Ng Albert, Si Dong
1 Division of Computing and Software Systems, University of Washington Bothell , Bothell, Washington.
J Comput Biol. 2018 Mar;25(3):326-336. doi: 10.1089/cmb.2017.0155. Epub 2017 Oct 16.
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 [Formula: see text]-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 [Formula: see text]-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 [Formula: see text]-barrels from medium resolution cryo-EM density maps.
冷冻电子显微镜（cryo-EM）是一种用于生成大型蛋白质复合物三维密度图的技术。这使得对这些蛋白质的结构进行研究成为可能。识别蛋白质中的二级结构对于理解蛋白质的整体结构和功能至关重要。β-桶就是这样一种二级结构，常见于脂质运载蛋白和膜蛋白中。在本文中，我们提出了一种新颖的方法，该方法利用遗传算法、kd树和光线追踪从冷冻电子显微镜密度图中自动检测和提取β-桶。此方法在模拟和实验密度图上进行了测试，这些密度图中含有零个、一个或多个桶状结构。结果表明，所提出的方法能够从中等分辨率的冷冻电子显微镜密度图中自动检测β-桶。
