Progressive assembly of multi-domain protein structures from cryo-EM density maps.
Progressive assembly of multi-domain protein structures from cryo-EM density maps.
复制标题
从冷冻电镜密度图逐步组装多域蛋白质结构。
DOI：
10.1038/s43588-022-00232-1
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发表时间：
2022-04
期刊：
影响因子：
--
通讯作者：
Zhang, Yang
中科院分区：
文献类型：
--
作者：
Zhou, Xiaogen;Li, Yang;Zhang, Chengxin;Zheng, Wei;Zhang, Guijun;Zhang, Yang
低温电子显微镜的发展为大尺寸蛋白质结构的测定提供了可能。然而，解决多结构域蛋白质的成功率仍然很低，因为难以建模结构域间的方向。在这里，我们开发了使用低温电子显微镜（DEMO-EM）的域增强建模，这是一种通过渐进的结构细化过程将刚体域拟合和柔性装配模拟与深度神经网络域间距离分布相结合来从低温电子显微镜图组装多域结构的自动方法。该方法在包含多达12个连续和不连续结构域的大规模蛋白质基准集上进行了测试，具有中等至低分辨率的密度图，其中DEMO-EM产生的模型具有正确的结构域间方向（模板建模得分（TM得分）>0.5），97%的情况下优于最先进的方法。DEMO-EM应用于严重急性呼吸综合征冠状病毒2型基因组，并生成模型，平均TM评分和均方根偏差分别为0.97和1.3 μ m，相对于沉积的结构。这些结果证明了一个有效的管道，使自动化和可靠的大规模多域蛋白质结构建模从冷冻电子显微镜图。
Progress in cryo-electron microscopy has provided the potential for large-size protein structure determination. However, the success rate for solving multi-domain proteins remains low because of the difficulty in modelling inter-domain orientations. Here we developed domain enhanced modeling using cryo-electron microscopy (DEMO-EM), an automatic method to assemble multi-domain structures from cryo-electron microscopy maps through a progressive structural refinement procedure combining rigid-body domain fitting and flexible assembly simulations with deep-neural-network inter-domain distance profiles. The method was tested on a large-scale benchmark set of proteins containing up to 12 continuous and discontinuous domains with medium- to low-resolution density maps, where DEMO-EM produced models with correct inter-domain orientations (template modeling score (TM-score) >0.5) for 97% of cases and outperformed state-of-the-art methods. DEMO-EM was applied to the severe acute respiratory syndrome coronavirus 2 genome and generated models with average TM-score and root-mean-square deviation of 0.97 and 1.3 Å, respectively, with respect to the deposited structures. These results demonstrate an efficient pipeline that enables automated and reliable large-scale multi-domain protein structure modelling from cryo-electron microscopy maps.
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