Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers.

X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

Energy-dispersive X-ray emission spectroscopy using an X-ray free-electron laser in a shot-by-shot mode.

The ultrabright femtosecond X-ray pulses provided by X-ray free-electron lasers open capabilities for studying the structure and dynamics of a wide variety of systems beyond what is possible with synchrotron sources. Recently, this "probe-before-destroy" approach has been demonstrated for atomic structure determination by serial X-ray diffraction of microcrystals. There has been the question whether a similar approach can be extended to probe the local electronic structure by X-ray spectroscopy. To address this, we have carried out femtosecond X-ray emission spectroscopy (XES) at the Linac Coherent Light Source using redox-active Mn complexes. XES probes the charge and spin states as well as the ligand environment, critical for understanding the functional role of redox-active metal sites. Kß(1,3) XES spectra of Mn(II) and Mn(2)(III,IV) complexes at room temperature were collected using a wavelength dispersive spectrometer and femtosecond X-ray pulses with an individual dose of up to >100 MGy. The spectra were found in agreement with undamaged spectra collected at low dose using synchrotron radiation. Our results demonstrate that the intact electronic structure of redox active transition metal compounds in different oxidation states can be characterized with this shot-by-shot method. This opens the door for studying the chemical dynamics of metal catalytic sites by following reactions under functional conditions. The technique can be combined with X-ray diffraction to simultaneously obtain the geometric structure of the overall protein and the local chemistry of active metal sites and is expected to prove valuable for understanding the mechanism of important metalloproteins, such as photosystem II.

Room temperature femtosecond X-ray diffraction of photosystem II microcrystals.

Most of the dioxygen on earth is generated by the oxidation of water by photosystem II (PS II) using light from the sun. This light-driven, four-photon reaction is catalyzed by the Mn(4)CaO(5) cluster located at the lumenal side of PS II. Various X-ray studies have been carried out at cryogenic temperatures to understand the intermediate steps involved in the water oxidation mechanism. However, the necessity for collecting data at room temperature, especially for studying the transient steps during the O-O bond formation, requires the development of new methodologies. In this paper we report room temperature X-ray diffraction data of PS II microcrystals obtained using ultrashort (< 50 fs) 9 keV X-ray pulses from a hard X-ray free electron laser, namely the Linac Coherent Light Source. The results presented here demonstrate that the "probe before destroy" approach using an X-ray free electron laser works even for the highly-sensitive Mn(4)CaO(5) cluster in PS II at room temperature. We show that these data are comparable to those obtained in synchrotron radiation studies as seen by the similarities in the overall structure of the helices, the protein subunits and the location of the various cofactors. This work is, therefore, an important step toward future studies for resolving the structure of the Mn(4)CaO(5) cluster without any damage at room temperature, and of the reaction intermediates of PS II during O-O bond formation.

Flexible torsion-angle noncrystallographic symmetry restraints for improved macromolecular structure refinement.

One of the great challenges in refining macromolecular crystal structures is a low data-to-parameter ratio. Historically, knowledge from chemistry has been used to help to improve this ratio. When a macromolecule crystallizes with more than one copy in the asymmetric unit, the noncrystallographic symmetry relationships can be exploited to provide additional restraints when refining the working model. However, although globally similar, NCS-related chains often have local differences. To allow for local differences between NCS-related molecules, flexible torsion-based NCS restraints have been introduced, coupled with intelligent rotamer handling for protein chains, and are available in phenix.refine for refinement of models at all resolutions.

New methods for indexing multi-lattice diffraction data.

A new indexing method is presented which is capable of indexing multiple crystal lattices from narrow wedges of diffraction data. The method takes advantage of a simplification of Fourier transform-based methods that is applicable when the unit-cell dimensions are known a priori. The efficacy of this method is demonstrated with both semi-synthetic multi-lattice data and real multi-lattice data recorded from crystals of ∼1 µm in size, where it is shown that up to six lattices can be successfully indexed and subsequently integrated from a 1° wedge of data. Analysis is presented which shows that improvements in data-quality indicators can be obtained through accurate identification and rejection of overlapping reflections prior to scaling.

Atomic structure of a nudivirus occlusion body protein determined from a 70-year-old crystal sample.

