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用于比较通过三维电子显微镜确定的大分子组装体结构的改进指标。

Improved metrics for comparing structures of macromolecular assemblies determined by 3D electron-microscopy.

作者信息

Joseph Agnel Praveen, Lagerstedt Ingvar, Patwardhan Ardan, Topf Maya, Winn Martyn

机构信息

Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom; Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom; Computational Chemistry and Cheminformatics, Lilly UK, Windlesham GU20 6PH, United Kingdom.

出版信息

J Struct Biol. 2017 Jul;199(1):12-26. doi: 10.1016/j.jsb.2017.05.007. Epub 2017 May 25.

Abstract

Recent developments in 3-dimensional electron microcopy (3D-EM) techniques and a concomitant drive to look at complex molecular structures, have led to a rapid increase in the amount of volume data available for biomolecules. This creates a demand for better methods to analyse the data, including improved scores for comparison, classification and integration of data at different resolutions. To this end, we developed and evaluated a set of scoring functions that compare 3D-EM volumes. To test our scores we used a benchmark set of volume alignments derived from the Electron Microscopy Data Bank. We find that the performance of different scores vary with the map-type, resolution and the extent of overlap between volumes. Importantly, adding the overlap information to the local scoring functions can significantly improve their precision and accuracy in a range of resolutions. A combined score involving the local mutual information and overlap (LMI_OV) performs best overall, irrespective of the map category, resolution or the extent of overlap, and we recommend this score for general use. The local mutual information score itself is found to be more discriminatory than cross-correlation coefficient for intermediate-to-low resolution maps or when the map size and density distribution differ significantly. For comparing map surfaces, we implemented two filters to detect the surface points, including one based on the 'extent of surface exposure'. We show that scores that compare surfaces are useful at low resolutions and for maps with evident surface features. All the scores discussed are implemented in TEMPy (http://tempy.ismb.lon.ac.uk/).

摘要

三维电子显微镜(3D-EM)技术的最新进展以及对复杂分子结构研究的推动,使得可用于生物分子的体积数据量迅速增加。这就需要更好的方法来分析这些数据,包括在不同分辨率下改进数据比较、分类和整合的评分。为此,我们开发并评估了一组用于比较3D-EM体积的评分函数。为了测试我们的评分,我们使用了从电子显微镜数据库中获取的一组体积比对基准。我们发现,不同评分的性能会因图谱类型、分辨率以及体积之间的重叠程度而异。重要的是,将重叠信息添加到局部评分函数中可以在一系列分辨率下显著提高其精度和准确性。涉及局部互信息和重叠的组合评分(LMI_OV)总体表现最佳,无论图谱类别、分辨率或重叠程度如何,我们建议普遍使用此评分。对于中低分辨率图谱或当图谱大小和密度分布差异显著时,发现局部互信息评分本身比互相关系数更具区分性。为了比较图谱表面,我们实现了两种检测表面点的滤波器,其中一种基于“表面暴露程度”。我们表明,比较表面的评分在低分辨率以及具有明显表面特征的图谱中很有用。所讨论的所有评分均在TEMPy(http://tempy.ismb.lon.ac.uk/)中实现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1061/5479444/bba20bd05234/gr1.jpg

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