SAD phasing of XFEL data depends critically on the error model
SAD phasing of XFEL data depends critically on the error model
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DOI：
10.1107/s2059798319012877
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发表时间：
2019-11-01
影响因子：
2.2
通讯作者：
Sauter, Nicholas K.
中科院分区：
文献类型：
--
作者：
Brewster, Aaron S.;Bhowmick, Asmit;Sauter, Nicholas K.
提出了一种非线性最小二乘法，用于修正描述连续晶体学（SX）数据中反射强度估计误差的参数表达式。这种方法，这是在同步加速器的晶体学数据收集的旋转方法中使用的类似，传播误差估计从光子计数统计合并的数据。在这里，它表明，这种方法的应用SX数据提供了更好的SAD定相能力，使自动构建的蛋白质结构，以前未能建立。估计合并的反射强度中的误差需要理解和传播由测量引起的所有误差源。一种类型的误差是当探测器对X射线光子进行计数时引入的计数误差，这是很好理解的。因此，如果完全理解其他类型的随机误差（诸如读出噪声）以及系统校正中的不确定性（诸如来自X射线衰减），则它们可以在适当时沿着计数误差传播。在实践中，大多数软件包传播尽可能多的误差，因为他们知道如何建模，然后包括误差调整项，缩放误差估计，直到他们解释测量之间的方差。如果仔细执行，则在SAD定相期间，基于似然的方法可以最佳地利用这些误差估计，从而增加成功的结构解决方案的机会。在连续晶体学中，SAD定相仍然具有挑战性，其中一些从头蛋白质结构解决方案的例子每个都需要数千个衍射图案。在这里，估计不同的方法处理的误差估计的影响，它示出，使用参数的方法，包括与已知的实验不确定性，反射强度和平方反射强度，以提高误差估计成比例的条款，可以允许SAD相位，甚至从弱锌异常信号。
A nonlinear least-squares method for refining a parametric expression describing the estimated errors of reflection intensities in serial crystallographic (SX) data is presented. This approach, which is similar to that used in the rotation method of crystallographic data collection at synchrotrons, propagates error estimates from photon-counting statistics to the merged data. Here, it is demonstrated that the application of this approach to SX data provides better SAD phasing ability, enabling the autobuilding of a protein structure that had previously failed to be built. Estimating the error in the merged reflection intensities requires the understanding and propagation of all of the sources of error arising from the measurements. One type of error, which is well understood, is the counting error introduced when the detector counts X-ray photons. Thus, if other types of random errors (such as readout noise) as well as uncertainties in systematic corrections (such as from X-ray attenuation) are completely understood, they can be propagated along with the counting error, as appropriate. In practice, most software packages propagate as much error as they know how to model and then include error-adjustment terms that scale the error estimates until they explain the variance among the measurements. If this is performed carefully, then during SAD phasing likelihood-based approaches can make optimal use of these error estimates, increasing the chance of a successful structure solution. In serial crystallography, SAD phasing has remained challenging, with the few examples of de novo protein structure solution each requiring many thousands of diffraction patterns. Here, the effects of different methods of treating the error estimates are estimated and it is shown that using a parametric approach that includes terms proportional to the known experimental uncertainty, the reflection intensity and the squared reflection intensity to improve the error estimates can allow SAD phasing even from weak zinc anomalous signal.