Infectious protein crystals are an essential part of the viral lifecycle for double-stranded DNA Baculoviridae and double-stranded RNA cypoviruses. These viral protein crystals, termed occlusion bodies or polyhedra, are dense protein assemblies that form a crystalline array, encasing newly formed virions. Here, using X-ray crystallography we determine the structure of a polyhedrin from Nudiviridae. This double-stranded DNA virus family is a sister-group to the baculoviruses, whose members were thought to lack occlusion bodies. The 70-year-old sample contains a well-ordered lattice formed by a predominantly α-helical building block that assembles into a dense, highly interconnected protein crystal. The lattice is maintained by extensive hydrophobic and electrostatic interactions, disulfide bonds, and domain switching. The resulting lattice is resistant to most environmental stresses. Comparison of this structure to baculovirus or cypovirus polyhedra shows a distinct protein structure, crystal space group, and unit cell dimensions, however, all polyhedra utilise common principles of occlusion body assembly.

Protein-to-structure pipeline for ambient-temperature in situ crystallography at VMXi.

The utility of X-ray crystal structures determined under ambient-temperature conditions is becoming increasingly recognized. Such experiments can allow protein dynamics to be characterized and are particularly well suited to challenging protein targets that may form fragile crystals that are difficult to cryo-cool. Room-temperature data collection also enables time-resolved experiments. In contrast to the high-throughput highly automated pipelines for determination of structures at cryogenic temperatures widely available at synchrotron beamlines, room-temperature methodology is less mature. Here, the current status of the fully automated ambient-temperature beamline VMXi at Diamond Light Source is described, and a highly efficient pipeline from protein sample to final multi-crystal data analysis and structure determination is shown. The capability of the pipeline is illustrated using a range of user case studies representing different challenges, and from high and lower symmetry space groups and varied crystal sizes. It is also demonstrated that very rapid structure determination from crystals in situ within crystallization plates is now routine with minimal user intervention.

The CCP4 suite: integrative software for macromolecular crystallography.

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Nanoflow electrospinning serial femtosecond crystallography.

An electrospun liquid microjet has been developed that delivers protein microcrystal suspensions at flow rates of 0.14-3.1 µl min(-1) to perform serial femtosecond crystallography (SFX) studies with X-ray lasers. Thermolysin microcrystals flowed at 0.17 µl min(-1) and diffracted to beyond 4 Å resolution, producing 14,000 indexable diffraction patterns, or four per second, from 140 µg of protein. Nanoflow electrospinning extends SFX to biological samples that necessitate minimal sample consumption.

Luminescent iridium(III) complexes with N

A family of complexes (1a-3a and 1b-3b) was prepared, having the structure Ir(N^C^N)(N^C)Cl. Here, N^C(∧)N represents a terdentate, cyclometallating ligand derived from 1,3-di(2-pyridyl)benzene incorporating CH(3) (1a,b), F (2a,b), or CF(3) (3a,b) substituents at the 4 and 6 positions of the benzene ring, and N^C is 2-phenylpyridine (series a) or 2-(2,4-difluorophenyl)pyridine (series b). The complexes are formed using a stepwise procedure that relies on the initial introduction of the terdentate ligand to form a dichloro-bridged iridium dimer, followed by cleavage with the N^C ligand. (1)H NMR spectroscopy reveals that the isomer that is exclusively formed in each case is that in which the pyridyl ring of the N^C ligand is trans to the cyclometallating aryl ring of the N^C^N ligand. This conclusion is unequivocally confirmed by X-ray diffraction analysis for two of the complexes (1b and 3a). All of the complexes are highly luminescent in degassed solution at room temperature, emitting in the green (1a,b), blue-green (2a,b), and orange-red (3a,b) regions. The bidentate ligand offers independent fine-tuning of the emission energy: for each pair, the "b" complex is blue-shifted relative to the analogous "a" complex. These trends in the excited-state energies are rationalized in terms of the relative magnitudes of the effects of the substituents on the highest occupied and lowest unoccupied orbitals, convincingly supported by time-dependent density functional theory (TD-DFT) calculations. Luminescence quantum yields are high, up to 0.7 in solution and close to unity in a PMMA matrix for the green-emitting complexes. Organic light emitting devices (OLEDs) employing this family of complexes as phosphorescent emitters have been prepared. They display high efficiencies, at least comparable, and in some cases superior, to similar devices using the well-known tris-bidentate complexes such as fac-Ir(ppy)(3). The combination of terdentate and bidentate ligands is seen to offer a versatile approach to tuning of the photophysical properties of iridium-based emitters for such applications.

xia2.multiplex: a multi-crystal data-analysis pipeline.

