Advanced exploitation of unmerged reflection data during processing and refinement with autoPROC and BUSTER.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2024-03-01 Epub Date: 2024-02-27 DOI:10.1107/S2059798324001487
Clemens Vonrhein, Claus Flensburg, Peter Keller, Rasmus Fogh, Andrew Sharff, Ian J Tickle, Gérard Bricogne
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Abstract

The validation of structural models obtained by macromolecular X-ray crystallography against experimental diffraction data, whether before deposition into the PDB or after, is typically carried out exclusively against the merged data that are eventually archived along with the atomic coordinates. It is shown here that the availability of unmerged reflection data enables valuable additional analyses to be performed that yield improvements in the final models, and tools are presented to implement them, together with examples of the results to which they give access. The first example is the automatic identification and removal of image ranges affected by loss of crystal centering or by excessive decay of the diffraction pattern as a result of radiation damage. The second example is the `reflection-auditing' process, whereby individual merged data items showing especially poor agreement with model predictions during refinement are investigated thanks to the specific metadata (such as image number and detector position) that are available for the corresponding unmerged data, potentially revealing previously undiagnosed instrumental, experimental or processing problems. The third example is the calculation of so-called F(early) - F(late) maps from carefully selected subsets of unmerged amplitude data, which can not only highlight the location and extent of radiation damage but can also provide guidance towards suitable fine-grained parametrizations to model the localized effects of such damage.

Abstract Image

利用 autoPROC 和 BUSTER,在处理和细化过程中对未合并的反射数据进行高级开发。
通过大分子 X 射线晶体学获得的结构模型,无论是在存入 PDB 之前还是之后,通常都是根据最终与原子坐标一起存档的合并数据,对照实验衍射数据进行验证的。本文显示,未合并反射数据的可用性使我们能够进行有价值的附加分析,从而改进最终模型,本文还介绍了实现这些分析的工具,并举例说明了这些工具所能获得的结果。第一个例子是自动识别和移除因晶体失中或因辐射损伤导致衍射图样过度衰减而受影响的图像范围。第二个例子是 "反射-审计 "过程,在此过程中,由于相应的未合并数据具有特定的元数据(如图像编号和探测器位置),因此可以对在细化过程中显示与模型预测特别不一致的个别合并数据项进行调查,从而有可能揭示之前未诊断出的仪器、实验或处理问题。第三个例子是通过精心挑选的未合并振幅数据子集计算所谓的 F(早期)-F(晚期)图,这不仅可以突出辐射损伤的位置和程度,还可以为适当的细粒度参数建模提供指导,以模拟此类损伤的局部效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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