Combining X-rays, neutrons and electrons, and NMR, for precision and accuracy in structure-function studies

The four Rs and crystal structure analysis: reliability, reproducibility, replicability and reusability

Within science, of which crystallography is a key part, there are questions posed to all fields that challenge the trust in results. The US National Academies of Sciences, Engineering and Medicine published a thorough report in 2019 on the Reproducibility and Replicability of Science: replicability being where a totally new study attempts to confirm if a phenomenon can be seen independently of another study. Data reuse is a key term in the FAIR data accord [Wilkinson et al. (2016). Sci. Data, 3, 160018], where the acronym FAIR means findable, accessible, interoperable and reusable. In the social sciences, the acronym FACT (namely fairness, accuracy, confidentiality and transparency) has emerged, the idea being that data should be FACTual to ensure trust [van der Aalst et al. (2017). Bus. Inf. Syst. Eng. 59, 311-313]. A distinction also must be made between accuracy and precision; indeed, the authors' lectures at the European Crystallography School ECS6 independently emphasized the need for use of other methods as well as crystal structure analysis to establish accuracy in biological and chemical/material functional contexts. The efforts by disparate science communities to introduce new terms to ensure trust have merit for discussion in crystallographic teaching commissions and possible adoption by crystallographers too.

Raw diffraction data are our ground truth from which all subsequent workflows develop

Defining best practice in science is challenging. International consensus is facilitated by the International Science Council via its members such as the International Union of Crystallography (IUCr). The crystallographic community has many decades of tradition linking articles with the underpinning data, and is admired across all sciences accordingly. Crystallography has always been at the forefront of harnessing new technology in the service of consensus. Technology has provided new vast data-archiving opportunities, allowing the preservation of raw diffraction data, along with article and database depositions of a model's coordinates and associated structure factors. The raw diffraction data, which can now be preserved, are the ground truth from which all subsequent workflows develop. Journal editorial boards provide a practical forum for setting the criteria to decide if a study's files are truly the version of record. Within that, reality involves a variance of reasonable workflows. But what is a reasonable variance? Workflows must be detailed carefully by authors in explaining what they have done. There is a great, and increasing, diversity of macromolecular crystallography analyses, and yet an increased constraint on how much can be written in an article about the workflow used. Raw data provide the ultimate reproducibility evidence. A part of reproducibility and replicability is using an agreed vocabulary; the meaning of words such as precision and accuracy and, more recently, the confidence of a protein structure prediction should feature in approaching `truth'.

Objective crystallographic symmetry classifications of a noisy crystal pattern with strong Fedorov-type pseudosymmetries and its optimal image-quality enhancement

Statistically sound crystallographic symmetry classifications are obtained with information-theory-based methods in the presence of approximately Gaussian distributed noise. A set of three synthetic patterns with strong Fedorov-type pseudosymmetries and varying amounts of noise serve as examples. Contrary to traditional crystallographic symmetry classifications with an image processing program such as CRISP, the classification process does not need to be supervised by a human being and is free of any subjectively set thresholds in the geometric model selection process. This enables crystallographic symmetry classification of digital images that are more or less periodic in two dimensions (2D), also known as crystal patterns, as recorded with sufficient structural resolution from a wide range of crystalline samples with different types of scanning probe and transmission electron microscopes. Correct symmetry classifications enable the optimal crystallographic processing of such images. That processing consists of the averaging over all asymmetric units in all unit cells in the selected image area and significantly enhances both the signal-to-noise ratio and the structural resolution of a microscopic study of a crystal. For sufficiently complex crystal patterns, the information-theoretic symmetry classification methods are more accurate than both visual classifications by human experts and the recommendations of one of the popular crystallographic image processing programs of electron crystallography.

