Orientation Determination of Cryo-EM Projection Images Using Reliable Common Lines and Spherical Embeddings.

IF 3.6 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Xiangwen Wang, Qiaoying Jin, Li Zou, Xianghong Lin, Yonggang Lu
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引用次数: 0

Abstract

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a critical technique for recovering and studying the fine 3D structure of proteins and other biological macromolecules, where the primary issue is to determine the orientations of projection images with high levels of noise. This paper proposes a method to determine the orientations of cryo-EM projection images using reliable common lines and spherical embeddings. First, the reliability of common lines between projection images is evaluated using a weighted voting algorithm based on an iterative improvement technique and binarized weighting. Then, the reliable common lines are used to calculate the normal vectors and local X-axis vectors of projection images after two spherical embeddings. Finally, the orientations of projection images are determined by aligning the results of the two spherical embeddings using an orthogonal constraint. Experimental results on both synthetic and real cryo-EM projection image datasets demonstrate that the proposed method can achieve higher accuracy in estimating the orientations of projection images and higher resolution in reconstructing preliminary 3D structures than some common line-based methods, indicating that the proposed method is effective in single-particle cryo-EM 3D reconstruction.

利用可靠的共线和球形嵌入确定冷冻电镜投影图像的方向
单颗粒冷冻电镜(cryo-EM)中的三维(3D)重建是恢复和研究蛋白质及其他生物大分子精细三维结构的关键技术,其中的首要问题是确定高噪声投影图像的方向。本文提出了一种利用可靠的共线和球形嵌入确定冷冻电镜投影图像方向的方法。首先,使用基于迭代改进技术和二值化加权的加权投票算法评估投影图像之间公共线的可靠性。然后,利用可靠的公共线计算经过两次球形嵌入后投影图像的法向量和局部 X 轴向量。最后,利用正交约束对两个球形嵌入的结果进行对齐,从而确定投影图像的方向。在合成和真实冷冻电镜投影图像数据集上的实验结果表明,与一些常见的基于线的方法相比,所提出的方法在估计投影图像的方向方面能达到更高的精度,在重建初步的三维结构方面能达到更高的分辨率,这表明所提出的方法在单粒子冷冻电镜三维重建方面是有效的。
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
479
审稿时长
3 months
期刊介绍: IEEE/ACM Transactions on Computational Biology and Bioinformatics emphasizes the algorithmic, mathematical, statistical and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development of biological databases; and important biological results that are obtained from the use of these methods, programs and databases; the emerging field of Systems Biology, where many forms of data are used to create a computer-based model of a complex biological system
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