Search

Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in both crystallography and cryo-EM. Indeed, previous crystallographic work on the errors in structural models is directly applicable to likelihood targets in cryo-EM. Likelihood targets in Fourier space are derived here to characterise, based on the comparison of half-maps, the direction- and resolution-dependent variation in the strength of both signal and noise in the data. Because the signal depends on local features, the signal and noise are analysed in local regions of the cryo-EM reconstruction. The likelihood analysis extends to prediction of the signal that will be achieved in any docking calculation for a model of specified quality and completeness. A related calculation generalises a previous measure of the information gained by making the cryo-EM reconstruction.

Funder: Phenix Industrial Consortium, Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold. Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of Cα atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

The process of platelet production has so far been understood to be a 2-stage process: megakaryocyte maturation from hematopoietic stem cells followed by proplatelet formation, with each phase regulating the peripheral blood platelet count. Proplatelet formation releases into the bloodstream beads-on-a-string preplatelets, which undergo fission into mature platelets. For the first time, we show that preplatelet maturation is a third, tightly regulated, critical process akin to cytokinesis that regulates platelet count. We show that deficiency in cytokine receptor-like factor 3 (CRLF3) in mice leads to an isolated and sustained 25% to 48% reduction in the platelet count without any effect on other blood cell lineages. We show that Crlf3−/− preplatelets have increased microtubule stability, possibly because of increased microtubule glutamylation via the interaction of CRLF3 with key members of the Hippo pathway. Using a mouse model of JAK2 V617F essential thrombocythemia, we show that a lack of CRLF3 leads to long-term lineage-specific normalization of the platelet count. We thereby postulate that targeting CRLF3 has therapeutic potential for treatment of thrombocythemia.

AI-based methods such as AlphaFold have revolutionized structural biology, often making it possible to predict protein structures with high accuracy. The accuracies of these predictions vary, however, and they do not include ligands, covalent modifications or other environmental factors. Here we focus on very-high-confidence parts of AlphaFold predictions, evaluating how well they can be expected to describe the structure of a protein in a particular environment. We compare predictions with experimental crystallographic maps of the same proteins for 102 crystal structures. In many cases, those parts of AlphaFold predictions that were predicted with very high confidence matched experimental maps remarkably closely. In other cases, these predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. Overall, Cαatoms in very-high-confidence parts of AlphaFold predictions differed from corresponding crystal structures by a median of 0.6 Å, and about 10% of these differed by more than 2 Å, each about twice the values found for pairs of crystal structures containing the same components but determined in different space groups. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log-likelihood-gain (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom–atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

The employment of directed acyclic graphs to advance the tracking, control and appraisal of crystallographic phasing strategies is discussed., Crystallographic phasing strategies increasingly require the exploration and ranking of many hypotheses about the number, types and positions of atoms, molecules and/or molecular fragments in the unit cell, each with only a small chance of being correct. Accelerating this move has been improvements in phasing methods, which are now able to extract phase information from the placement of very small fragments of structure, from weak experimental phasing signal or from combinations of molecular replacement and experimental phasing information. Describing phasing in terms of a directed acyclic graph allows graph-management software to track and manage the path to structure solution. The crystallographic software supporting the graph data structure must be strictly modular so that nodes in the graph are efficiently generated by the encapsulated functionality. To this end, the development of new software, Phasertng, which uses directed acyclic graphs natively for input/output, has been initiated. In Phasertng, the codebase of Phaser has been rebuilt, with an emphasis on modularity, on scripting, on speed and on continuing algorithm development. As a first application of phasertng, its advantages are demonstrated in the context of phasertng.xtricorder, a tool to analyse and triage merged data in preparation for molecular replacement or experimental phasing. The description of the phasing strategy with directed acyclic graphs is a generalization that extends beyond the functionality of Phasertng, as it can incorporate results from bioinformatics and other crystallographic tools, and will facilitate multifaceted search strategies, dynamic ranking of alternative search pathways and the exploitation of machine learning to further improve phasing strategies.

