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== Citation ==
== Citation ==
S. Jonic (2017) Computational methods for analyzing conformational variability of macromolecular complexes from cryo-electron microscopy images. Current Opinion in Structural Biology 43:114–121.
Jonic, S. Computational methods for analyzing conformational variability of macromolecular complexes from cryo-electron microscopy images. Current Opinion in Structural Biology, 2017, 43, 114–121


== Abstract ==
== Abstract ==

Latest revision as of 19:56, 13 January 2017

Citation

Jonic, S. Computational methods for analyzing conformational variability of macromolecular complexes from cryo-electron microscopy images. Current Opinion in Structural Biology, 2017, 43, 114–121

Abstract

Thanks to latest technical advances in cryo-electron microscopy (cryo-EM), structures of macromolecular complexes (viruses, ribosomes, etc.) are now often obtained at near-atomic resolution. Also, studies of conformational changes of complexes, in connection with their function, are gaining ground. Conformational variability analysis is usually done by classifying images in a number of discrete classes supposedly representing all conformational states present in the specimen. However, discrete classes cannot be meaningfully defined when the conformational change is continuous (the specimen contains a continuum of states instead of a few discrete states). For such cases, first image analysis methods that explicitly consider continuous conformational changes were recently developed. The latest developments in cryo-EM image analysis methods for conformational variability analysis are the focus of this review.

Keywords

Structure; dynamics; macromolecular complexes; cryo-electron microscopy; conformational changes; single-particle analysis


Links

http://dx.doi.org/10.1016/j.sbi.2016.12.011


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