English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Fast and accurate reference-free alignment of subtomograms

MPS-Authors
/persons/resource/persons77858

Chen,  Yuxiang
Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons78500

Pfeffer,  Stefan
Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons78135

Hrabe,  Thomas
Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons98592

Schuller,  Jan Michael
Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons77965

Förster,  Friedrich
Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Chen, Y., Pfeffer, S., Hrabe, T., Schuller, J. M., & Förster, F. (2013). Fast and accurate reference-free alignment of subtomograms. JOURNAL OF STRUCTURAL BIOLOGY, 182(3), 235-245. doi:10.1016/j.jsb.2013.03.002.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-FCF1-8
Abstract
In cryoelectron tomography alignment and averaging of subtomograms, each dnepicting the same macromolecule, improves the resolution compared to the individual subtomogram. Major challenges of subtomogram alignment are noise enhancement due to overfitting, the bias of an initial reference in the iterative alignment process, and the computational cost of processing increasingly large amounts of data. Here, we propose an efficient and accurate alignment algorithm via a generalized convolution theorem, which allows computation of a constrained correlation function using spherical harmonics. This formulation increases computational speed of rotational matching dramatically compared to rotation search in Cartesian space without sacrificing accuracy in contrast to other spherical harmonic based approaches. Using this sampling method, a reference-free alignment procedure is proposed to tackle reference bias and overfitting, which also includes contrast transfer function correction by Wiener filtering. Application of the method to simulated data allowed us to obtain resolutions near the ground truth. For two experimental datasets, ribosomes from yeast lysate and purified 20S proteasomes, we achieved reconstructions of approximately 20 angstrom and 16 angstrom, respectively. The software is ready-to-use and made public to the community. (c) 2013 Elsevier Inc. All rights reserved.