Structure solution with ARCIMBOLDO using fragments derived from distant homology models

Molecular and structural basis of oligopeptide recognition by the Ami transporter system in pneumococci

ATP-binding cassette (ABC) transport systems are crucial for bacteria to ensure sufficient uptake of nutrients that are not produced de novo or improve the energy balance. The cell surface of the pathobiont Streptococcus pneumoniae (pneumococcus) is decorated with a substantial array of ABC transporters, critically influencing nasopharyngeal colonization and invasive infections. Given the auxotrophic nature of pneumococci for certain amino acids, the Ami ABC transporter system, orchestrating oligopeptide uptake, becomes indispensable in host compartments lacking amino acids. The system comprises five exposed Oligopeptide Binding Proteins (OBPs) and four proteins building the ABC transporter channel. Here, we present a structural analysis of all the OBPs in this system. Multiple crystallographic structures, capturing both open and closed conformations along with complexes involving chemically synthesized peptides, have been solved at high resolution providing insights into the molecular basis of their diverse peptide specificities. Mass spectrometry analysis of oligopeptides demonstrates the unexpected remarkable promiscuity of some of these proteins when expressed in Escherichia coli, displaying affinity for a wide range of peptides. Finally, a model is proposed for the complete Ami transport system in complex with its various OBPs. We further disclosed, through in silico modelling, some essential structural changes facilitating oligopeptide transport into the cellular cytoplasm. Thus, the structural analysis of the Ami system provides valuable insights into the mechanism and specificity of oligopeptide binding by the different OBPs, shedding light on the intricacies of the uptake mechanism and the in vivo implications for this human pathogen.

Structural characterization of PaaX, the main repressor of the phenylacetate degradation pathway in Escherichia coli W: A novel fold of transcription regulator proteins

PaaX is a transcriptional repressor of the phenylacetic acid (PAA) catabolic pathway, a central route for bacterial aerobic degradation of aromatic compounds. Induction of the route is achieved through the release of PaaX from its promoter sequences by the first compound of the pathway, phenylacetyl-coenzyme A (PA-CoA). We report the crystal structure of PaaX from Escherichia coli W. PaaX displays a novel type of fold for transcription regulators, showing a dimeric conformation where the monomers present a three-domain structure: an N-terminal winged helix-turn-helix domain, a dimerization domain similar to the Cas2 protein and a C-terminal domain without structural homologs. The domains are separated by a crevice amenable to harbour a PA-CoA molecule. The biophysical characterization of the protein in solution confirmed several hints predicted from the structure, i.e. its dimeric conformation, a modest importance of cysteines and a high dependence of solubility and thermostability on ionic strength. At a moderately acidic pH, the protein formed a stable folding intermediate with remaining α-helical structure, a disrupted tertiary structure and exposed hydrophobic patches. Our results provide valuable information to understand the stability and mechanism of PaaX and pave the way for further analysis of other regulators with similar structural configurations.

Modes and model building in SHELXE

Density modification is a standard step to provide a route for routine structure solution by any experimental phasing method, with single-wavelength or multi-wavelength anomalous diffraction being the most popular methods, as well as to extend fragments or incomplete models into a full solution. The effect of density modification on the starting maps from either source is illustrated in the case of SHELXE. The different modes in which the program can run are reviewed; these include less well known uses such as reading external phase values and weights or phase distributions encoded in Hendrickson-Lattman coefficients. Typically in SHELXE, initial phases are calculated from experimental data, from a partial model or map, or from a combination of both sources. The initial phase set is improved and extended by density modification and, if the resolution of the data and the type of structure permits, polyalanine tracing. As a feature to systematically eliminate model bias from phases derived from predicted models, the trace can be set to exclude the area occupied by the starting model. The trace now includes an extension into the gamma position or hydrophobic and aromatic side chains if a sequence is provided, which is performed in every tracing cycle. Once a correlation coefficient of over 30% between the structure factors calculated from such a trace and the native data indicates that the structure has been solved, the sequence is docked in all model-building cycles and side chains are fitted if the map supports it. The extensions to the tracing algorithm brought in to provide a complete model are discussed. The improvement in phasing performance is assessed using a set of tests.