The prerequisites for density modification of maps from electron cryomicroscopy are examined and a procedure for incorporating model-based information is presented., Density modification uses expectations about features of a map such as a flat solvent and expected distributions of density in the region of the macromolecule to improve individual Fourier terms representing the map. This process transfers information from one part of a map to another and can improve the accuracy of a map. Here, the assumptions behind density modification for maps from electron cryomicroscopy are examined and a procedure is presented that allows the incorporation of model-based information. Density modification works best in cases where unfiltered, unmasked maps with clear boundaries between the macromolecule and solvent are visible, and where there is substantial noise in the map, both in the region of the macromolecule and the solvent. It also is most effective if the characteristics of the map are relatively constant within regions of the macromolecule and the solvent. Model-based information can be used to improve density modification, but model bias can in principle occur. Here, model bias is reduced by using ensemble models that allow an estimation of model uncertainty. A test of model bias is presented that suggests that even if the expected density in a region of a map is specified incorrectly by using an incorrect model, the incorrect expectations do not strongly affect the final map.

A density modification procedure for improving maps produced by single-particle electron cryo-microscopy is presented. The theoretical basis of the method is identical to that of maximum-likelihood density modification, previously used to improve maps from macromolecular X-ray crystallography. Two key differences from applications in crystallography are that the errors in Fourier coefficients are largely in the phases in crystallography but in both phases and amplitudes in electron cryo-microscopy, and that half-maps with independent errors are available in electron cryo-microscopy. These differences lead to a distinct approach for combination of information from starting maps with information obtained in the density modification process. The applicability of density modification theory to electron cryo-microscopy was evaluated using half-maps for apoferritin at a resolution of 3.1 Å and a matched 1.8 Å reference map. Error estimates for the map obtained by density modification were found to closely agree with true errors as estimated by comparison with the reference map. The density modification procedure was applied to a set of 104 datasets where half-maps, a full map and a model all had been deposited. The procedure improved map-model correlation and increased the visibility of details in the maps. The procedure requires two unmasked half-maps and a sequence file or other source of information on the volume of the macromolecule that has been imaged.

The editors discuss the submission of structural biology data.

Funder: CCP4, Funder: Max‐Planck‐Gesellschaft; Id: http://dx.doi.org/10.13039/501100004189, The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real‐world application. In CASP7, the metric for molecular replacement assessment involved full likelihood‐based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood‐based rigid‐body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log‐likelihood‐gain (LLG) score. This enabled multi‐copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative‐expected‐LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X‐ray, NMR or cryo‐EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

Glycine N-acyltransferase (GLYAT; EC 2.3.1.13) is a key enzyme in mammalian homeostasis that has been linked to several pathologies in humans, including cancer. Here we report the first crystal structure of a member of the GLYAT family, and a detailed interpretation of its structure and enzymatic mechanism. This work will aid further studies on GLYAT and its involvement in metabolic diseases and cancer.

DeepMind presented remarkably accurate protein structure predictions at the CASP14 conference. We explored network architectures incorporating related ideas and obtained the best performance with a 3-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The 3-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate models of protein-protein complexes from sequence information alone, short circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.One-Sentence SummaryAccurate protein structure modeling enables rapid solution of structure determination problems and provides insights into biological function.

The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high- coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. We here use the data from CASP14 to explore the prospect for changes in phasing methods, and in particular to explore the prospects for molecular replacement phasing using in silico models.SynopsisWe discuss the implications of the AlphaFold2 protein structure modelling software for crystallographic phasing strategies.

