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自动化 MrBUMP 搜索模型识别在冷冻电镜中的图谱拟合中的重新部署。

Redeployment of automated MrBUMP search-model identification for map fitting in cryo-EM.

机构信息

Institute of Structural, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom.

UKRI-STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.

出版信息

Acta Crystallogr D Struct Biol. 2021 Nov 1;77(Pt 11):1378-1385. doi: 10.1107/S2059798321009165. Epub 2021 Oct 20.

Abstract

In crystallography, the phase problem can often be addressed by the careful preparation of molecular-replacement search models. This has led to the development of pipelines such as MrBUMP that can automatically identify homologous proteins from an input sequence and edit them to focus on the areas that are most conserved. Many of these approaches can be applied directly to cryo-EM to help discover, prepare and correctly place models (here called cryo-EM search models) into electrostatic potential maps. This can significantly reduce the amount of manual model building that is required for structure determination. Here, MrBUMP is repurposed to fit automatically obtained PDB-derived chains and domains into cryo-EM maps. MrBUMP was successfully able to identify and place cryo-EM search models across a range of resolutions. Methods such as map segmentation are also explored as potential routes to improved performance. Map segmentation was also found to improve the effectiveness of the pipeline for higher resolution (<8 Å) data sets.

摘要

在晶体学中,通过精心准备分子置换搜索模型,通常可以解决相位问题。这导致了诸如 MrBUMP 等管道的发展,这些管道可以自动从输入序列中识别同源蛋白质,并对其进行编辑,以专注于最保守的区域。这些方法中的许多都可以直接应用于 cryo-EM,以帮助发现、准备和正确放置模型(这里称为 cryo-EM 搜索模型)到静电势图中。这可以大大减少结构确定所需的手动模型构建量。在这里,MrBUMP 被重新用于自动将从 PDB 获得的链和结构域拟合到 cryo-EM 图谱中。MrBUMP 成功地能够识别和放置 cryo-EM 搜索模型,涵盖了一系列分辨率。还探索了诸如图谱分割等方法作为提高性能的潜在途径。还发现图谱分割提高了该管道对更高分辨率(<8 Å)数据集的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94fd/8561737/7fa4cb7208d7/d-77-01378-fig1.jpg

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