XDSGUI: a graphical user interface for XDS, SHELX and ARCIMBOLDO

XDSGUI is a lightweight graphical user interface (GUI) for the XDS, SHELX and ARCIMBOLDO program packages that serves both novice and experienced users in obtaining optimal processing and phasing results for X-ray, neutron and electron diffraction data. The design of the program enables data processing and phasing without command line usage, and supports advanced command flows in a simple user-modifiable and user-extensible way. The GUI supplies graphical information based on the tabular log output of the programs, which is more intuitive, comprehensible and efficient than text output can be.

Predicted models and CCP4

In late 2020, the results of CASP14, the 14th event in a series of competitions to assess the latest developments in computational protein structure-prediction methodology, revealed the giant leap forward that had been made by Google's Deepmind in tackling the prediction problem. The level of accuracy in their predictions was the first instance of a competitor achieving a global distance test score of better than 90 across all categories of difficulty. This achievement represents both a challenge and an opportunity for the field of experimental structural biology. For structure determination by macromolecular X-ray crystallography, access to highly accurate structure predictions is of great benefit, particularly when it comes to solving the phase problem. Here, details of new utilities and enhanced applications in the CCP4 suite, designed to allow users to exploit predicted models in determining macromolecular structures from X-ray diffraction data, are presented. The focus is mainly on applications that can be used to solve the phase problem through molecular replacement.

Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER

Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios.

Electron Diffraction of 3D Molecular Crystals

Electron crystallography has a storied history which rivals that of its more established X-ray-enabled counterpart. Recent advances in data collection and analysis have sparked a renaissance in the field, opening a new chapter for this venerable technique. Burgeoning interest in electron crystallography has spawned innovative methods described by various interchangeable labels (3D ED, MicroED, cRED, etc.). This Review covers concepts and findings relevant to the practicing crystallographer, with an emphasis on experiments aimed at using electron diffraction to elucidate the atomic structure of three-dimensional molecular crystals.

MrParse: finding homologues in the PDB and the EBI AlphaFold database for molecular replacement and more

Crystallographers have an array of search-model options for structure solution by molecular replacement (MR). The well established options of homologous experimental structures and regular secondary-structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may be carried out locally or may use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help to streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any experimental homologues found using eLLG, which indicates the likelihood that a given search model will work in MR. Inbuilt displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians.

Implications of AlphaFold2 for crystallographic phasing by molecular replacement

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. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models.

Structure of the class XI myosin globular tail reveals evolutionary hallmarks for cargo recognition in plants

The plant-specific class XI myosins (MyoXIs) play key roles at the molecular, cellular and tissue levels, engaging diverse adaptor proteins to transport cargoes along actin filaments. To recognize their cargoes, MyoXIs have a C-terminal globular tail domain (GTD) that is evolutionarily related to those of class V myosins (MyoVs) from animals and fungi. Despite recent advances in understanding the functional roles played by MyoXI in plants, the structure of its GTD, and therefore the molecular determinants for cargo selectivity and recognition, remain elusive. In this study, the first crystal structure of a MyoXI GTD, that of MyoXI-K from Arabidopsis thaliana, was elucidated at 2.35 Å resolution using a low-identity and fragment-based phasing approach in ARCIMBOLDO_SHREDDER. The results reveal that both the composition and the length of the α5-α6 loop are distinctive features of MyoXI-K, providing evidence for a structural stabilizing role for this loop, which is otherwise carried out by a molecular zipper in MyoV GTDs. The crystal structure also shows that most of the characterized cargo-binding sites in MyoVs are not conserved in plant MyoXIs, pointing to plant-specific cargo-recognition mechanisms. Notably, the main elements involved in the self-regulation mechanism of MyoVs are conserved in plant MyoXIs, indicating this to be an ancient ancestral trait.

