Estimation of anomalous signal in diffraction data

Abstract

It is difficult to judge objectively the amount and resolution limit of the anomalous signal present in diffraction data. While several criteria can be used for this purpose, the usefulness of these indicators varies and depends on factors such as the data redundancy, the accuracy of the estimation of intensities and their uncertainties, and the properties of the anomalously scattering atoms in the crystal. Various indicators give an approximate measure of the anomalous signal, but do not provide a reliable guarantee that the crystal structure will be solved. The ultimate criterion of the anomalous signal is a successful structure solution. The current data‐acquisition and phasing methods are so advanced that it is often possible to phase reflections and obtain preliminary electron‐density maps in a few minutes, while the crystal still resides at the experimental station and further data can be collected if necessary.

A shape-shifting redox foldase contributes to Proteus mirabilis copper resistance

“…After several rounds of manual building in Coot40 and PHENIX38 refinements R/Rfree values dropped to 29.1 and 32.3%, but further refinement cycles were unsuccessful. Careful examination of Ctruncate41 indicated the presence of nearly perfect pseudo-merohedral twinning (-h,-k,l) and led to a reconsideration of space group. Reprocessing the data set to a resolution of 2.6 Å in space group P 2 1 yielded lower R-merge (0.072 versus 0.097 for data processed in P 2 1 2 1 2).…”

Bayesian machine learning improves single-wavelength anomalous diffraction phasing

“…Negative intensities have no place in diffraction theory; therefore, French and Wilson developed an ingenious Bayesian treatment for these reflections (French & Wilson, 1978). This method represents the first use of Bayesian statistics in physical sciences and it is still widely used in programs such as truncate (French & Wilson, 1978), ctruncate (Zwart, 2005;Dauter, 2006) and XDSCONV (Kabsch, 2010). French & Wilson's method was adapted to the interpretation of just a single set of observations (univariate model).…”

A prokaryotic perspective on pentameric ligand-gated ion channel structure

“…[146,147] or the Bijvoet ratio [142] ). Overall there is no reliable factor predicting the phasing power of an anomalous dataset and the final criterion for the quality of the anomalous signal is a successful structure solution [148] . The graph in figure 2.7 shows the resolution dependence in the ratio of the anomalous signal to the background of the selenium dataset.…”