An intensity-based likelihood method is provided to estimate scattering from an anomalous substructure considering the effect of measurement errors in Bijvoet pairs and the correlations between these errors., SAD phasing can be challenging when the signal-to-noise ratio is low. In such cases, having an accurate estimate of the substructure content can determine whether or not the substructure of anomalous scatterer positions can successfully be determined. Here, a likelihood-based target function is proposed to accurately estimate the strength of the anomalous scattering contribution directly from the measured intensities, determining a complex correlation parameter relating the Bijvoet mates as a function of resolution. This gives a novel measure of the intrinsic anomalous signal. The SAD likelihood target function also accounts for correlated errors in the measurement of intensities from Bijvoet mates, which can arise from the effects of radiation damage. When the anomalous signal is assumed to come primarily from a substructure comprising one anomalous scatterer with a known value of f′′ and when the protein composition of the crystal is estimated correctly, the refined complex correlation parameters can be interpreted in terms of the atomic content of the primary anomalous scatterer before the substructure is known. The maximum-likelihood estimation of substructure content was tested on a curated database of 357 SAD cases with useful anomalous signal. The prior estimates of substructure content are highly correlated to the content determined by phasing calculations, with a correlation coefficient (on a log–log basis) of 0.72.

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution., IU acknowledges support from the Spanish Ministry of Economy and Competitiveness by grants BIO2015-64216-P, PGC2018-101370-B-100 and MDM2014-0435-01 and from Generalitat de Catalunya by grant 2017SGR-1192. IC acknowledges support from the Spanish Ministry of Economy and Competitiveness by grant BES-2016-076329. PVA acknowledges support from the US Department of Energy under Contract No. DE-AC02-05CH11231 and the PHENIX Industrial Consortium. RJR acknowledges support from Wellcome Trust Principal Research Fellowship grant 209407/ Z/17/Z and National Institutes of Health grant P01GM063210. MDS gratefully acknowledges fellowship support from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant (number 790122).

In the past 50 years, molecular replacement (MR) has grown from being a way to shortcut the occasional determination of identical or closely related structures to being the route to the majority of protein crystal structures. The 2019 CCP4 Study Weekend on Molecular Replacement, held on 9–10 January 2019 in Nottingham, UK, looked briefly at its long history but focused on recent developments that have helped to push its reach to a much greater range of structures. The special issue at https://journals.iucr.org/ special_issues/2020/CCP42019/ contains contributions from the majority of the speakers at the meeting.

When building atomic models into weak and/or low-resolution density, a common strategy is to restrain its conformation to that of a higher-resolution model of the same or similar sequence. When doing so, it is important to avoid over-restraining to the reference model in the face of disagreement with the experimental data. The most common strategy for this is the use of “top-out” potentials. These act like simple harmonic restraints within a defined range, but gradually weaken when the deviation between the model and reference grows larger than a defined transition point. In each current implementation, the rate at which the potential flattens beyond the transition region follows a fixed form – although the form chosen varies between implementations. A restraint potential with a tuneable rate of flattening would provide greater flexibility to encode the confidence in any given restraint. Here we describe two new such potentials: a Cartesian distance restraint derived from a recent generalisation of common loss functions, and a periodic torsion restraint based on a renormalisation of the von Mises distribution. Further, we describe their implementation as user-adjustable/switchable restraints in ISOLDE, and demonstrate their use in some real-world examples.SynopsisNew forms of adaptive or top-out distance and torsion restraints are described, suitable for restraining a model to match a reference structure during interactive rebuilding. In addition, their implementation in ISOLDE is described along with some illustrative example applications.

DEN refinement and automated model building with AutoBuild were used to determine the structure of a putative succinyl-diaminopimelate desuccinylase from C. glutamicum. This difficult case of molecular-replacement phasing shows that the synergism between DEN refinement and AutoBuild outperforms standard refinement protocols., Phasing by molecular replacement remains difficult for targets that are far from the search model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 Å resolution is described using a combination of homology modeling with MODELLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and automated model building using AutoBuild in a semi-automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting model to guide the movements of the model during refinement. The resulting improved model phases provide better starting points for automated model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of automated procedures that require manual adjustment of local sequence misalignments between the homology model and the target sequence.

