Andy Zhang, Oscar Mickelin, Joe Kileel, Eric J Verbeke, Nicholas F Marshall, Marc Aurèle Gilles, Amit Singer
{"title":"Moment-based metrics for molecules computable from cryogenic electron microscopy images.","authors":"Andy Zhang, Oscar Mickelin, Joe Kileel, Eric J Verbeke, Nicholas F Marshall, Marc Aurèle Gilles, Amit Singer","doi":"10.1017/S2633903X24000023","DOIUrl":null,"url":null,"abstract":"<p><p>Single-particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of recovering the high-resolution three-dimensional (3D) structure of biological macromolecules from many noisy and randomly oriented projection images. One notable approach to 3D reconstruction, known as Kam's method, relies on the moments of the two-dimensional (2D) images. Inspired by Kam's method, we introduce a rotationally invariant metric between two molecular structures, which does not require 3D alignment. Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3D reconstruction. Additionally, the latter metric does not assume a uniform distribution of viewing angles. We demonstrate the uses of the new metrics on synthetic and experimental datasets, highlighting their ability to measure structural similarity.</p>","PeriodicalId":72371,"journal":{"name":"Biological imaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10951804/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/S2633903X24000023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Single-particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of recovering the high-resolution three-dimensional (3D) structure of biological macromolecules from many noisy and randomly oriented projection images. One notable approach to 3D reconstruction, known as Kam's method, relies on the moments of the two-dimensional (2D) images. Inspired by Kam's method, we introduce a rotationally invariant metric between two molecular structures, which does not require 3D alignment. Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3D reconstruction. Additionally, the latter metric does not assume a uniform distribution of viewing angles. We demonstrate the uses of the new metrics on synthetic and experimental datasets, highlighting their ability to measure structural similarity.
单颗粒低温电子显微镜(cryo-EM)是一种成像技术,能够从许多嘈杂和随机定向的投影图像中恢复生物大分子的高分辨率三维(3D)结构。一种著名的三维重建方法,即 Kam 方法,依赖于二维(2D)图像的矩。受 Kam 方法的启发,我们引入了两个分子结构之间的旋转不变度量,它不需要三维对齐。此外,我们还引入了投影图像堆栈与分子结构之间的度量,该度量对旋转和反射不变,无需进行三维重建。此外,后一种度量方法不假定观察角度的均匀分布。我们在合成数据集和实验数据集上演示了新度量方法的应用,突出了它们测量结构相似性的能力。