He Bintao, Zhang Fa, Feng Chenjie, Yang Jianyi, Gao Xin, Han Renmin
Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, 266237, China.
School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China.
Nat Commun. 2024 Feb 21;15(1):1593. doi: 10.1038/s41467-024-45861-4.
Advances in cryo-electron microscopy (cryo-EM) imaging technologies have led to a rapidly increasing number of cryo-EM density maps. Alignment and comparison of density maps play a crucial role in interpreting structural information, such as conformational heterogeneity analysis using global alignment and atomic model assembly through local alignment. Here, we present a fast and accurate global and local cryo-EM density map alignment method called CryoAlign, that leverages local density feature descriptors to capture spatial structure similarities. CryoAlign is a feature-based cryo-EM map alignment tool, in which the employment of feature-based architecture enables the rapid establishment of point pair correspondences and robust estimation of alignment parameters. Extensive experimental evaluations demonstrate the superiority of CryoAlign over the existing methods in terms of both alignment accuracy and speed.
冷冻电子显微镜(cryo-EM)成像技术的进步导致冷冻电镜密度图的数量迅速增加。密度图的比对和比较在解释结构信息方面起着至关重要的作用,例如使用全局比对进行构象异质性分析以及通过局部比对进行原子模型组装。在此,我们提出了一种快速且准确的全局和局部冷冻电镜密度图比对方法,称为CryoAlign,它利用局部密度特征描述符来捕捉空间结构相似性。CryoAlign是一种基于特征的冷冻电镜图比对工具,其中基于特征的架构使得能够快速建立点对对应关系并稳健地估计比对参数。广泛的实验评估证明了CryoAlign在比对准确性和速度方面均优于现有方法。