Document Type
Article
Publication Date
2015
DOI
10.1016/j.jsb.2015.09.011
Publication Title
Journal of Structural Biology
Volume
192
Issue
2
Pages
255-261
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 8 angstrom) and medium (4-8 angstrom) 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: naive 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.
Original Publication Citation
Wriggers, W., & He, J. (2015). Numerical geometry of map and model assessment. Journal of Structural Biology, 192(2), 255-261. doi:10.1016/j.jsb.2015.09.011
Repository Citation
Wriggers, Willy and He, Jing, "Numerical Geometry of Map and Model Assessment" (2015). Mechanical & Aerospace Engineering Faculty Publications. 58.
https://digitalcommons.odu.edu/mae_fac_pubs/58
Comments
NOTE: This is the author's post-print version of a work that was published in Journal of Structural Biology. The final version was published as:
Wriggers, W., & He, J. (2015). Numerical geometry of map and model assessment. Journal of Structural Biology, 192(2), 255-261. doi:10.1016/j.jsb.2015.09.011
Available at: http://dx.doi.org/10.1016/j.jsb.2015.09.011