Journal
JOURNAL OF COMPUTATIONAL BIOLOGY
Volume 25, Issue 3, Pages 326-336Publisher
MARY ANN LIEBERT, INC
DOI: 10.1089/cmb.2017.0155
Keywords
beta-barrel; cryo-electron microscopy; feature detection; genetic algorithm; ray tracing
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Funding
- Graduate Research Award from the Computing and Software Systems division of the University of Washington Bothell
- [74-0525]
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Cryo-electron microscopy (cryo-EM) is a technique that produces three-dimensional density maps of large protein complexes. This allows for the study of the structure of these proteins. Identifying the secondary structures within proteins is vital to understanding the overall structure and function of the protein. The beta-barrel is one such secondary structure, commonly found in lipocalins and membrane proteins. In this article, we present a novel approach that utilizes genetic algorithms, kd-trees, and ray tracing to automatically detect and extract beta-barrels from cryo-EM density maps. This approach was tested on simulated and experimental density maps with zero, one, or multiple barrels in the density map. The results suggest that the proposed approach is capable of performing automatic detection of beta-barrels from medium resolution cryo-EM density maps.
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