Angiotensinogen (AGT) is a critical protein in the renin-angiotensin-aldosterone system and may have an important role in the pathogenesis of pre-eclampsia. The disulphide linkage between cysteines 18 and 138 has a key role in the redox switch of AGT which modulates the release of angiotensin I with consequential effects on blood pressure. In this paper, we report a quantitative targeted LC-MS/MS method for the reliable measurement of the total AGT and its reduced and oxidised forms in human plasma. AGT was selectively enriched from human plasma using two-dimensional chromatography employing concanavalin A lectin affinity and reversed phase steps and then deglycosylated using PNGase F. A differential alkylation approach was coupled with targeted LC-MS/MS method to identify the two AGT forms in the plasma chymotryptic digest. An additional AGT proteolytic marker peptide was identified and used to measure total AGT levels. The developed MS workflow enabled the reproducible detection of total AGT and its two distinct forms in human plasma with analytical precision of ≤ 15%. The LC-MS/MS assay for total AGT in plasma showed a linear response (R2 = 0.992) with a limit of quantification in the low nanomolar range. The method gave suitable validation characteristics for biomedical application to the quantification of the oxidation level and the total level of AGT in plasma samples collected from normal and pre-eclamptic patients. Electronic supplementary material The online version of this article (10.1007/s00216-018-1455-2) contains supplementary material, which is available to authorized users.

Macromolecular structures can be solved by molecular replacement provided that suitable search models are available. Models from distant homologues may deviate too much from the target structure to succeed, notwithstanding an overall similar fold or even their featuring areas of very close geometry. Successful methods to make the most of such templates usually rely on the degree of conservation to select and improve search models. ARCIMBOLDO_ SHREDDER uses fragments derived from distant homologues in a brute-force approach driven by the experimental data, instead of by sequence similarity. The new algorithms implemented in ARCIMBOLDO_SHREDDER are described in detail, illustrating its characteristic aspects in the solution of new and test structures. In an advance from the previously published algorithm, which was based on omitting or extracting contiguous polypeptide spans, model generation now uses three-dimensional volumes respecting structural units. The optimal fragment size is estimated from the expected log-likelihood gain (LLG) values computed assuming that a substructure can be found with a level of accuracy near that required for successful extension of the structure, typically below 0.6 A ° root-mean-square deviation (r.m.s.d.) from the target. Better sampling is attempted through model trimming or decomposition into rigid groups and optimization through Phaser’s gyre refinement. Also, after model translation, packing filtering and refinement, models are either disassembled into predetermined rigid groups and refined (gimble refinement) or Phaser’s LLGguided pruning is used to trim the model of residues that are not contributing signal to the LLG at the target r.m.s.d. value. Phase combination among consistent partial solutions is performed in reciprocal space with ALIXE. Finally, density modification and main-chain autotracing in SHELXE serve to expand to the full structure and identify successful solutions. The performance on test data and the solution of new structures are described., MS and CM received financial support from CCP4 for a research stay in the group of RJR. CM is grateful to MINECO for her BES-2015-071397 scholarship associated with the Structural Biology Maria de Maeztu Unit of Excellence. AFZN received a fellowship from Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´ gico (CNPq), Brazil. GP acknowledges the Generalitat de Catalunya for an Industrial Doctorate predoctoral fellowship at Biochemize S.L. This work was supported by grants BIO2015-64216-P, BIO2013- 49604-EXP, BFU2014-59389-P and MDM2014-0435-01 from the Spanish Ministry of Economy and Competitiveness and 2014SGR-997 from Generalitat de Catalunya. This research was supported by the Wellcome Trust (Principal Research Fellowship to RJR, grant 082961/Z/07/Z) and by grant BB/ L006014/1 from the BBSRC, UK. The research was facilitated by Wellcome Trust Strategic Award 100140 to the Cambridge Institute for Medical Research. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 635595 (CarbaZymes).

The unprecedented progress of modern science is driven, to a large extent, by the fast propagation of information. Descriptions of experiments and results, and their interpretation, are no longer disseminated solely in peer-reviewed scientific publications, but are frequently distributed through non-reviewed publication platforms as preprints, entries to data repositories, databases etc. As a result of ever faster computers and internet connections, many experimental results are now available instantaneously at the click of a mouse, irrespective of the location of the source or consumer.

