Institute of Complex Systems, Structural Biochemistry (ICS-6), Forschungszentrum Jülich, 52425 Jülich, Germany; Physics Department, Heinrich-Heine Universität Düsseldorf, 40225 Düsseldorf, Germany.
Curr Opin Struct Biol. 2015 Apr;31:20-7. doi: 10.1016/j.sbi.2015.02.016. Epub 2015 Mar 18.
Studies of large and heterogeneous macromolecules often yield low-resolution data that alone does not suffice to build accurate atomic models. Adding information from molecular simulation or other structure prediction methods can lead to models with significantly better quality. Different strategies are discussed to combine experimental data with results from simulation and prediction. This review describes recent approaches for building atomic models with a focus on X-ray diffraction and single-particle cryo-electron microscopy (cryo-EM) data. In addition, both cryo-EM and X-ray diffraction provide information on molecular dynamics. Therefore, the best description of molecular structures is often by an ensemble of models. It furthermore becomes apparent that using raw data for the modeling ensures that all information obtained by the experiment can be fully exploited. It is also important to quantify the errors of both experiment and simulation to correctly weigh their different contributions.
对大型和异质大分子的研究通常会产生低分辨率的数据，这些数据本身不足以构建准确的原子模型。添加来自分子模拟或其他结构预测方法的信息可以得到质量显著提高的模型。本文讨论了不同的策略，以将实验数据与模拟和预测结果相结合。本综述描述了使用 X 射线衍射和单颗粒低温电子显微镜（cryo-EM）数据构建原子模型的最新方法。此外，cryo-EM 和 X 射线衍射都提供了关于分子动力学的信息。因此，对分子结构的最佳描述通常是通过一组模型来实现。此外，使用原始数据进行建模可以确保充分利用实验获得的所有信息。量化实验和模拟的误差也很重要，以正确衡量它们的不同贡献。
