Kirmizialtin Serdal, Loerke Justus, Behrmann Elmar, Spahn Christian M T, Sanbonmatsu Karissa Y
Department of Chemistry, New York University, Abu Dhabi, United Arab Emirates; New Mexico Consortium, Los Alamos, New Mexico, USA; Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.
Institut für Medizinische Physik und Biophysik, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Methods Enzymol. 2015;558:497-514. doi: 10.1016/bs.mie.2015.02.011. Epub 2015 May 9.
An explosion of new data from high-resolution cryo-electron microscopy (cryo-EM) studies has produced a large number of data sets for many species of ribosomes in various functional states over the past few years. While many methods exist to produce structural models for lower resolution cryo-EM reconstructions, high-resolution reconstructions are often modeled using crystallographic techniques and extensive manual intervention. Here, we present an automated fitting technique for high-resolution cryo-EM data sets that produces all-atom models highly consistent with the EM density. Using a molecular dynamics approach, atomic positions are optimized with a potential that includes the cross-correlation coefficient between the structural model and the cryo-EM electron density, as well as a biasing potential preserving the stereochemistry and secondary structure of the biomolecule. Specifically, we use a hybrid structure-based/ab initio molecular dynamics potential to extend molecular dynamics fitting. In addition, we find that simulated annealing integration, as opposed to straightforward molecular dynamics integration, significantly improves performance. We obtain atomistic models of the human ribosome consistent with high-resolution cryo-EM reconstructions of the human ribosome. Automated methods such as these have the potential to produce atomistic models for a large number of ribosome complexes simultaneously that can be subsequently refined manually.
在过去几年中,高分辨率冷冻电子显微镜(cryo-EM)研究产生的大量新数据为处于各种功能状态的多种核糖体物种提供了众多数据集。虽然存在许多方法可用于为低分辨率冷冻电镜重建生成结构模型,但高分辨率重建通常使用晶体学技术并进行大量人工干预来建模。在此,我们提出了一种针对高分辨率冷冻电镜数据集的自动拟合技术,该技术可生成与电子密度高度一致的全原子模型。使用分子动力学方法,通过一种势能来优化原子位置,该势能包括结构模型与冷冻电镜电子密度之间的互相关系数,以及一个保持生物分子立体化学和二级结构的偏向势能。具体而言,我们使用基于结构的混合/从头算分子动力学势能来扩展分子动力学拟合。此外,我们发现与直接的分子动力学积分相比,模拟退火积分显著提高了性能。我们获得了与人类核糖体的高分辨率冷冻电镜重建一致的人类核糖体原子模型。诸如此类的自动化方法有潜力同时为大量核糖体复合物生成原子模型,随后可进行人工细化。