Indexed on: 05 Dec '18Published on: 05 Dec '18Published in: Current Opinion in Structural Biology
Electron cryomicroscopy (cryo-EM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. Cryo-EM has been successfully used to visualize molecules such as ribosomes, viruses, and ion channels, for example. Obtaining structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryo-EM a scientific rebirth. Because of imaging improvements, image processing and analysis of the resultant images have increased the resolution such that molecular structures can be resolved at the atomic level. Cryo-EM is ripe with stimulating image processing challenges. In this article, we will touch on the most essential in order to build an accurate structural three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. With this review, however, we will highlight fresh approaches from new and varied angles for each image processing sub-problem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking. Copyright © 2018 Elsevier Ltd. All rights reserved.