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J Struct Biol. 2015 Nov;192(2):255-61. doi: 10.1016/j.jsb.2015.09.011. Epub 2015 Sep 28.

Numerical geometry of map and model assessment.

Author information

1
Department of Mechanical & Aerospace Engineering, Old Dominion University, Norfolk, VA 23529, United States. Electronic address: wwrigger@odu.edu.
2
Department of Computer Science, Old Dominion University, Norfolk, VA 23529, United States. Electronic address: jhe@odu.edu.

Abstract

We are describing best practices and assessment strategies for the atomic interpretation of cryo-electron microscopy (cryo-EM) maps. Multiscale numerical geometry strategies in the Situs package and in secondary structure detection software are currently evolving due to the recent increases in cryo-EM resolution. Criteria that aim to predict the accuracy of fitted atomic models at low (worse than 8Å) and medium (4-8 Å) resolutions remain challenging. However, a high level of confidence in atomic models can be achieved by combining such criteria. The observed errors are due to map-model discrepancies and due to the effect of imperfect global docking strategies. Extending the earlier motion capture approach developed for flexible fitting, we use simulated fiducials (pseudoatoms) at varying levels of coarse-graining to track the local drift of structural features. We compare three tracking approaches: naïve vector quantization, a smoothly deformable model, and a tessellation of the structure into rigid Voronoi cells, which are fitted using a multi-fragment refinement approach. The lowest error is an upper bound for the (small) discrepancy between the crystal structure and the EM map due to different conditions in their structure determination. When internal features such as secondary structures are visible in medium-resolution EM maps, it is possible to extend the idea of point-based fiducials to more complex geometric representations such as helical axes, strands, and skeletons. We propose quantitative strategies to assess map-model pairs when such secondary structure patterns are prominent.

KEYWORDS:

Cryo-electron microscopy; Fitting; Protein structure; Secondary structure; Validation

PMID:
26416532
PMCID:
PMC4786442
DOI:
10.1016/j.jsb.2015.09.011
[Indexed for MEDLINE]
Free PMC Article

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