Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
J Mol Biol. 2020 Sep 4;432(19):5365-5377. doi: 10.1016/j.jmb.2020.07.027. Epub 2020 Aug 6.
The rapid progress of cryo-electron microscopy (cryo-EM) in structural biology has raised an urgent need for robust methods to create and refine atomic-level structural models using low-resolution EM density maps. We propose a new protocol to create initial models using I-TASSER protein structure prediction, followed by EM density map-based rigid-body structure fitting, flexible fragment adjustment and atomic-level structure refinement simulations. The protocol was tested on a large set of 285 non-homologous proteins and generated structural models with correct folds for 260 proteins, where 28% had RMSDs below 2 Å. Compared to other state-of-the-art methods, the major advantage of the proposed pipeline lies in the uniform structure prediction and refinement protocol, as well as the extensive structural re-assembly simulations, which allow for low-to-medium resolution EM density map-guided structure modeling starting from amino acid sequences. Interestingly, the quality of both the image fitting and subsequent structure refinement was found to be strongly correlated with the correctness of the initial I-TASSER models; this is mainly due to the different correlation patterns observed between force field and structural quality for the models with template modeling score (or TM-score, a metric quantifying the similarity of models to the native) above and below a threshold of 0.5. Overall, the results demonstrate a new avenue that is ready to use for large-scale cryo-EM-based structure modeling and atomic-level density map-guided structure refinement.
冷冻电镜(cryo-EM)在结构生物学中的快速发展提出了一个迫切的需求,即用低分辨率的 EM 密度图创建和完善原子级结构模型的稳健方法。我们提出了一个新的方案,使用 I-TASSER 蛋白质结构预测来创建初始模型,然后进行基于 EM 密度图的刚体结构拟合、柔性片段调整和原子级结构精修模拟。该方案在一组 285 个非同源蛋白质上进行了测试,为 260 个蛋白质生成了具有正确折叠的结构模型,其中 28%的 RMSD 值低于 2Å。与其他最先进的方法相比,该方案的主要优势在于统一的结构预测和精修方案,以及广泛的结构重新组装模拟,允许从氨基酸序列开始,针对低至中分辨率的 EM 密度图进行结构建模。有趣的是,图像拟合和随后的结构精修的质量都与初始 I-TASSER 模型的正确性密切相关;这主要是由于在模板建模得分(或 TM 分数,用于衡量模型与天然结构的相似性的指标)高于和低于 0.5 阈值的模型中观察到的力场和结构质量之间的相关性模式不同。总体而言,结果表明了一种新的途径,可用于大规模的基于 cryo-EM 的结构建模和原子级密度图引导的结构精修。