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从蛋白质三维图像分析β链扭曲

Analysis of β-strand Twist from the 3-dimensional Image of a Protein.

作者信息

Islam Tunazzina, Poteat Michael, He Jing

机构信息

Department of Computer Science, Old Dominion University, Norfolk, VA 23529.

出版信息

ACM BCB. 2017 Aug;2017:650-654.

PMID:35838360
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9279011/
Abstract

Electron cryo-microscopy (Cryo-EM) technique produces density maps that are 3-dimensional (3D) images of molecules. It is challenging to derive atomic structures of proteins from 3D images of medium resolutions. Twist of a β-strand has been studied extensively while little of the known information has been directly obtained from the 3D image of a β-sheet. We describe a method to characterize the twist of β-strands from the 3D image of a protein. An analysis of 11 β-sheet images shows that the Averaged Minimum Twist (AMT) angle is larger for a close set than for a far set of β-traces.

摘要

电子冷冻显微镜(Cryo-EM)技术可生成分子的三维(3D)图像密度图。从中等分辨率的3D图像推导蛋白质的原子结构具有挑战性。β-链的扭曲已得到广泛研究,而很少有已知信息是直接从β-折叠的3D图像中获得的。我们描述了一种从蛋白质的3D图像中表征β-链扭曲的方法。对11个β-折叠图像的分析表明,β-链迹线紧密组的平均最小扭曲(AMT)角大于远组的平均最小扭曲角。

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本文引用的文献

1
An Iterative Bézier Method for Fitting Beta-sheet Component of a Cryo-EM Density Map.一种用于拟合冷冻电镜密度图中β-折叠组件的迭代贝塞尔方法。
Mol Based Math Biol. 2017 Jan;5(1):31-39. doi: 10.1515/mlbmb-2017-0003. Epub 2017 Apr 27.
2
Deep Convolutional Neural Networks for Detecting Secondary Structures in Protein Density Maps from Cryo-Electron Microscopy.用于检测冷冻电子显微镜蛋白质密度图中二级结构的深度卷积神经网络
Proceedings (IEEE Int Conf Bioinformatics Biomed). 2016 Dec;2016:41-46. doi: 10.1109/BIBM.2016.7822490. Epub 2017 Jan 19.
3
Structure of a headful DNA-packaging bacterial virus at 2.9 Å resolution by electron cryo-microscopy.
通过电子冷冻显微镜以 2.9 Å 分辨率得到的一个满载 DNA 的细菌病毒的结构。
Proc Natl Acad Sci U S A. 2017 Apr 4;114(14):3601-3606. doi: 10.1073/pnas.1615025114. Epub 2017 Mar 20.
4
Accurate model annotation of a near-atomic resolution cryo-EM map.近原子分辨率冷冻电镜图谱的精确模型注释。
Proc Natl Acad Sci U S A. 2017 Mar 21;114(12):3103-3108. doi: 10.1073/pnas.1621152114. Epub 2017 Mar 7.
5
Modeling Beta-Traces for Beta-Barrels from Cryo-EM Density Maps.利用冷冻电镜密度图对β桶的β迹线进行建模。
Biomed Res Int. 2017;2017:1793213. doi: 10.1155/2017/1793213. Epub 2017 Jan 10.
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An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images.一种在冷冻电镜图像拓扑结构确定中结合多个二级结构预测的有效计算方法。
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7
Solving the Secondary Structure Matching Problem in Cryo-EM De Novo Modeling Using a Constrained K-Shortest Path Graph Algorithm.使用约束K最短路径图算法解决冷冻电镜从头建模中的二级结构匹配问题。
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8
2.2 Å resolution cryo-EM structure of β-galactosidase in complex with a cell-permeant inhibitor.与一种细胞渗透性抑制剂结合的β-半乳糖苷酶的2.2埃分辨率冷冻电镜结构。
Science. 2015 Jun 5;348(6239):1147-51. doi: 10.1126/science.aab1576. Epub 2015 May 7.
9
Tracing beta strands using StrandTwister from cryo-EM density maps at medium resolutions.使用StrandTwister从中等分辨率的冷冻电镜密度图追踪β链。
Structure. 2014 Nov 4;22(11):1665-76. doi: 10.1016/j.str.2014.08.017. Epub 2014 Oct 9.
10
A machine learning approach for the identification of protein secondary structure elements from electron cryo-microscopy density maps.一种基于机器学习的方法,用于从电子冷冻显微镜密度图中识别蛋白质二级结构元件。
Biopolymers. 2012 Sep;97(9):698-708. doi: 10.1002/bip.22063.