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Flexible fitting to cryo-electron microscopy maps with coarse-grained elastic network models

机译:灵活配合以粗大的弹性网络模型的Cryo-Croto-Collecton显微镜地图

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摘要

Cryo-electron microscopy has become an important tool for protein structure determination in recent decades. Since proteins may exist in multiple conformational states, combining high resolution X-ray or NMR structures with cryo-electron microscopy maps is a useful approach to obtain proteins in different functional states. Flexible fitting methods used in cryo-electron microscopy aim to obtain an unknown protein conformation from a high resolution structure and a cryo-electron microscopy map. Since all-atom flexible fitting is computationally expensive, many efficient flexible fitting algorithms that utilize coarse-grained elastic network models have been proposed. In this study, we investigated performance of three coarse-grained elastic network model-based flexible fitting methods (EMFF, iModFit, NMFF) using 25 protein pairs at four resolutions. This study shows that the application of coarse-grained elastic network models to flexible fitting of cryo-electron microscopy maps can provide fast and fruitful models of various conformational states of proteins.
机译:近几十年来,冷冻电子显微镜已成为蛋白质结构测定的重要工具。由于蛋白质可以存在于多个构象状态中,因此将高分辨率X射线或NMR结构与冷冻电子显微镜图组合是一种有用的方法,以获得不同官能状态的蛋白质。在冷冻电子显微镜下使用的柔性拟合方法旨在获得从高分辨率结构和冷冻电子显微镜图中获得未知的蛋白质构象。由于所有原子柔性拟合是计算昂贵的,所以提出了利用粗粒粒子的弹性网络模型的许多有效的灵活拟合算法。在这项研究中,我们在四个分辨率下研究了三种粗粒弹性网络模型的灵活拟合方法(Emff,Imodfit,NMFF)的性能。本研究表明,粗粒粒度的弹性网络模型将柔和拟合的柔和电子显微镜映射的应用可以提供快速且富有成效的蛋白质蛋白质。

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