A typical diffraction experiment will generate many images and data sets from different crystals in a very short time. This creates a challenge for the high-throughput operation of modern synchrotron beamlines as well as for the subsequent data processing. Novice users in particular may feel overwhelmed by the tables, plots and numbers that the different data-processing programs and software packages present to them. Here, some of the more common problems that a user has to deal with when processing a set of images that will finally make up a processed data set are shown, concentrating on difficulties that may often show up during the first steps along the path of turning the experiment (i.e. data collection) into a model (i.e. interpreted electron density). Difficulties such as unexpected crystal forms, issues in crystal handling and suboptimal choices of data-collection strategies can often be dealt with, or at least diagnosed, by analysing specific data characteristics during processing. In the end, one wants to distinguish problems over which one has no immediate control once the experiment is finished from problems that can be remedied a posteriori. A new software package, autoPROC, is also presented that combines third-party processing programs with new tools and an automated workflow script that is intended to provide users with both guidance and insight into the offline processing of data affected by the difficulties mentioned above, with particular emphasis on the automated treatment of multi-sweep data sets collected on multi-axis goniostats.

The methods for treating experimental data in the isomorphous replacement and anomalous scattering methods of macromolecular phase determination have undergone considerable evolution since their inception 50 years ago. The successive formulations used are reviewed, from the most simplistic viewpoint to the most advanced, including the exploration of some blind alleys. A new treatment is proposed and demonstrated for the improved encoding and subsequent exploitation of phase information in the complex plane. It is concluded that there is still considerable scope for further improvements in the statistical analysis of phase information, which touch upon numerous fundamental issues related to data processing and experimental design.

Local structural similarity restraints (LSSR) provide a novel method for exploiting NCS or structural similarity to an external target structure. Two examples are given where BUSTER re-refinement of PDB entries with LSSR produces marked improvements, enabling further structural features to be modelled.

Recently, there has been a resurgence in phasing using the single-wavelength anomalous diffraction (SAD) experiment -data from a single wavelength in combination with density modification techniques have been used to solve structures, even with a very small anomalous signal. Furthermore, SAD can be favorable to a multi-wavelength anomalous diffraction (MAD) experiment in a case where a crystal exhibits radiation decay during the course of a MAD experiment.Currently, to refine the anomalous substructure and phase a SAD data set, conventional techniques employ a least squares function either on the Bijvoet differences or the Bijvoet/Friedal pairs. These equations neglect some of the important correlations that occur in a SAD experiment. Indeed, since data from a SAD experiment comes from the same crystal and share the same model of anomalous scatterers, explicitly accounting for these correlations may improve results further. Here, a novel formulation for SAD phasing and refinement employing multivariate statistical techniques is presented. The equation developed accounts explicitly for the correlations from the observed and calculated Friedal mates in a SAD experiment. Furthermore, the function derived requires only a one dimensional numerical integration. The correlated SAD equation has been implemented and test cases performed on real diffraction data have revealed significantly better results than the currently most used programs in terms of correlation with the final map and producing more reliable phase probability statistics. We present the largest successful application of selenomethionine MAD reported to date: the crystal structure of the decameric E.coli enzyme ketopantoate hydroxymethyltransferase (KPHMT), with 160 ordered selenium atoms and 560 kDa of protein in the asymmetric unit. Despite small (<150 µ m), irregular, weakly diffracting (<3.2 Å) crystals, the substructure was solved by SAD combined with Direct Methods, using a 20-fold redundant "peak" dataset. SnB 1 produced the first correct solution after 2600 computing hours, and phases from SHARP 2 and Solomon 3 produced traceable maps, even before 20-fold NCS averaging. Subsequent analysis revealed that data redundancy was critical for success; on the other hand, speed and success rate vary considerably between direct methods programs. Apart from a favorable ratio of selenium to scattering matter, the procedure was quite general, suggesting that this is still a long way from the practical upper limit of applicability, if that exists. The current release (1.4.0) of SHARP [1] has been incorporated into a set of scripts called 'autoSHARP' which extend in both the upstream and downstream directions the initial coupling of SHARP to the SOLOMON density modification program. Upstream, autoSHARP can perform data checking and scaling, and heavy-atom detection; downstream, it can carry out density modification with automatic optimization of solvent flattening parameter and choice of hand, and launch the ARP/wARP map interpretation and model building proto...

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