Insights into the molecular determinants of thermal stability in halohydrin dehalogenase HheD2

Halohydrin dehalogenases (HHDHs) are promising enzymes for application in biocatalysis due to their promiscuous epoxide ring-opening activity with various anionic nucleophiles. So far, seven different HHDH subtypes A to G have been reported with subtype D containing the by far largest number of enzymes. Moreover, several characterized members of subtype D have been reported to display outstanding characteristics such as high catalytic activity, broad substrate spectra or remarkable thermal stability. Yet, no structure of a D-type HHDH has been reported to date that could be used to investigate and understand those features on a molecular level. We therefore solved the crystal structure of HheD2 from gamma proteobacterium HTCC2207 at 1.6 Å resolution and used it as a starting point for targeted mutagenesis in combination with molecular dynamics (MD) simulation, in order to study the low thermal stability of HheD2 in comparison with other members of subtype D. This revealed a hydrogen bond between conserved residues Q160 and D198 to be connected with a high catalytic activity of this enzyme. Moreover, a flexible surface region containing two α-helices was identified to impact thermal stability of HheD2. Exchange of this surface region by residues of HheD3 yielded a variant with 10 °C higher melting temperature and reaction temperature optimum. Overall, our results provide important insights into the structure-function relationship of HheD2 and presumably for other D-type HHDHs. DATABASES: Structural data are available in PDB database under the accession number 7B73.

Phasertng: directed acyclic graphs for crystallographic phasing

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.

Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER

Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO, a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Å resolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE. The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.

The use of local structural similarity of distant homologues for crystallographic model building from a molecular-replacement solution

The performance of automated protein model building usually decreases with resolution, mainly owing to the lower information content of the experimental data. This calls for a more elaborate use of the available structural information about macromolecules. Here, a new method is presented that uses structural homologues to improve the quality of protein models automatically constructed using ARP/wARP. The method uses local structural similarity between deposited models and the model being built, and results in longer main-chain fragments that in turn can be more reliably docked to the protein sequence. The application of the homology-based model extension method to the example of a CFA synthase at 2.7 Å resolution resulted in a more complete model with almost all of the residues correctly built and docked to the sequence. The method was also evaluated on 1493 molecular-replacement solutions at a resolution of 4.0 Å and better that were submitted to the ARP/wARP web service for model building. A significant improvement in the completeness and sequence coverage of the built models has been observed.

ALIXE: a phase-combination tool for fragment-based molecular replacement

Fragment-based molecular replacement exploits the use of very accurate yet incomplete search models. In the case of the ARCIMBOLDO programs, consistent phase sets produced from the placement and refinement of fragments with Phaser can be combined in order to increase their signal before proceeding to the step of density modification and autotracing with SHELXE. The program ALIXE compares multiple phase sets, evaluating mean phase differences to determine their common origin, and subsequently produces sets of combined phases that group consistent solutions. In this work, its use on different scenarios of very partial molecular-replacement solutions and its performance after the development of a much-optimized set of algorithms are described. The program is available both standalone and integrated within the ARCIMBOLDO programs. ALIXE has been analysed to identify its rate-limiting steps while exploring the best parameterization to improve its performance and make this software efficient enough to work on modest hardware. The algorithm has been parallelized and redesigned to meet the typical landscape of solutions. Analysis of pairwise correlation between the phase sets has also been explored to test whether this would provide additional insight. ALIXE can be used to exhaustively analyse all partial solutions produced or to complement those already selected for expansion, and also to reduce the number of redundant solutions, which is particularly relevant to the case of coiled coils, or to combine partial solutions from different programs. In each case parallelization and optimization to provide speedup makes its use amenable to typical hardware found in crystallography. ARCIMBOLDO_BORGES and ARCIMBOLDO_SHREDDER now call on ALIXE by default.

