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cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination
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Journal Article
cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination
2017
Overview
A software tool, cryoSPARC, addresses the speed bottleneck in cryo-EM image processing, enabling automated macromolecular structure determination in hours on a desktop computer without requiring a starting model.
Single-particle electron cryomicroscopy (cryo-EM) is a powerful method for determining the structures of biological macromolecules. With automated microscopes, cryo-EM data can often be obtained in a few days. However, processing cryo-EM image data to reveal heterogeneity in the protein structure and to refine 3D maps to high resolution frequently becomes a severe bottleneck, requiring expert intervention, prior structural knowledge, and weeks of calculations on expensive computer clusters. Here we show that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer. Furthermore, SGD with Bayesian marginalization allows
ab initio
3D classification, enabling automated analysis and discovery of unexpected structures without bias from a reference map. These algorithms are combined in a user-friendly computer program named cryoSPARC (
http://www.cryosparc.com
).
Publisher
Nature Publishing Group US,Nature Publishing Group
Subject
/ Adenosine Triphosphatases - ultrastructure
/ Animals
/ Biomedical Engineering/Biotechnology
/ Computational Biology - methods
/ Cryoelectron Microscopy - methods
/ Image Processing, Computer-Assisted - methods
/ Imaging, Three-Dimensional - methods
/ Plasmodium falciparum - cytology
/ Rats
/ Software
