Motivation: The assessment of protein structure prediction techniques requires objective criteria to measure the similarity between a computational model and the experimentally determined reference structure. Conventional similarity measures based on a global superposition of carbon α atoms are strongly influenced by domain motions and do not assess the accuracy of local atomic details in the model.Results: The Local Distance Difference Test (lDDT) is a superposition-free score that evaluates local distance differences of all atoms in a model, including validation of stereochemical plausibility. The reference can be a single structure, or an ensemble of equivalent structures. We demonstrate that lDDT is well suited to assess local model quality, even in the presence of domain movements, while maintaining good correlation with global measures. These properties make lDDT a robust tool for the automated assessment of structure prediction servers without manual intervention.Availability and implementation: Source code, binaries for Linux and MacOSX, and an interactive web server are available at http://swissmodel.expasy.org/lddtContact: torsten.schwede@unibas.chSupplementary information: Supplementary data are available at Bioinformatics online.

CrystFEL is a suite of programs for processing data from 'serial crystallography' experiments, which are usually performed using X-ray free-electron lasers (FELs) but also increasingly with other X-ray sources. The CrystFEL software suite has been under development since 2009, just before the first hard FEL experiments were performed, and has been significantly updated and improved since then. This article describes the most important improvements which have been made to CrystFEL since the first release version. These changes include the addition of new programs to the suite, the ability to resolve 'indexing ambiguities' and several ways to improve the quality of the integrated data by more accurately modelling the underlying diffraction physics.

The three-dimensional structures of macromolecules and their complexes are predominantly elucidated by X-ray protein crystallography. A major limitation is access to high-quality crystals, to ensure X-ray diffraction extends to sufficiently large scattering angles and hence yields sufficiently high-resolution information that the crystal structure can be solved. The observation that crystals with shrunken unit-cell volumes and tighter macromolecular packing often produce higher-resolution Bragg peaks1,2 hints that crystallographic resolution for some macromolecules may be limited not by their heterogeneity but rather by a deviation of strict positional ordering of the crystalline lattice. Such displacements of molecules from the ideal lattice give rise to a continuous diffraction pattern, equal to the incoherent sum of diffraction from rigid single molecular complexes aligned along several discrete crystallographic orientations and hence with an increased information content3. Although such continuous diffraction patterns have long been observed—and are of interest as a source of information about the dynamics of proteins4 —they have not been used for structure determination. Here we show for crystals of the integral membrane protein complex photosystem II that lattice disorder increases the information content and the resolution of the diffraction pattern well beyond the 4.5 Å limit of measurable Bragg peaks, which allows us to directly phase5 the pattern. With the molecular envelope conventionally determined at 4.5 Å as a constraint, we then obtain a static image of the photosystem II dimer at 3.5 Å resolution. This result shows that continuous diffraction can be used to overcome long-supposed resolution limits of macromolecular crystallography, with a method that puts great value in commonly encountered imperfect crystals and opens up the possibility for model-free phasing6,7.

In the Ninth Edition of the Critical Assessment of Techniques for Protein Structure Prediction (CASP9), 61,665 models submitted by 176 groups were assessed for their accuracy in the template based modeling category. The models were evaluated numerically in comparison to their experimental control structures using two global measures (GDT and GDC), and a novel local score evaluating the correct modeling of local interactions (lDDT). Overall, the state of the art of template based modeling in CASP9 is high, with many groups performing well. Among the methods registered as prediction "servers", six independent groups are performing on average better than the rest. The submissions by "human" groups are dominated by meta-predictors, with one group performing noticeably better than the others. Most of the participating groups failed to assign realistic confidence estimates to their predictions, and only a very small fraction of the assessed methods have provided highly accurate models and realistic error estimates at the same time. Also, the accuracy of predictions for homo-oligomeric assemblies was overall poor, and only one group performed better than a naïve control predictor. Here, we present the results of our assessment of the CASP9 predictions in the category of template based modeling, documenting the state of the art and highlighting areas for future developments.