Topf Maya, Baker Matthew L, Marti-Renom Marc A, Chiu Wah, Sali Andrej
Department of Biopharmaceutical Sciences, California Institute for Quantitative Biomedical Research, QB3, 1700 4th Street, Suite 503B, University of California at San Francisco, San Francisco, CA 94143-2552, USA.
J Mol Biol. 2006 Apr 14;357(5):1655-68. doi: 10.1016/j.jmb.2006.01.062. Epub 2006 Feb 2.
We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52% to 66%, which is half-way between the starting models and the models from the best possible alignments (82%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.
我们开发了一种通过迭代比较蛋白质结构建模并将其拟合到冷冻电子显微镜（cryoEM）密度图中来对组装组件进行结构表征的方法。具体而言，我们通过考虑目标序列与相关模板结构之间的多种比对方式，同时优化模型与相应密度图的拟合度，来计算给定组件的比较模型。该方法依赖于先前开发的Moulder协议，该协议在比对、模型构建和模型评估之间进行迭代。使用20对已知结构的不同目标-模板对（序列同一性小于30%）以及分辨率从5埃到25埃的相应模拟密度图对该协议进行了基准测试。相对于基于现有最佳序列轮廓比对方法的模型，在叠加的天然结构中，与相应Cα原子距离在5埃以内的Cα原子百分比平均从52%增加到66%，这处于起始模型和最佳可能比对模型（82%）之间的中间水平。测试还表明，尽管适应度函数的准确性有所提高，但该函数仍然是减少剩余误差的瓶颈。为了证明该协议的实用性，我们将其应用于水稻矮缩病毒P8衣壳蛋白的上结构域，该结构域已通过6.8埃分辨率的冷冻电子显微镜进行了研究。基于远缘相关模板蓝舌病毒VP7的模型的Cα均方根偏差从8.7埃提高到了6.0埃，而最佳可能模型的Cα均方根偏差值为5.3埃。此外，所得模型比初始模板结构更适合冷冻电子显微镜密度图。该方法正在我们用于通过满足空间约束进行蛋白质结构建模的程序MODELLER中实现，并将适用于数量迅速增加的大分子组装体的冷冻电子显微镜密度图。
