Dou Hang, Burrows Derek W, Baker Matthew L, Ju Tao
Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri.
Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri.
Biophys J. 2017 Jun 20;112(12):2479-2493. doi: 10.1016/j.bpj.2017.04.054.
Although electron cryo-microscopy (cryo-EM) has recently achieved resolutions of better than 3 Å, at which point molecular modeling can be done directly from the density map, analysis and annotation of a cryo-EM density map still primarily rely on fitting atomic or homology models to the density map. In this article, we present, to our knowledge, a new method for flexible fitting of known or modeled protein structures into cryo-EM density maps. Unlike existing methods that are guided by local density gradients, our method is guided by correspondences between the α-helices in the density map and model, and does not require an initial rigid-body fitting step. Compared with current methods on both simulated and experimental density maps, our method not only achieves greater accuracy for proteins with large deformations but also runs as fast or faster than many of the other flexible fitting routines.
尽管电子冷冻显微镜(cryo-EM)最近已实现优于3埃的分辨率,达到此分辨率时可直接从密度图进行分子建模,但cryo-EM密度图的分析和注释仍主要依赖于将原子模型或同源模型拟合到密度图上。在本文中,据我们所知,我们提出了一种将已知或建模的蛋白质结构灵活拟合到cryo-EM密度图中的新方法。与现有方法以局部密度梯度为导向不同,我们的方法以密度图和模型中的α-螺旋之间的对应关系为导向,并且不需要初始刚体拟合步骤。与当前在模拟和实验密度图上的方法相比,我们的方法不仅对具有大变形的蛋白质具有更高的准确性,而且运行速度与许多其他灵活拟合程序一样快或更快。