Dynamical diffraction of high-energy electrons by light-atom structures: a multiple forward scattering interpretation.

Because of the strong electron-atom interaction, the kinematic theory of diffraction cannot be used to describe the scattering of electrons by an assembly of atoms due to the strong dynamical diffraction that needs to be taken into account. In this paper, the scattering of high-energy electrons by a regular array of light atoms is solved exactly by applying the T-matrix formalism to the corresponding Schrödinger's equation in spherical coordinates. The independent atom model is used, where each atom is represented by a sphere with an effective constant potential. The validity of the forward scattering approximation and the phase grating approximation, assumed by the popular multislice method, is discussed, and an alternative interpretation of multiple scattering is proposed and compared with existing interpretations.

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology.

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

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.

Small Molecule Microcrystal Electron Diffraction for the Pharmaceutical Industry-Lessons Learned From Examining Over Fifty Samples.

The emerging field of microcrystal electron diffraction (MicroED) is of great interest to industrial researchers working in the drug discovery and drug development space. The promise of being able to routinely solve high-resolution crystal structures without the need to grow large crystals is very appealing. Despite MicroED's exciting potential, adoption across the pharmaceutical industry has been slow, primarily owing to a lack of access to specialized equipment and expertise. Here we present our experience building a small molecule MicroED service pipeline for members of the pharmaceutical industry. In the past year, we have examined more than fifty small molecule samples submitted by our clients, the majority of which have yielded data suitable for structure solution. We also detail our experience determining small molecule MicroED structures of pharmaceutical interest and offer some insights into the typical experimental outcomes. This experience has led us to conclude that small molecule MicroED adoption will continue to grow within the pharmaceutical industry where it is able to rapidly provide structures inaccessible by other methods.

Leginon: New features and applications.

Leginon is a system for automated data acquisition from a transmission electron microscope. Here we provide an updated summary of the overall Leginon architecture and an update of the current state of the package. We also highlight a few recent developments to provide some concrete examples and use cases.

A Workflow for Protein Structure Determination From Thin Crystal Lamella by Micro-Electron Diffraction.

MicroED has recently emerged as a powerful method for the analysis of biological structures at atomic resolution. This technique has been largely limited to protein nanocrystals which grow either as needles or plates measuring only a few hundred nanometers in thickness. Furthermore, traditional microED data processing uses established X-ray crystallography software that is not optimized for handling compound effects that are unique to electron diffraction data. Here, we present an integrated workflow for microED, from sample preparation by cryo-focused ion beam milling, through data collection with a standard Ceta-D detector, to data processing using the DIALS software suite, thus enabling routine atomic structure determination of protein crystals of any size and shape using microED. We demonstrate the effectiveness of the workflow by determining the structure of proteinase K to 2.0 Å resolution and show the advantage of using protein crystal lamellae over nanocrystals.

The predictive power of data-processing statistics.

This study describes a method to estimate the likelihood of success in determining a macromolecular structure by X-ray crystallography and experimental single-wavelength anomalous dispersion (SAD) or multiple-wavelength anomalous dispersion (MAD) phasing based on initial data-processing statistics and sample crystal properties. Such a predictive tool can rapidly assess the usefulness of data and guide the collection of an optimal data set. The increase in data rates from modern macromolecular crystallography beamlines, together with a demand from users for real-time feedback, has led to pressure on computational resources and a need for smarter data handling. Statistical and machine-learning methods have been applied to construct a classifier that displays 95% accuracy for training and testing data sets compiled from 440 solved structures. Applying this classifier to new data achieved 79% accuracy. These scores already provide clear guidance as to the effective use of computing resources and offer a starting point for a personalized data-collection assistant.

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.

Electron diffraction data processing with DIALS.

