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域Fit:在使用AlphaFold2预测模型的中间分辨率的冷EM图中识别蛋白质域

Jerry Gao¹, Maxwell Tong¹, Chinkyu Lee²

¹Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC H3A 0C7, Canada; Centre de recherche en biologie structurale, McGill University, Montréal, QC H3G 0B1, Canada.

Structure (London, England : 1993)

|May 16, 2024

概括

DomainFit是一个新的工具,用于在冷电子显微镜 (cryo-EM) 地图中识别蛋白质,特别是在低分辨率下. 它通过分析蛋白质域来帮助理解复杂的细胞结构.

科学领域:

结构生物学是结构生物学.
生物化学生物化学
细胞生物学细胞生物学

背景情况:

低温电子显微镜 (cryo-EM) 允许对宏分子复合物的结构性确定.
现场和活体结构生物学揭示了原生复合体,通常与未识别的蛋白质.
在低于4 Å分辨率的冷电磁图中识别蛋白质是具有挑战性的,原因是不可靠的侧链可视化.

研究的目的:

介绍DomainFit,这是一个新的程序,用于半自动化,在冷-EM地图中的域级蛋白质识别.
为了应对在低分辨率的冷EM数据 (低于4 Å) 中识别蛋白质的挑战.

主要方法:

域名Fit利用AlphaFold2预测模型,将域名安装到冷EM地图中.
该程序进行统计分析,以确定为观察到的密度做出贡献的蛋白质域和候选物.
应用DomainFit来分析Tetrahymena thermophila的冷EM数据.

主要成果:

"DomainFit"可以从冷EM密度图中实现半自动化蛋白质识别.
该工具对于分辨率低于4 Å的地图特别有效.
在Tetrahymena thermophila中发现了两种微管内部蛋白质,其中一种具有CCDC81域,局部位于双重微管的近位区域.

结论:

"DomainFit"是一个有价值的工具,可以通过在低分辨率的冷EM地图中识别蛋白质来推进in situ结构生物学.
识别新的微管相关蛋白质有助于理解微管的结构和功能.
这种方法有助于描述复杂的细胞机械和过程.

关键词:

在AlphaFold2建模中,使用的是AlphaFold2模型.西里亚西里亚是什么意思低温电磁波冷却器 (Cryo-EM) 是一个非常好的方法.化-ETET可以使用.域名识别域名识别一个双重的双重.微管内蛋白质是微管内部的蛋白质.蛋白质识别蛋白质识别亚断层图谱的平均值是

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