要使用Patterson或直接方法从单波长异常衍射(SAD)数据确定子结构,首先估计子结构因子振幅(|Fa|)。目前,Bijvoet差的绝对值被广泛用作SAD数据的|Fa|值的估计。这里,从多元统计中得出一个方程,并进行了测试,该方程考虑了观察到的正(F)和负(F-)Friedel对与Fa之间的相关性以及观察到的数据中的测量误差。|Fa|的多变量估计已经在一个新的程序中实现,非洲裔。超过180个测试用例的结果表明,Afro提供了与最终子结构因子振幅的更高相关性(从改进的,最终子结构)比Bijvoet差异更大,并提高了直接方法子结构检测的鲁棒性。
To determine a substructure from single-wavelength anomalous diffraction (SAD) data using Patterson or direct methods, the substructure-factor amplitude (|Fa|) is first estimated. Currently, the absolute value of the Bijvoet difference is widely used as an estimate of |Fa| values for SAD data. Here, an equation is derived from multivariate statistics and tested that takes into account the correlation between the observed positive (F+) and negative (F-) Friedel pairs and Fa along with measurement errors in the observed data. The multivariate estimation of |Fa| has been implemented in a new program, Afro. Results on over 180 test cases show that Afro provides a higher correlation to the final substructure-factor amplitudes (calculated from the refined, final substructures) than the Bijvoet differences and improves the robustness of direct-methods substructure detection.