Computational methods for analyzing conformational variability of macromolecular complexes from cryo-electron microscopy images

S Jonić - Current opinion in structural biology, 2017 - Elsevier
Current opinion in structural biology, 2017Elsevier
Highlights•Recent cryo-EM technology allows near-atomic structural resolution of many
complexes.•Conformational changes, functionally relevant, hinder higher resolution of
complexes.•Most image processing procedures do not consider continuous conformational
changes.•New methods are needed to observe details of the change cycle directly from
images.•This review will help the future computational developments in cryo-EM.Thanks to
latest technical advances in cryo-electron microscopy (cryo-EM), structures of …
Highlights
  • Recent cryo-EM technology allows near-atomic structural resolution of many complexes.
  • Conformational changes, functionally relevant, hinder higher resolution of complexes.
  • Most image processing procedures do not consider continuous conformational changes.
  • New methods are needed to observe details of the change cycle directly from images.
  • This review will help the future computational developments in cryo-EM.
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.
Elsevier
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