Accurate global and local 3D alignment of cryo-EM density maps using local spatial structural features

Bintao He, Fa Zhang, Chenjie Feng, Jianyi Yang, Xin Gao () and Renmin Han ()
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Bintao He: Shandong University
Fa Zhang: Beijing Institute of Technology
Chenjie Feng: Ningxia Medical University
Jianyi Yang: Shandong University
Xin Gao: King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Renmin Han: Shandong University

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: Abstract 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.

Date: 2024
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DOI: 10.1038/s41467-024-45861-4

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