The determination and refinement of heavy‐atom parameters in protein heavy‐atom derivatives. Some model calculations using acentric reflexions
The determination and refinement of heavy‐atom parameters in protein heavy‐atom derivatives. Some model calculations using acentric reflexions
复制标题
蛋白质重原子衍生物中重原子参数的确定和细化使用无心反射的一些模型计算。
DOI：
10.1107/s0567740871005946
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发表时间：
1971
期刊：
影响因子：
--
通讯作者：
M. Vijayan
中科院分区：
文献类型：
--
作者：
E. Dodson;M. Vijayan
本文借助于模型系统的计算，对用完全偏心数据确定和修正蛋白质衍生物中重原子参数的一些问题进行了严格的研究。发现即使在高取代度下，差分Patterson（Δ F2 Patterson）合成也能很好地近似重原子矢量图.给出了传统差分傅里叶合成系数的理论展开式。随着重原子取代量的增加，差分图的质量迅速下降。理论分析和模型计算表明，背景噪声与蛋白质傅立叶图的特征非常相似。X射线数据中的统计误差很可能会导致系统性高估的占有因子时，重原子参数的最小二乘法对重原子的贡献估计从类质同晶和异常的差异进行了改进。然而，可以通过在估计重原子贡献时使用经验估计的k值（重原子形状因子的真实的和虚部之间的比率）或通过对最小化函数中的项应用合适的加权函数来获得合理地精炼的占有因子，接近它们的真实值。本文还讨论了基于最小化缺闭合误差平方和的最小二乘法的某些方面。
Some problems associated with the determination and refinement of heavy-atom parameters in protein derivatives using totally acentric data are critically examined with the aid of calculations on model systems. The difference Patterson (ΔF 2 Patterson) synthesis is found to be a good approximation to the heavy-atom vector map even when the substitution is high. A theoretical expansion for the coefficients of the conventional difference Fourier synthesis is given. The quality of the difference map decreases rapidly with increasing heavy-atom substitution. Theoretical considerations and model calculations show that the background noise closely resembles the features of the protein Fourier map. Statistical errors in the X-ray data are likely to lead to a systamatic overestimation of the occupancy factors when the heavy-atom parameters are refined by the least-squares method against the heavy-atom contributions estimated from isomorphous and anomalous differences. Refined occupancy factors reasonably, close to their true values can, however, be obtained either by using empirically evaluated values of k (the ratio between the real and imaginary parts of the heavy-atom form factor) in estimating the heavy-atom contribution or by applying suitable weighting functions to the terms in the minimization function. Some aspects of the least-squares method based on tbe minimization of the sum of squares of the lack-of-closure errors are also discussed.