Saved in:
Bibliographic Details
Main Authors: Zhang, Qi, Bao, Chenglong, Lin, Hai, Hu, Mingxu
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2301.05426
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915004602646528
author Zhang, Qi
Bao, Chenglong
Lin, Hai
Hu, Mingxu
author_facet Zhang, Qi
Bao, Chenglong
Lin, Hai
Hu, Mingxu
contents Cryogenic electron microscopy (cryo-EM) is an invaluable technique for determining high-resolution three-dimensional structures of biological macromolecules using transmission particle images. The inherent symmetry in these macromolecules is advantageous, as it allows each image to represent multiple perspectives. However, data processing that incorporates symmetry can inadvertently average out asymmetric features. Therefore, a key preliminary step is to visualize 2D asymmetric features in the particle images, which requires estimating orientation statistics under molecular symmetry constraints. Motivated by this challenge, we introduce a novel method for estimating the mean and variance of orientations with molecular symmetry. Utilizing tools from non-unique games, we show that our proposed non-convex formulation can be simplified as a semi-definite programming problem. Moreover, we propose a novel rounding procedure to determine the representative values. Experimental results demonstrate that the proposed approach can find the global minima and the appropriate representatives with a high degree of probability. We release the code of our method as an open-source Python package named pySymStat. Finally, we apply pySymStat to visualize an asymmetric feature in an icosahedral virus, a feat that proved unachievable using the conventional 2D classification method in RELION.
format Preprint
id arxiv_https___arxiv_org_abs_2301_05426
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Averaging Orientations with Molecular Symmetry in Cryo-EM
Zhang, Qi
Bao, Chenglong
Lin, Hai
Hu, Mingxu
Optimization and Control
Cryogenic electron microscopy (cryo-EM) is an invaluable technique for determining high-resolution three-dimensional structures of biological macromolecules using transmission particle images. The inherent symmetry in these macromolecules is advantageous, as it allows each image to represent multiple perspectives. However, data processing that incorporates symmetry can inadvertently average out asymmetric features. Therefore, a key preliminary step is to visualize 2D asymmetric features in the particle images, which requires estimating orientation statistics under molecular symmetry constraints. Motivated by this challenge, we introduce a novel method for estimating the mean and variance of orientations with molecular symmetry. Utilizing tools from non-unique games, we show that our proposed non-convex formulation can be simplified as a semi-definite programming problem. Moreover, we propose a novel rounding procedure to determine the representative values. Experimental results demonstrate that the proposed approach can find the global minima and the appropriate representatives with a high degree of probability. We release the code of our method as an open-source Python package named pySymStat. Finally, we apply pySymStat to visualize an asymmetric feature in an icosahedral virus, a feat that proved unachievable using the conventional 2D classification method in RELION.
title Averaging Orientations with Molecular Symmetry in Cryo-EM
topic Optimization and Control
url https://arxiv.org/abs/2301.05426