The majority of macromolecular crystal structures are determined using the method of molecular replacement, in which known related structures are rotated and translated to provide an initial atomic model for the new structure. A theoretical understanding of the signal-to-noise ratio in likelihood-based molecular replacement searches has been developed to account for the influence of model quality and completeness, as well as the resolution of the diffraction data. Here we show that, contrary to current belief, molecular replacement need not be restricted to the use of models comprising a substantial fraction of the unknown structure. Instead, likelihood-based methods allow a continuum of applications depending predictably on the quality of the model and the resolution of the data. Unexpectedly, our understanding of the signal-to-noise ratio in molecular replacement leads to the finding that, with data to sufficiently high resolution, fragments as small as single atoms of elements usually found in proteins can yield ab initio solutions of macromolecular structures, including some that elude traditional direct methods.

Improved coordinate error estimates are proposed for the X-ray and NMR models used for maximum-likelihood-based molecular-replacement phasing., Good prior estimates of the effective root-mean-square deviation (r.m.s.d.) between the atomic coordinates of the model and the target optimize the signal in molecular replacement, thereby increasing the success rate in difficult cases. Previous studies using protein structures solved by X-ray crystallography as models showed that optimal error estimates (refined after structure solution) were correlated with the sequence identity between the model and target, and with the number of residues in the model. Here, this work has been extended to find additional correlations between parameters of the model and the target and hence improved prior estimates of the coordinate error. Using a graph database, a curated set of 6030 molecular-replacement calculations using models that had been solved by X-ray crystallography was analysed to consider about 120 model and target parameters. Improved estimates were achieved by replacing the sequence identity with the Gonnet score for sequence similarity, as well as by considering the resolution of the target structure and the MolProbity score of the model. This approach was extended by analysing 12 610 additional molecular-replacement calculations where the model was determined by NMR. The median r.m.s.d. between pairs of models in an ensemble was found to be correlated with the estimated r.m.s.d. to the target. For models solved by NMR, the overall coordinate error estimates were larger than for structures determined by X-ray crystallography, and were more highly correlated with the number of residues.

The information content gained by making a diffraction-intensity measurement is a natural criterion for deciding which data make a useful contribution and which can legitimately be omitted from a calculation., The information gained by making a measurement, termed the Kullback–Leibler divergence, assesses how much more precisely the true quantity is known after the measurement was made (the posterior probability distribution) than before (the prior probability distribution). It provides an upper bound for the contribution that an observation can make to the total likelihood score in likelihood-based crystallographic algorithms. This makes information gain a natural criterion for deciding which data can legitimately be omitted from likelihood calculations. Many existing methods use an approximation for the effects of measurement error that breaks down for very weak and poorly measured data. For such methods a different (higher) information threshold is appropriate compared with methods that account well for even large measurement errors. Concerns are raised about a current trend to deposit data that have been corrected for anisotropy, sharpened and pruned without including the original unaltered measurements. If not checked, this trend will have serious consequences for the reuse of deposited data by those who hope to repeat calculations using improved new methods.

AMPylation is an inactivating modification that alters the activity of the major endoplasmic reticulum (ER) chaperone BiP to match the burden of unfolded proteins. A single ER‐localised Fic protein, FICD (HYPE), catalyses both AMPylation and deAMPylation of BiP. However, the basis for the switch in FICD's activity is unknown. We report on the transition of FICD from a dimeric enzyme, that deAMPylates BiP, to a monomer with potent AMPylation activity. Mutations in the dimer interface, or of residues along an inhibitory pathway linking the dimer interface to the enzyme's active site, favour BiP AMPylation in vitro and in cells. Mechanistically, monomerisation relieves a repressive effect allosterically propagated from the dimer interface to the inhibitory Glu234, thereby permitting AMPylation‐competent binding of MgATP. Moreover, a reciprocal signal, propagated from the nucleotide‐binding site, provides a mechanism for coupling the oligomeric state and enzymatic activity of FICD to the energy status of the ER.