Application of Coarse-Grained (CG) Models to Explore Conformational Pathway of Large-Scale Protein Machines

Protein machines are clusters of protein assemblies that function in order to control the transfer of matter and energy in cells. For a specific protein machine, its working mechanisms are not only determined by the static crystal structures, but also related to the conformational transition dynamics and the corresponding energy profiles. With the rapid development of crystallographic techniques, the spatial scale of resolved structures is reaching up to thousands of residues, and the concomitant conformational changes become more and more complicated, posing a great challenge for computational biology research. Previously, a coarse-grained (CG) model aiming at conformational free energy evaluation was developed and showed excellent ability to reproduce the energy profiles by accurate electrostatic interaction calculations. In this study, we extended the application of the CG model to a series of large-scale protein machine systems. The spike protein trimer of SARS-CoV-2, ATP citrate lyase (ACLY) tetramer, and P4-ATPases systems were carefully studied and discussed as examples. It is indicated that the CG model is effective to depict the energy profiles of the conformational pathway between two endpoint structures, especially for large-scale systems. Both the energy change and energy barrier between endpoint structures provide reasonable mechanism explanations for the associated biological processes, including the opening of receptor binding domain (RBD) of spike protein, the phospholipid transportation of P4-ATPase, and the loop translocation of ACLY. Taken together, the CG model provides a suitable alternative in mechanistic studies related to conformational change in large-scale protein machines.

Trends in coordination of rhenium organometallic complexes in the Protein Data Bank

Radiopharmaceutical development has similar overall characteristics to any biomedical drug development requiring a compound's stability, aqueous solubility and selectivity to a specific disease site. However, organometallic complexes containing 188/186Re or 99mTc involve a d-block transition-metal radioactive isotope and therefore bring additional factors such as metal oxidation states, isotope purity and half life into play. This topical review is focused on the development of radiopharmaceuticals containing the radioisotopes of rhenium and technetium and, therefore, on the occurrence of these organometallic complexes in protein structures in the Worldwide Protein Data Bank (wwPDB). The purpose of incorporating the group 7 transition metals of rhenium/technetium in the protein and the reasons for study by protein crystallography are described, as certain PDB studies were not aimed at drug development. Technetium is used as a medical diagnostic agent and involves the 99mTc isotope which decays to release gamma radiation, thereby employed for its use in gamma imaging. Due to the periodic relationship among group 7 transition metals, the coordination chemistry of rhenium is similar (but not identical) to that of technetium. The types of reactions the potential model radiopharmaceutical would prefer to partake in, and by extension knowing which proteins and biomolecules the compound would react with in vivo, are needed. Crystallography studies, both small molecule and macromolecular, are a key aspect in understanding chemical coordination. Analyses of bonding modes, coordination to particular residues and crystallization conditions are presented. In our Forward look as a concluding summary of this topical review, the question we ask is: what is the best way for this field to progress?

High-Precision X-ray Total Scattering Measurements Using a High-Accuracy Detector System

The total scattering method, which is based on measurements of both Bragg and diffuse scattering on an equal basis, has been still challenging even by means of synchrotron X-rays. This is because such measurements require a wide coverage in scattering vector Q, high Q resolution, and a wide dynamic range for X-ray detectors. There is a trade-off relationship between the coverage and resolution in Q, whereas the dynamic range is defined by differences in X-ray response between detector channels (X-ray response non-uniformity: XRNU). XRNU is one of the systematic errors for individual channels, while it appears to be a random error for different channels. In the present study, taking advantage of the randomness, the true sensitivity for each channel has been statistically estimated. Results indicate that the dynamic range of microstrip modules (MYTHEN, Dectris, Baden-Daettwil, Switzerland), which have been assembled for a total scattering measurement system (OHGI), has been successfully restored from 104 to 106. Furthermore, the correction algorithm has been optimized to increase time efficiencies. As a result, the correcting time has been reduced from half a day to half an hour, which enables on-demand correction for XRNU according to experimental settings. High-precision X-ray total scattering measurements, which has been achieved by a high-accuracy detector system, have demonstrated valence density studies from powder and PDF studies for atomic displacement parameters.