One often observes small but measurable differences in diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and potentially reflect the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step to extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data are measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here we address this problem using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformation space. We illustrate this method using two independent observables – unit cell constants and intensities – to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. We observe that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin.

The XtaLAB Synergy Flow turns any Synergy cabinet diffractometer into an automated, high-throughput machine by incorporating a 6-axis UR3 Universal Robot and a 3-puck dewar. The Flow system can automatically screen and collect 48 crystal samples with minimal human intervention. CrysAlisPro has been upgraded with tools to control all aspects of robotics and sample queuing. A unique X-ray safe dewar-drawer system allows loading and unloading of pucks without opening the X-ray enclosure or disturbing data collection. Ultimately, the XtaLAB Synergy Flow system is the perfect solution to allow full-time use of your diffractometer during a time when human interaction and contamination must be minimized.

For half a century the refinement of atomic model parameters to best explain the observed diffraction pattern has been fundamental to the process of crystallographic structure solution. This process has traditionally been carried out by the optimization of individual atomic parameters, with the use of stereochemical restraints to maintain plausible model geometry, particularly when data resolution is poor. However the data are often too poor to reliably indicate how individual atoms should be moved, and as a result the refinement calculation becomes a protracted battle between the noisy data pulling atoms in different directions and the restraints which are trying to maintain model geometry. This limits both the speed and radius of convergence of the calculation.

Shift field refinement is a new approach in which shifts to the calculated electron density are determined over extended regions of the unit cell, where the region size may be varied according to the resolution of the data and the type of feature (from whole domain to individual atom) being refined. The enables refinement to capture large domain shifts at low resolution, and to be applied at any resolution with rapid convergence. We have already demonstrated improved molecular replacement results when incorporating this step. We now demonstrate how the method can be used to refine a map against a set of diffraction observations, even in the absence of an atomic model.

We also demonstrate how the incorporation of a separate regularization step can be used to improve the refinement results by allowing more cycles of refinement to be run without the risk of model degradation due to accumulated model distortions. This in turn leads to further improvements in the refinement results.

High-end x-ray diffraction techniques such as macromolecular crystallography rely heavily on the x-ray source brightness for resolution and exposure time. As boundaries of technology are pushed forward samples are becoming smaller, weaker diffracting and less stable which put additional requirements on ever brighter sources. With bright enough compact sources, even the toughest challenges can be solved in the home laboratory. Traditional solid or rotating anode x-ray tubes are typically limited in brightness by when the e-beam power density melts the anode. The liquid-metal-jet technology (MetalJet) has overcome this limitation by using an anode that is already in the molten state thus e-beam power loading above several megawatts per mm are now feasible.

Over a decade ago the first prototypes of liquid-metal-jet x-ray sources were demonstrated. These immediately demonstrated unprecedented brightness in the range of one order of magnitude above current state-of-the art sources. Over the last years, the liquid-metal-jet technology has developed from prototypes into fully operational and stable X-ray tubes running in more than 100 labs over the world. X-ray crystallography is naturally considered a key application for the x-ray tube technology, since this application benefits greatly from small spot-sizes, high-brightness in combination with a need for stable output. To achieve a single-crystal-diffraction (SCD) platform addressing the needs of the most demanding crystallographers, multiple users and system manufacturers has since installed the MetalJet x-ray source into their SCD set-ups with successful results.

This contribution reviews the evolvement of the MetalJet technology specifically in terms of flux and brightness and its applicability for pushing boundaries of what is possible in the home lab. Recent user examples will illustrate how the MetalJet has enabled faster turnaround time of research and also enabled easy and convenient 24/7 access to the highest quality of crystallography data.

Carbohydrates are central to many biological processes. As protein glycosylation, they mediate interactions in recognition processes in cancer, viral infection, fertilisation. For example, the surfaces of viruses and antibodies are often covered in carbohydrates, which has been exploited in the development of vaccines and therapies. To further such efforts, it is important to have a good understanding of their 3D structure.

A software, Sails (Software for Automated Identification of Linked Sugars), has been developed to build sugars into electron density/potential maps automatically. It currently works for N-glycosylation and ligands, with plans to expand it for O-glycosylation. Sails uses a database of sugar fingerprints. These fingerprints are generated by superposing sugars from high-resolution structures in the PDB in their minimal-energy conformation, with correct anomeric forms and stereochemistry. The resulting fingerprints contain a set of coordinates of the atoms, plus a set of peaks and voids. Peaks represent map places where the electron density/potential of the fingerprint is expected to be high, while voids are places where map density values are likely to be close to zero. Figure 1 represents examples of sugars detected with Sails. As part of this presentation, I will discuss the fingerprinting method, its application to sugars and real world results from using Sails on published datasets.

Deep UV laser ablation is a technique to improve diffraction data quality from cryocooled macromolecular crystals by removing non-crystalline portion of the sample in the cryoloop or fabricating the crystal into symmetrical shape such as sphere [1]. It has been shown particularly effective for native single-wavelength anomalous dispersion (SAD) phasing in macromolecular crystallography (MX), where very accurate data is required to detect week anomalous signals from light atoms [2]. The systematic errors due to the beam absorption by the sample itself are reduced which is problematic in performing diffraction experiment using long wavelength X-ray. The application is straightforward, however, time consuming with human intervention, and even difficult in case the crystal is hard to identify by visual inspection, such as membrane protein crystals in lipidic cubic phase.

We are developing an unattended system to shape large number of samples based on the 3D map constructed by visual images or by X-ray raster images. In the case of using X-ray raster images, the map is automatically created from the raster images collected at several orientations at a synchrotron MX beamline in a standard, unattended manner. The map is then transferred to the laser shaping machine, allowing to visualize the envelope of the crystal on the mounted, ready-to-shape sample. By specifying the type of processing, e.g., ‘removing non-crystalline region’ or ‘fabricating into inscribed sphere’, the system automatically defines the orbit of the laser and repeats processing until the sample converges to the target shape. It is quite useful in preparing large number of shaped samples, typically in native SAD phasing experiment where high-redundant diffraction data is required.

XALOC is a tunable MX beamline, in user operation since 2012, located at the 3^rd generation synchrotron ALBA (Barcelona). XALOC has been designed to deal with automatable X-ray diffraction experiments of micrometer-sized crystals, including a variety of crystal sizes, unit-cell dimensions and crystals with high mosaic spread and/or poor diffraction. The aim for a reliable all-in-one beamline is equaled by the aim to maximize ease-of-use and automatization. Mail-in data collection is now in routine operation and dewar transport expenses are covered for users from Spain and abroad. To achieve a high-throughput MX beamline, we have implemented a new double gripper at the CATS sample changer that allows sample interchange in less than 20 seconds. Besides, an improvement in the CATS dewar allows to allocate up to 6 Unipucks (96 samples). EMBL/ESRF pucks are also acceptable with a capacity of 30 samples. In addition, MXCube and ISPyB software platforms for data collection and sample tracking/experiment reporting are routinely used at the beamline, allowing automated centering and the possibility to download the results obtained with the EDNA automated data processing pipeline through a web browser (https://ispyb.cells.es/). The beamline allows “in-situ” diffraction and serial crystallography experiments have been carried out successfully. XALOC is continuously open to new proposals providing beamtime within a few weeks. The latest updates and efforts and future developments on automation will be presented