Improved joint X-ray and neutron refinement procedure in Phenix.

IF 2.6 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Dorothee Liebschner, Pavel V Afonine, Billy K Poon, Nigel W Moriarty, Paul D Adams
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Abstract

Neutron diffraction is one of the three crystallographic techniques (X-ray, neutron and electron diffraction) used to determine the atomic structures of molecules. Its particular strengths derive from the fact that H (and D) atoms are strong neutron scatterers, meaning that their positions, and thus protonation states, can be derived from crystallographic maps. However, because of technical limitations and experimental obstacles, the quality of neutron diffraction data is typically much poorer (completeness, resolution and signal to noise) than that of X-ray diffraction data for the same sample. Further, refinement is more complex as it usually requires additional parameters to describe the H (and D) atoms. The increase in the number of parameters may be mitigated by using the `riding hydrogen' refinement strategy, in which the positions of H atoms without a rotational degree of freedom are inferred from their neighboring heavy atoms. However, this does not address the issues related to poor data quality. Therefore, neutron structure determination often relies on the presence of an X-ray data set for joint X-ray and neutron (XN) refinement. In this approach, the X-ray data serve to compensate for the deficiencies of the neutron diffraction data by refining one model simultaneously against the X-ray and neutron data sets. To be applicable, it is assumed that both data sets are highly isomorphous, and preferably collected from the same crystals and at the same temperature. However, the approach has a number of limitations that are discussed in this work by comparing four separately re-refined neutron models. To address the limitations, a new method for joint XN refinement is introduced that optimizes two different models against the different data sets. This approach is tested using neutron models and data deposited in the Protein Data Bank. The efficacy of refining models with H atoms as riding or as individual atoms is also investigated.

改进了Phenix的X射线和中子联合细化程序。
中子衍射是用于确定分子原子结构的三种晶体学技术(X射线、中子和电子衍射)之一。它的特殊强度源于H(和D)原子是强中子散射体这一事实,这意味着它们的位置以及质子化状态可以从晶体学图中得出。然而,由于技术限制和实验障碍,中子衍射数据的质量通常比同一样品的X射线衍射数据差得多(完整性、分辨率和信噪比)。此外,细化更为复杂,因为它通常需要额外的参数来描述H(和D)原子。参数数量的增加可以通过使用“骑氢”细化策略来缓解,在该策略中,没有旋转自由度的H原子的位置是从它们相邻的重原子推断出来的。然而,这并不能解决与数据质量差有关的问题。因此,中子结构的确定通常依赖于X射线数据集的存在,用于联合X射线和中子(XN)细化。在这种方法中,X射线数据通过对X射线和中子数据集同时细化一个模型来弥补中子衍射数据的不足。为了适用,假设两个数据集都是高度同晶的,并且优选地从相同的晶体和在相同的温度下收集。然而,该方法有许多局限性,本工作通过比较四个单独重新精炼的中子模型来讨论这些局限性。为了解决这些限制,引入了一种新的联合XN精化方法,该方法针对不同的数据集优化两个不同的模型。该方法使用中子模型和蛋白质数据库中存储的数据进行了测试。还研究了以H原子为骑行原子或单个原子的精炼模型的有效性。
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来源期刊
Acta Crystallographica. Section D, Structural Biology
Acta Crystallographica. Section D, Structural Biology BIOCHEMICAL RESEARCH METHODSBIOCHEMISTRY &-BIOCHEMISTRY & MOLECULAR BIOLOGY
CiteScore
4.50
自引率
13.60%
发文量
216
期刊介绍: Acta Crystallographica Section D welcomes the submission of articles covering any aspect of structural biology, with a particular emphasis on the structures of biological macromolecules or the methods used to determine them. Reports on new structures of biological importance may address the smallest macromolecules to the largest complex molecular machines. These structures may have been determined using any structural biology technique including crystallography, NMR, cryoEM and/or other techniques. The key criterion is that such articles must present significant new insights into biological, chemical or medical sciences. The inclusion of complementary data that support the conclusions drawn from the structural studies (such as binding studies, mass spectrometry, enzyme assays, or analysis of mutants or other modified forms of biological macromolecule) is encouraged. Methods articles may include new approaches to any aspect of biological structure determination or structure analysis but will only be accepted where they focus on new methods that are demonstrated to be of general applicability and importance to structural biology. Articles describing particularly difficult problems in structural biology are also welcomed, if the analysis would provide useful insights to others facing similar problems.
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