Autoindexing the diffraction patterns from crystals with a pseudotranslation.

Autoindexing the diffraction patterns from crystals with a pseudotranslation.
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使用伪平移自动索引晶体的衍射图案。

DOI:
10.1107/s0907444909010725
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发表时间:
2009
期刊:
Acta crystallographica. Section D, Biological crystallography
影响因子:
--
通讯作者:
Zwart,PeterH
Zwart,PeterH
中科院分区:
--
文献类型:
--
作者:
Sauter,NicholasK;Zwart,PeterH

文献摘要

相似文献

旋转照片可以很容易地索引,如果有足够的候选布拉格点被识别,以适当地采样倒格。然而,虽然自动索引算法广泛用于大分子数据处理,但在系统地忽略布拉格点子集的特殊情况下,它们可能产生不正确的结果。这是一个潜在的结果,在情况下,一个非晶体平移对称算子密切模仿一个精确的晶体平移。在这些情况下,对衍射图像的目视检查将显示出强弱反射的交替。然而,通过软件可靠地检测弱强反射需要系统地搜索针对特定互向空间位置的衍射信号,通过考虑所有可能的伪平移来先验地计算。必须注意区分真正的晶格衍射和由相邻重叠的布拉格斑点、非布拉格衍射和噪声引起的杂散信号。这些程序已经在自动索引程序LABELIT中实现,并应用于来自公开可用数据集的已知病例。常规使用这种类型的信号搜索只会使自动索引的典型运行时间增加几秒钟。该程序可从https://cci.lbl.gov/labelit下载。
Rotation photographs can be readily indexed if enough candidate Bragg spots are identified to properly sample the reciprocal lattice. However, while automatic indexing algorithms are widely used for macromolecular data processing, they can produce incorrect results in special situations where a subset of Bragg spots is systematically overlooked. This is a potential outcome in cases where a noncrystallographic translational symmetry operator closely mimics an exact crystallographic translation. In these cases, a visual inspection of the diffraction image will reveal alternating strong and weak reflections. However, reliable detection of the weak-intensity reflections by software requires a systematic search for a diffraction signal targeted at specific reciprocal-space locations calculated a priori by considering all possible pseudotranslations. Care must be exercised to distinguish between true lattice diffraction and spurious signals contributed by neighboring overlapping Bragg spots, non-Bragg diffraction and noise. Such procedures have been implemented within the autoindexing program LABELIT and applied to known cases from publicly available data sets. Routine use of this type of signal search adds only a few seconds to the typical run time for autoindexing. The program can be downloaded from https://cci.lbl.gov/labelit.