In macromolecular crystallography, radiation damage limits the amount of data that can be collected from a single crystal. It is often necessary to merge data sets from multiple crystals; for example, small-wedge data collections from micro-crystals, in situ room-temperature data collections and data collection from membrane proteins in lipidic mesophases. Whilst the indexing and integration of individual data sets may be relatively straightforward with existing software, merging multiple data sets from small wedges presents new challenges. The identification of a consensus symmetry can be problematic, particularly in the presence of a potential indexing ambiguity. Furthermore, the presence of non-isomorphous or poor-quality data sets may reduce the overall quality of the final merged data set. To facilitate and help to optimize the scaling and merging of multiple data sets, a new program, xia2.multiplex, has been developed which takes data sets individually integrated with DIALS and performs symmetry analysis, scaling and merging of multi-crystal data sets. xia2.multiplex also performs analysis of various pathologies that typically affect multi-crystal data sets, including non-isomorphism, radiation damage and preferential orientation. After the description of a number of use cases, the benefit of xia2.multiplex is demonstrated within a wider autoprocessing framework in facilitating a multi-crystal experiment collected as part of in situ room-temperature fragment-screening experiments on the SARS-CoV-2 main protease.

DIALS as a toolkit.

The DIALS software for the processing of X-ray diffraction data is presented, with an emphasis on how the suite may be used as a toolkit for data processing. The description starts with an overview of the history and intent of the toolkit, usage as an automated system, command-line use, and ultimately how new tools can be written using the API to perform bespoke analysis. Consideration is also made to the application of DIALS to techniques outside of macromolecular X-ray crystallography.

Scaling diffraction data in the DIALS software package: algorithms and new approaches for multi-crystal scaling.

In processing X-ray diffraction data, the intensities obtained from integration of the diffraction images must be corrected for experimental effects in order to place all intensities on a common scale both within and between data collections. Scaling corrects for effects such as changes in sample illumination, absorption and, to some extent, global radiation damage that cause the measured intensities of symmetry-equivalent observations to differ throughout a data set. This necessarily requires a prior evaluation of the point-group symmetry of the crystal. This paper describes and evaluates the scaling algorithms implemented within the DIALS data-processing package and demonstrates the effectiveness and key features of the implementation on example macromolecular crystallographic rotation data. In particular, the scaling algorithms enable new workflows for the scaling of multi-crystal or multi-sweep data sets, providing the analysis required to support current trends towards collecting data from ever-smaller samples. In addition, the implementation of a free-set validation method is discussed, which allows the quantification of the suitability of scaling-model and algorithm choices.

How best to use photons.

Strategies for collecting X-ray diffraction data have evolved alongside beamline hardware and detector developments. The traditional approaches for diffraction data collection have emphasised collecting data from noisy integrating detectors (i.e. film, image plates and CCD detectors). With fast pixel array detectors on stable beamlines, the limiting factor becomes the sample lifetime, and the question becomes one of how to expend the photons that your sample can diffract, i.e. as a smaller number of stronger measurements or a larger number of weaker data. This parameter space is explored via experiment and synthetic data treatment and advice is derived on how best to use the equipment on a modern beamline. Suggestions are also made on how to acquire data in a conservative manner if very little is known about the sample lifetime.

Determination of Patterson group symmetry from sparse multi-crystal data sets in the presence of an indexing ambiguity.

Combining X-ray diffraction data from multiple samples requires determination of the symmetry and resolution of any indexing ambiguity. For the partial data sets typical of in situ room-temperature experiments, determination of the correct symmetry is often not straightforward. The potential for indexing ambiguity in polar space groups is also an issue, although methods to resolve this are available if the true symmetry is known. Here, a method is presented to simultaneously resolve the determination of the Patterson symmetry and the indexing ambiguity for partial data sets.