Recent developments in the Phenix software package are described in the context of macromolecular structure determination using X-rays, neutrons and electrons., Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Performance in the model refinement category of the 13th round of Critical Assessment of Structure Prediction (CASP13) is assessed, showing that some groups consistently improve most starting models whereas the majority of participants continue to degrade the starting model on average. Using the ranking formula developed for CASP12, it is shown that only 7 of 32 groups perform better than a "naive predictor" who just submits the starting model. Common features in their approaches include a dependence on physics-based force fields to judge alternative conformations and the use of molecular dynamics to relax models to local minima, usually with some restraints to prevent excessively large movements. In addition to the traditional CASP metrics that focus largely on the quality of the overall fold, alternative metrics are evaluated, including comparisons of the main-chain and side-chain torsion angles, and the utility of the models for solving crystal structures by the molecular replacement method. It is proposed that the introduction of these metrics, as well as consideration of the accuracy of coordinate error estimates, would improve the discrimination between good and very good models.

AMPylation is an inactivating modification that matches the activity of the major endoplasmic reticulum (ER) chaperone BiP to the burden of unfolded proteins. A single ER-localised Fic protein, FICD (HYPE), catalyses both AMPylation and deAMPylation of BiP. However, the basis for the switch in FICD’s activity is unknown. We report on the transition of FICD from a dimeric enzyme, that deAMPylates BiP, to a monomer with potent AMPylation activity. Mutations in the dimer interface or in residues tracing an inhibitory relay from the dimer interface to the enzyme’s active site favour BiP AMPylation in vitro and in cells. Mechanistically, monomerisation relieves a repressive effect allosterically-propagated from the dimer interface to the inhibitory Glu234, thereby permitting AMPylation-competent binding of MgATP. Whereas, a reciprocal signal propagated from the nucleotide binding site, provides a mechanism for coupling the oligomeric-state and enzymatic activity of FICD to the energy status of the ER.Impact StatementUnique amongst known chaperones, the endoplasmic reticulum (ER)-localized Hsp70, BiP, is subject to transient inactivation under conditions of low ER stress by reversible, covalent modification – AMPylation. The enzyme responsible for this modification, FICD, is in fact a bifunctional enzyme with a single active site capable of both AMPylation and deAMPylation. Here we elucidate, by biochemical, biophysical and structural means, the mechanism by which this enzyme is able to switch enzymatic modality: by regulation of its oligomeric state. The oligomeric state-dependent reciprocal regulation of FICD activity is, in turn, sensitive to the ATP/ADP ratio. This allosteric pathway potentially facilitates the sensing of unfolded protein load in the ER and permits the transduction of this signal into a post-translational buffering of ER chaperone activity.

The solution of a structure of human Rab27a suffering from severe anisotropy and translational noncrystallographic symmetry was aided by identifying diffraction measurements with low information content., Data pathologies caused by effects such as diffraction anisotropy and translational noncrystallographic symmetry (tNCS) can dramatically complicate the solution of the crystal structures of macromolecules. Such problems were encountered in determining the structure of a mutant form of Rab27a, a member of the Rab GTPases. Mutant Rab27a constructs that crystallize in the free form were designed for use in the discovery of drugs to reduce primary tumour invasiveness and metastasis. One construct, hRab27aMut, crystallized within 24 h and diffracted to 2.82 Å resolution, with a unit cell possessing room for a large number of protein copies. Initial efforts to solve the structure using molecular replacement by Phaser were not successful. Analysis of the data set revealed that the crystals suffered from both extreme anisotropy and strong tNCS. As a result, large numbers of reflections had estimated standard deviations that were much larger than their measured intensities and their expected intensities, revealing problems with the use of such data at the time in Phaser. By eliminating extremely weak reflections with the largest combined effects of anisotropy and tNCS, these problems could be avoided, allowing a molecular-replacement solution to be found. The lessons that were learned in solving this structure have guided improvements in the numerical analysis used in Phaser, particularly in identifying diffraction measurements that convey very little information content. The calculation of information content could also be applied as an alternative to ellipsoidal truncation. The post-mortem analysis also revealed an oversight in accounting for measurement errors in the fast rotation function. While the crystal of mutant Rab27a is not amenable to drug screening, the structure can guide new modifications to obtain more suitable crystal forms.

