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晶体学 B 因子的可再现常态。

The reproducible normality of the crystallographic B-factor.

机构信息

National Institute for Metrology, Quality and Technology (INMETRO), INMETRO, Duque de Caxias, RJ, 25250-020, Brazil.

Pharmaceutical Biotechnology Laboratory (pbiotech), Faculty of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, 21941-902, Brazil.

出版信息

Anal Biochem. 2022 May 15;645:114594. doi: 10.1016/j.ab.2022.114594. Epub 2022 Feb 18.

Abstract

Reproducibility determines the utility of a measurement. In structural biology the reproducibility permeate areas such as mechanics, data measurement, data analysis and refinement. In order to access the reproducibility of the combined contribution of these sources in uncertainties of protein crystallography we evaluated four groups of parameters from data collection to final structural model. We used lysozyme as a model, with 20 datasets collected at 1.6 Å resolution using two dissimilar x-ray diffraction setups and refined through a single automatic pipeline without arbitrary interpretation. Besides statistical differences in some structural parameters, the reproducibility of the final refined models allowed the determination of positional uncertainty, in good agreement with the Luzzati coordinate error. While the raw B-factor was found non-reproducible, an empirical scaling/normalization resulted in reproducible B-factors. The validity of this empirical scaling was corroborated by the reproducibility of normalized B-factors of independently solved datasets from proteins (insulin and myoglobin) from varying space groups available from structural database. The reproducibility of normalized B-factor may reposition this displacement parameter in the analysis of chemical (ligands, pH) and physical (pressure, temperature, space groups) variables.

摘要

可重复性决定了测量的效用。在结构生物学中,可重复性渗透到力学、数据测量、数据分析和精修等领域。为了评估这些来源在蛋白质晶体学不确定度中综合贡献的可重复性,我们从数据收集到最终结构模型评估了四个参数组。我们使用溶菌酶作为模型,使用两种不同的 X 射线衍射装置在 1.6Å 分辨率下收集了 20 个数据集,并通过单一的自动流水线进行了精修,没有任意的解释。除了一些结构参数存在统计学差异外,最终精修模型的可重复性允许确定位置不确定性,与卢扎蒂坐标误差吻合良好。虽然原始 B 因子被发现不可重复,但经验性缩放/归一化导致了可重复的 B 因子。这种经验性缩放的有效性得到了来自结构数据库中不同空间群的独立解决数据集的归一化 B 因子的可重复性的证实。归一化 B 因子的可重复性可能会将这个位移参数重新定位到化学(配体、pH)和物理(压力、温度、空间群)变量的分析中。

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