Electron diffraction is a relatively novel alternative to X-ray crystallography for the structure determination of macromolecules from three-dimensional nanometre-sized crystals. The continuous-rotation method of data collection has been adapted for the electron microscope. However, there are important differences in geometry that must be considered for successful data integration. The wavelength of electrons in a TEM is typically around 40 times shorter than that of X-rays, implying a nearly flat Ewald sphere, and consequently low diffraction angles and a high effective sample-to-detector distance. Nevertheless, the DIALS software package can, with specific adaptations, successfully process continuous-rotation electron diffraction data. Pathologies encountered specifically in electron diffraction make data integration more challenging. Errors can arise from instrumentation, such as beam drift or distorted diffraction patterns from lens imperfections. The diffraction geometry brings additional challenges such as strong correlation between lattice parameters and detector distance. These issues are compounded if calibration is incomplete, leading to uncertainty in experimental geometry, such as the effective detector distance and the rotation rate or direction. Dynamic scattering, absorption, radiation damage and incomplete wedges of data are additional factors that complicate data processing. Here, recent features of DIALS as adapted to electron diffraction processing are shown, including diagnostics for problematic diffraction geometry refinement, refinement of a smoothly varying beam model and corrections for distorted diffraction images. These novel features, combined with the existing tools in DIALS, make data integration and refinement feasible for electron crystallography, even in difficult cases.

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.

Molecular symmetry-constrained systematic search approach to structure solution of the coiled-coil SRGAP2 F-BARx domain.

SRGAP2 (Slit-Robo GTPase-activating protein 2) is a cytoplasmic protein found to be involved in neuronal branching, restriction of neuronal migration and restriction of the length and density of dendritic postsynaptic spines. The extended F-BAR (F-BARx) domain of SRGAP2 generates membrane protrusions when expressed in COS-7 cells, while most F-BARs induce the opposite effect: membrane invaginations. As a first step to understand this discrepancy, the F-BARx domain of SRGAP2 was isolated and crystallized after co-expression with the carboxy domains of the protein. Diffraction data were collected from two significantly non-isomorphous crystals in the same monoclinic C2 space group. A correct molecular-replacment solution was obtained by applying a molecular symmetry-constrained systematic search approach that took advantage of the conserved biological symmetry of the F-BAR domains. It is shown that similar approaches can solve other F-BAR structures that were previously determined by experimental phasing. Diffraction data were reprocessed with a high-resolution cutoff of 2.2 Å, chosen using less strict statistical criteria. This has improved the outcome of multi-crystal averaging and other density-modification procedures.

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.

The 1.1†Šresolution structure of a periplasmic phosphate-binding protein from Stenotrophomonas maltophilia: a crystallization contaminant identified by molecular replacement using the entire Protein Data Bank.

During efforts to crystallize the enzyme 2,4-dihydroxyacetophenone dioxygenase (DAD) from Alcaligenes sp. 4HAP, a small number of strongly diffracting protein crystals were obtained after two years of crystal growth in one condition. The crystals diffracted synchrotron radiation to almost 1.0 Šresolution and were, until recently, assumed to be formed by the DAD protein. However, when another crystal form of this enzyme was eventually solved at lower resolution, molecular replacement using this new structure as the search model did not give a convincing solution with the original atomic resolution data set. Hence, it was considered that these crystals might have arisen from a protein impurity, although molecular replacement using the structures of common crystallization contaminants as search models again failed. A script to perform molecular replacement using MOLREP in which the first chain of every structure in the PDB was used as a search model was run on a multi-core cluster. This identified a number of prokaryotic phosphate-binding proteins as scoring highly in the MOLREP peak lists. Calculation of an electron-density map at 1.1 Šresolution based on the solution obtained with PDB entry 2q9t allowed most of the amino acids to be identified visually and built into the model. A BLAST search then indicated that the molecule was most probably a phosphate-binding protein from Stenotrophomonas maltophilia (UniProt ID B4SL31; gene ID Smal_2208), and fitting of the corresponding sequence to the atomic resolution map fully corroborated this. Proteins in this family have been linked to the virulence of antibiotic-resistant strains of pathogenic bacteria and with biofilm formation. The structure of the S. maltophilia protein has been refined to an R factor of 10.15% and an Rfree of 12.46% at 1.1 Šresolution. The molecule adopts the type II periplasmic binding protein (PBP) fold with a number of extensively elaborated loop regions. A fully dehydrated phosphate anion is bound tightly between the two domains of the protein and interacts with conserved residues and a number of helix dipoles.