ALEPH: a network-oriented approach for the generation of fragment-based libraries and for structure interpretation

The analysis of large structural databases reveals general features and relationships among proteins, providing useful insight. A different approach is required to characterize ubiquitous secondary-structure elements, where flexibility is essential in order to capture small local differences. The ALEPH software is optimized for the analysis and the extraction of small protein folds by relying on their geometry rather than on their sequence. The annotation of the structural variability of a given fold provides valuable information for fragment-based molecular-replacement methods, in which testing alternative model hypotheses can succeed in solving difficult structures when no homology models are available or are successful. ARCIMBOLDO_BORGES combines the use of composite secondary-structure elements as a search model with density modification and tracing to reveal the rest of the structure when both steps are successful. This phasing method relies on general fold libraries describing variations around a given pattern of β-sheets and helices extracted using ALEPH. The program introduces characteristic vectors defined from the main-chain atoms as a way to describe the geometrical properties of the structure. ALEPH encodes structural properties in a graph network, the exploration of which allows secondary-structure annotation, decomposition of a structure into small compact folds, generation of libraries of models representing a variation of a given fold and finally superposition of these folds onto a target structure. These functions are available through a graphical interface designed to interactively show the results of structure manipulation, annotation, fold decomposition, clustering and library generation. ALEPH can produce pictures of the graphs, structures and folds for publication purposes.

SEQUENCE SLIDER: expanding polyalanine fragments for phasing with multiple side-chain hypotheses

Fragment-based molecular-replacement methods can solve a macromolecular structure quasi-ab initio. ARCIMBOLDO, using a common secondary-structure or tertiary-structure template or a library of folds, locates these with Phaser and reveals the rest of the structure by density modification and autotracing in SHELXE. The latter stage is challenging when dealing with diffraction data at lower resolution, low solvent content, high β-sheet composition or situations in which the initial fragments represent a low fraction of the total scattering or where their accuracy is low. SEQUENCE SLIDER aims to overcome these complications by extending the initial polyalanine fragment with side chains in a multisolution framework. Its use is illustrated on test cases and previously unknown structures. The selection and order of fragments to be extended follows the decrease in log-likelihood gain (LLG) calculated with Phaser upon the omission of each single fragment. When the starting substructure is derived from a remote homolog, sequence assignment to fragments is restricted by the original alignment. Otherwise, the secondary-structure prediction is matched to that found in fragments and traces. Sequence hypotheses are trialled in a brute-force approach through side-chain building and refinement. Scoring the refined models through their LLG in Phaser may allow discrimination of the correct sequence or filter the best partial structures for further density modification and autotracing. The default limits for the number of models to pursue are hardware dependent. In its most economic implementation, suitable for a single laptop, the main-chain trace is extended as polyserine rather than trialling models with different sequence assignments, which requires a grid or multicore machine. SEQUENCE SLIDER has been instrumental in solving two novel structures: that of MltC from 2.7 Å resolution data and that of a pneumococcal lipoprotein with 638 residues and 35% solvent content.

Molecular replacement using structure predictions from databases

Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling. Recently, the accuracy of such models has improved significantly as a result of the availability, in many cases, of residue-contact predictions derived from evolutionary covariance analysis. Covariance-assisted ab initio models representing structurally uncharacterized Pfam families are now available on a large scale in databases, potentially representing a valuable and easily accessible supplement to the PDB as a source of search models. Here, the unconventional MR pipeline AMPLE is employed to explore the value of structure predictions in the GREMLIN and PconsFam databases. It was tested whether these deposited predictions, processed in various ways, could solve the structures of PDB entries that were subsequently deposited. The results were encouraging: nine of 27 GREMLIN cases were solved, covering target lengths of 109-355 residues and a resolution range of 1.4-2.9 Å, and with target-model shared sequence identity as low as 20%. The cluster-and-truncate approach in AMPLE proved to be essential for most successes. For the overall lower quality structure predictions in the PconsFam database, remodelling with Rosetta within the AMPLE pipeline proved to be the best approach, generating ensemble search models from single-structure deposits. Finally, it is shown that the AMPLE-obtained search models deriving from GREMLIN deposits are of sufficiently high quality to be selected by the sequence-independent MR pipeline SIMBAD. Overall, the results help to point the way towards the optimal use of the expanding databases of ab initio structure predictions.