Improving signal strength in serial crystallography with DIALS geometry refinement.

The DIALS diffraction-modeling software package has been applied to serial crystallography data. Diffraction modeling is an exercise in determining the experimental parameters, such as incident beam wavelength, crystal unit cell and orientation, and detector geometry, that are most consistent with the observed positions of Bragg spots. These parameters can be refined by nonlinear least-squares fitting. In previous work, it has been challenging to refine both the positions of the sensors (metrology) on multipanel imaging detectors such as the CSPAD and the orientations of all of the crystals studied. Since the optimal models for metrology and crystal orientation are interdependent, alternate cycles of panel refinement and crystal refinement have been required. To simplify the process, a sparse linear algebra technique for solving the normal equations was implemented, allowing the detector panels to be refined simultaneously against the diffraction from thousands of crystals with excellent computational performance. Separately, it is shown how to refine the metrology of a second CSPAD detector, positioned at a distance of 2.5 m from the crystal, used for recording low-angle reflections. With the ability to jointly refine the detector position against the ensemble of all crystals used for structure determination, it is shown that ensemble refinement greatly reduces the apparent nonisomorphism that is often observed in the unit-cell distributions from still-shot serial crystallography. In addition, it is shown that batching the images by timestamp and re-refining the detector position can realistically model small, time-dependent variations in detector position relative to the sample, and thereby improve the integrated structure-factor intensity signal and heavy-atom anomalous peak heights.

DIALS: implementation and evaluation of a new integration package.

The DIALS project is a collaboration between Diamond Light Source, Lawrence Berkeley National Laboratory and CCP4 to develop a new software suite for the analysis of crystallographic X-ray diffraction data, initially encompassing spot finding, indexing, refinement and integration. The design, core algorithms and structure of the software are introduced, alongside results from the analysis of data from biological and chemical crystallography experiments.

Background modelling of diffraction data in the presence of ice rings.

An algorithm for modelling the background for each Bragg reflection in a series of X-ray diffraction images containing Debye-Scherrer diffraction from ice in the sample is presented. The method involves the use of a global background model which is generated from the complete X-ray diffraction data set. Fitting of this model to the background pixels is then performed for each reflection independently. The algorithm uses a static background model that does not vary over the course of the scan. The greatest improvement can be expected for data where ice rings are present throughout the data set and the local background shape at the size of a spot on the detector does not exhibit large time-dependent variation. However, the algorithm has been applied to data sets whose background showed large pixel variations (variance/mean > 2) and has been shown to improve the results of processing for these data sets. It is shown that the use of a simple flat-background model as in traditional integration programs causes systematic bias in the background determination at ice-ring resolutions, resulting in an overestimation of reflection intensities at the peaks of the ice rings and an underestimation of reflection intensities either side of the ice ring. The new global background-model algorithm presented here corrects for this bias, resulting in a noticeable improvement in R factors following refinement.

Diffraction-geometry refinement in the DIALS framework.

Rapid data collection and modern computing resources provide the opportunity to revisit the task of optimizing the model of diffraction geometry prior to integration. A comprehensive description is given of new software that builds upon established methods by performing a single global refinement procedure, utilizing a smoothly varying model of the crystal lattice where appropriate. This global refinement technique extends to multiple data sets, providing useful constraints to handle the problem of correlated parameters, particularly for small wedges of data. Examples of advanced uses of the software are given and the design is explained in detail, with particular emphasis on the flexibility and extensibility it entails.

Robust background modelling in DIALS.

A method for estimating the background under each reflection during integration that is robust in the presence of pixel outliers is presented. The method uses a generalized linear model approach that is more appropriate for use with Poisson distributed data than traditional approaches to pixel outlier handling in integration programs. The algorithm is most applicable to data with a very low background level where assumptions of a normal distribution are no longer valid as an approximation to the Poisson distribution. It is shown that traditional methods can result in the systematic underestimation of background values. This then results in the reflection intensities being overestimated and gives rise to a change in the overall distribution of reflection intensities in a dataset such that too few weak reflections appear to be recorded. Statistical tests performed during data reduction may mistakenly attribute this to merohedral twinning in the crystal. Application of the robust generalized linear model algorithm is shown to correct for this bias.