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.

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.

dxtbx: the diffraction experiment toolbox.

Data formats for recording X-ray diffraction data continue to evolve rapidly to accommodate new detector technologies developed in response to more intense light sources. Processing the data from single-crystal X-ray diffraction experiments therefore requires the ability to read, and correctly interpret, image data and metadata from a variety of instruments employing different experimental representations. Tools that have previously been developed to address this problem have been limited either by a lack of extensibility or by inconsistent treatment of image metadata. The dxtbx software package provides a consistent interface to both image data and experimental models, while supporting a completely generic user-extensible approach to reading the data files. The library is written in a mixture of C++ and Python and is distributed as part of the cctbx under an open-source licence at http://cctbx.sourceforge.net.

Clustering procedures for the optimal selection of data sets from multiple crystals in macromolecular crystallography.

The availability of intense microbeam macromolecular crystallography beamlines at third-generation synchrotron sources has enabled data collection and structure solution from microcrystals of <10 µm in size. The increased likelihood of severe radiation damage where microcrystals or particularly sensitive crystals are used forces crystallographers to acquire large numbers of data sets from many crystals of the same protein structure. The associated analysis and merging of multi-crystal data is currently a manual and time-consuming step. Here, a computer program, BLEND, that has been written to assist with and automate many of the steps in this process is described. It is demonstrated how BLEND has successfully been used in the solution of a novel membrane protein.

S-Adenosyl-S-carboxymethyl-L-homocysteine: a novel cofactor found in the putative tRNA-modifying enzyme CmoA.

Uridine at position 34 of bacterial transfer RNAs is commonly modified to uridine-5-oxyacetic acid (cmo(5)U) to increase the decoding capacity. The protein CmoA is involved in the formation of cmo(5)U and was annotated as an S-adenosyl-L-methionine-dependent (SAM-dependent) methyltransferase on the basis of its sequence homology to other SAM-containing enzymes. However, both the crystal structure of Escherichia coli CmoA at 1.73 Å resolution and mass spectrometry demonstrate that it contains a novel cofactor, S-adenosyl-S-carboxymethyl-L-homocysteine (SCM-SAH), in which the donor methyl group is substituted by a carboxymethyl group. The carboxyl moiety forms a salt-bridge interaction with Arg199 that is conserved in a large group of CmoA-related proteins but is not conserved in other SAM-containing enzymes. This raises the possibility that a number of enzymes that have previously been annotated as SAM-dependent are in fact SCM-SAH-dependent. Indeed, inspection of electron density for one such enzyme with known X-ray structure, PDB entry 1im8, suggests that the active site contains SCM-SAH and not SAM.

Structure and activity of a novel archaeal ß-CASP protein with N-terminal KH domains.

MTH1203, a ß-CASP metallo-ß-lactamase family nuclease from the archaeon Methanothermobacter thermautotrophicus, was identified as a putative nuclease that might contribute to RNA processing. The crystal structure of MTH1203 reveals that, in addition to the metallo-ß-lactamase nuclease and the ß-CASP domains, it contains two contiguous KH domains that are unique to MTH1203 and its orthologs. RNA-binding experiments indicate that MTH1203 preferentially binds U-rich sequences with a dissociation constant in the micromolar range. In vitro nuclease activity assays demonstrated that MTH1203 is a zinc-dependent nuclease. MTH1203 is also shown to be a dimer and, significantly, this dimerization enhances the nuclease activity. Transcription termination in archaea produces mRNA transcripts with U-rich 3' ends that could be degraded by MTH1203 considering its RNA-binding specificity. We hypothesize that this nuclease degrades mRNAs of proteins targeted for degradation and so regulates archaeal RNA turnover, possibly in concert with the exosome.