed method is shown to be able to rectify the initial computation errors and produce a more accurate estimation of the projection angles, which results in a better final model reconstruction from the noisy image data.
在冷冻电子显微镜中，单颗粒分析（SPA）已成为确定和研究大分子结构在原子水平上的有力工具。然而，由于 SPA 问题是一个具有巨大搜索空间的非凸优化问题，并且输入图像中有高水平的噪声，因此现有方法可能会产生有偏差甚至错误的最终模型。在这项工作中，为了解决这个问题，在嵌入空间（一个三维球面）中探索了来自输入数据的一致约束。更具体地说，投影图像的方向由投影图像上的法向量和局部 X 轴向量与单位球面的两个交点表示。为了确定投影图像的方向，通过两个分别估计投影图像的法向量和局部 X 轴向量的球面嵌入来满足所有投影图像的相对方向的全局一致性约束。与传统方法相比，所提出的方法能够纠正初始计算错误，并对投影角度进行更准确的估计，从而从噪声图像数据中获得更好的最终模型重建。
