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Protein Cell. 2016 Jan;7(1):46-62. doi: 10.1007/s13238-015-0229-2. Epub 2015 Dec 17.

A local-optimization refinement algorithm in single particle analysis for macromolecular complex with multiple rigid modules.

Author information

1
Department of Biophysics, College of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China.
2
Key Lab of Intelligent Information Processing and Advanced Computing Research Lab, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
3
University of Chinese Academy of Sciences, Beijing, 100049, China.
4
Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06511, USA.
5
Department of Biophysics, College of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China. ccyin@hsc.pku.edu.cn.
6
National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China. feisun@ibp.ac.cn.
7
University of Chinese Academy of Sciences, Beijing, 100049, China. feisun@ibp.ac.cn.
8
Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China. feisun@ibp.ac.cn.

Abstract

Single particle analysis, which can be regarded as an average of signals from thousands or even millions of particle projections, is an efficient method to study the three-dimensional structures of biological macromolecules. An intrinsic assumption in single particle analysis is that all the analyzed particles must have identical composition and conformation. Thus specimen heterogeneity in either composition or conformation has raised great challenges for high-resolution analysis. For particles with multiple conformations, inaccurate alignments and orientation parameters will yield an averaged map with diminished resolution and smeared density. Besides extensive classification approaches, here based on the assumption that the macromolecular complex is made up of multiple rigid modules whose relative orientations and positions are in slight fluctuation around equilibriums, we propose a new method called as local optimization refinement to address this conformational heterogeneity for an improved resolution. The key idea is to optimize the orientation and shift parameters of each rigid module and then reconstruct their three-dimensional structures individually. Using simulated data of 80S/70S ribosomes with relative fluctuations between the large (60S/50S) and the small (40S/30S) subunits, we tested this algorithm and found that the resolutions of both subunits are significantly improved. Our method provides a proof-of-principle solution for high-resolution single particle analysis of macromolecular complexes with dynamic conformations.

KEYWORDS:

conformational heterogeneity; cryo-electron microscopy; local optimization refinement; rigid module; single particle analysis

PMID:
26678751
PMCID:
PMC4707152
DOI:
10.1007/s13238-015-0229-2
[Indexed for MEDLINE]
Free PMC Article

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