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首页> 外文期刊>Acta crystallographica.Section D. Biological crystallography >On the use of logarithmic scales for analysis of diffraction data
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On the use of logarithmic scales for analysis of diffraction data

机译：使用对数尺度的分析衍射数据

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Predictions of the possible model parameterization and of the values of model characteristics such as R factors are important for macromolecular refinement and validation protocols. One of the key parameters defining these and other values is the resolution of the experimentally measured diffraction data. The higher the resolution, the larger the number of diffraction data Nref, the larger its ratio to the number Nat of non-H atoms, the more parameters per atom can be used for modelling and the more precise and detailed a model can be obtained. The ratio Nref/N at was calculated for models deposited in the Protein Data Bank as a function of the resolution at which the structures were reported. The most frequent values for this distribution depend essentially linearly on resolution when the latter is expressed on a uniform logarithmic scale. This defines simple analytic formulae for the typical Matthews coefficient and for the typically allowed number of parameters per atom for crystals diffracting to a given resolution. This simple dependence makes it possible in many cases to estimate the expected resolution of the experimental data for a crystal with a given Matthews coefficient. When expressed using the same logarithmic scale, the most frequent values for R and Rfree factors and for their difference are also essentially linear across a large resolution range. The minimal R-factor values are practically constant at resolutions better than 3 ?, below which they begin to grow sharply. This simple dependence on the resolution allows the prediction of expected R-factor values for unknown structures and may be used to guide model refinement and validation.
机译：预测可能的参数化模型和的值模型的特征作为大分子R因素是很重要的细化和验证协议。关键参数定义这些和其他值实验测量的分辨率衍射数据。大Nref衍射数据的数量更大的Nat non-H的数量的比率原子,每个原子可以使用多个参数造型和更精确和详细的一个模型可以获得。蛋白质沉积模型的计算数据银行作为解析的函数报告的结构。这个分布取决于频率值本质上是线性时解决后者表示在一个统一的对数规模。典型的马修斯系数和通常允许每个原子的参数数量晶体衍射给定的决议。这个简单的依赖可以在许多情况下估计预期的解决实验数据与给定晶体马修斯系数。相同的对数刻度,最常见的值R和Rfree因素和他们的区别也基本上是线性跨大吗决议范围内。几乎恒定的分辨率比3?,下面开始大幅增长。该决议允许简单的依赖预测预期的r因子值未知的结构,可用于指导模型优化和验证。

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