Sawaya Michael R
UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, CA, USA.
Methods Mol Biol. 2014;1091:205-14. doi: 10.1007/978-1-62703-691-7_15.
Diffraction anisotropy is characterized by variation in diffraction quality with reciprocal lattice direction. In the example presented here, diffraction extended to 2.1 Å resolution along a* and c* directions but only to 3.0 Å along the b* direction. Severe anisotropy such as this is often associated with lack of detail in electron density maps, stalled model improvement, and poor refinement statistics. Published methods for overcoming these difficulties have been combined and implemented in the diffraction anisotropy server. Specifically, the server offers information to diagnose the degree of anisotropy, and then applies ellipsoidal resolution boundaries, anisotropic scaling, and B-factor sharpening to the data set to compensate for the deleterious effects of diffraction anisotropy. Here, I offer advice on implementing these methods to facilitate refinement of macromolecular structures in cases of severely anisotropic data.
衍射各向异性的特征是衍射质量随倒易晶格方向而变化。在本文给出的例子中,衍射在a和c方向上延伸至2.1 Å分辨率,但在b*方向上仅延伸至3.0 Å。如此严重的各向异性通常与电子密度图细节缺失、模型改进停滞以及精修统计不佳相关。已将已发表的克服这些困难的方法进行整合并在衍射各向异性服务器中实施。具体而言,该服务器提供用于诊断各向异性程度的信息,然后对数据集应用椭球分辨率边界、各向异性缩放和B因子锐化,以补偿衍射各向异性的有害影响。在此,我提供关于实施这些方法的建议,以便在数据严重各向异性的情况下促进大分子结构的精修。