Performance in the template-based modeling (TBM) category of CASP13 is assessed here, using a variety of metrics. Performance of the predictor groups that participated is ranked using the primary ranking score that was developed by the assessors for CASP12. This reveals that the best results are obtained by groups that include contact predictions or inter-residue distance predictions derived from deep multiple sequence alignments. In cases where there is a good homologue in the wwPDB (TBM-easy category), the best results are obtained by modifying a template. However, for cases with poorer homologues (TBM-hard), very good results can be obtained without using an explicit template, by deep learning algorithms trained on the wwPDB. Alternative metrics are introduced, to allow testing of aspects of structural models that are not addressed by traditional CASP metrics. These include comparisons to the main-chain and side-chain torsion angles of the target, and the utility of models for solving crystal structures by the molecular replacement method. The alternative metrics are poorly correlated with the traditional metrics, and it is proposed that modeling has reached a sufficient level of maturity that the best models should be expected to satisfy this wider range of criteria.

The ability of bacteria to infect a host relies in part on the secretion of molecular virulence factors across the cell envelope. Pseudomonas aeruginosa, a ubiquitous environmental bacterium causing opportunistic infections in humans, employs the type II secretion system (T2SS) to transport effector proteins across its cellular envelope as part of a diverse array of virulence strategies. General secretory pathway protein L (GspL) is an essential inner-membrane component of the T2SS apparatus, and is thought to facilitate transduction of the energy from ATP hydrolysis in the cytoplasm to the periplasmic components of the system. However, our incomplete understanding of the assembly principles of the T2SS machinery prevents the mechanistic deconvolution of T2SS-mediated protein secretion. Here we show via two crystal structures that the periplasmic ferredoxin-like domain of GspL (GspLfld) is a dimer stabilized by hydrophobic interactions, and that this interface may allow significant interdomain plasticity. The general dimerization mode of GspLfld is shared with GspL from Vibrio parahaemolyticus suggesting a conserved oligomerization mode across the GspL family. Furthermore, we identified a tetrameric form of the complete periplasmic segment of GspL (GspLperi) which indicates that GspL may be able to adopt multiple oligomeric states as part of its dynamic role in the T2SS apparatus.

A recent publication by Seng et al. in this journal reports the crystallographic structure of refolded, full-length SMN protein and two disease-relevant derivatives thereof. Here, we would like to suggest that at least two of the structures reported in that study are incorrect. We present evidence that one of the associated crystallographic datasets is derived from a crystal of the bacterial Sm-like protein Hfq and that a second dataset is derived from a crystal of the bacterial Gab protein. Both proteins are frequent contaminants of bacterially overexpressed proteins which might have been co-purified during metal affinity chromatography. A third structure presented in the Seng et al. paper cannot be examined further because neither the atomic coordinates, nor the diffraction intensities were made publicly available. The Tudor domain protein SMN has been shown to be a component of the SMN complex, which mediates the assembly of RNA-protein complexes of uridine-rich small nuclear ribonucleoproteins (UsnRNPs). Importantly, this activity is reduced in SMA patients, raising the possibility that the aetiology of SMA is linked to RNA metabolism. Structural studies on diverse components of the SMN complex, including fragments of SMN itself have contributed greatly to our understanding of the cellular UsnRNP assembly machinery. Yet full-length SMN has so far evaded structural elucidation. The Seng et al. study claimed to have closed this gap, but based on the results presented here, the only conclusion that can be drawn is that the Seng et al. study is largely invalid and should be retracted from the literature. published