Beta-Barrel Detection for Medium Resolution Cryo-Electron Microscopy Density Maps Using Genetic Algorithms and Ray Tracing

Journal of computational biology: A journal of computational molecular cell biology

AlbertNg^1¹ 

[1]Division of Computing and Software Systems, University of Washington Bothell, Bothell, Washington^1

关键词: beta-barrel;    cryo-electron microscopy;    feature detection;    genetic algorithm;    ray tracing;   

DOI  :  10.1089/cmb.2017.0155

学科分类：生物科学（综合）

来源: Mary Ann Liebert, Inc. Publishers

【 摘 要 】

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 -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 -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 -barrels from medium resolution cryo-EM density maps.

【 授权许可】

Unknown