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cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

Punjani, Ali, Rubinstein, John L, Fleet, David J, Brubaker, Marcus A·2017·Nature Methods
DOI 10.1038/nmeth.4169
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Abstract

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).

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    From Structural organization of the retriever–CCC endosomal recycling complex (2024) · cites this paper as [65]

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Metadata

Authors
Punjani, A., Rubinstein, J. L., Fleet, D. J., & Brubaker, M. A.
Venue
Nature Methods
Publisher
Springer Science and Business Media LLC
Published
2017-02-06
Volume
14
Issue
3
Pages
290-296
ISSN
  • 1548-7091
  • 1548-7105
DOI
10.1038/nmeth.4169
Cited by
11,626
References
1
Language
en
Licence
www.springer.com/tdm (tdm)

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