Sequence assignment for low-resolution modelling of protein crystal structures

Recent advances in automated protein model building using ARP/wARP are presented. The new methods include machine-learning-enhanced sequence assignment and loop building using a fragment database.

The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for machine-learning-based docking of main-chain fragments to the sequence and for their sequence-independent connection using a dedicated library of protein fragments. The combined use of these new methods noticeably increases sequence coverage and reduces fragmentation of the protein models automatically built with ARP/wARP.

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models

Molecular replacement (MR) has commonly been employed to derive the phase information in protein crystal X-ray diffraction, but its success rate decreases rapidly when the search model is dissimilar to the target. MR-REX has been developed to perform an MR search by replica-exchange Monte Carlo simulations, which enables cooperative rotation and translation searches and simultaneous clash and occupancy optimization. MR-REX was tested on a set of 1303 protein structures of different accuracies and successfully placed 699 structures at positions that have an r.m.s.d. of below 2 Å to the target position, which is 10% higher than was obtained by Phaser. However, cases studies show that many of the models for which Phaser failed and MR-REX succeeded can be solved by Phaser by pruning them and using nondefault parameters. The factors effecting success and the parts of the methodology which lead to success are studied. The results demonstrate a new avenue for molecular replacement which outperforms (and has results that are complementary to) the state-of-the-art MR methods, in particular for distantly homologous proteins.

Exolytic and endolytic turnover of peptidoglycan by lytic transglycosylase Slt of Pseudomonas aeruginosa

β-Lactam antibiotics inhibit cell-wall transpeptidases, preventing the peptidoglycan, the major constituent of the bacterial cell wall, from cross-linking. This causes accumulation of long non-cross-linked strands of peptidoglycan, which leads to bacterial death. Pseudomonas aeruginosa, a nefarious bacterial pathogen, attempts to repair this aberrantly formed peptidoglycan by the function of the lytic transglycosylase Slt. We document in this report that Slt turns over the peptidoglycan by both exolytic and endolytic reactions, which cause glycosidic bond scission from a terminus or in the middle of the peptidoglycan, respectively. These reactions were characterized with complex synthetic peptidoglycan fragments that ranged in size from tetrasaccharides to octasaccharides. The X-ray structure of the wild-type apo Slt revealed it to be a doughnut-shaped protein. In a series of six additional X-ray crystal structures, we provide insights with authentic substrates into how Slt is enabled for catalysis for both the endolytic and exolytic reactions. The substrate for the exolytic reaction binds Slt in a canonical arrangement and reveals how both the glycan chain and the peptide stems are recognized by the Slt. We document that the apo enzyme does not have a fully formed active site for the endolytic reaction. However, binding of the peptidoglycan at the existing subsites within the catalytic domain causes a conformational change in the protein that assembles the surface for binding of a more expansive peptidoglycan between the catalytic domain and an adjacent domain. The complexes of Slt with synthetic peptidoglycan substrates provide an unprecedented snapshot of the endolytic reaction.

Exploiting distant homologues for phasing through the generation of compact fragments, local fold refinement and partial solution combination

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 Å 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 LLG-guided 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.

On the application of the expected log-likelihood gain to decision making in molecular replacement

Molecular-replacement phasing of macromolecular crystal structures is often fast, but if a molecular-replacement solution is not immediately obtained the crystallographer must judge whether to pursue molecular replacement or to attempt experimental phasing as the quickest path to structure solution. The introduction of the expected log-likelihood gain [eLLG; McCoy et al. (2017), Proc. Natl Acad. Sci. USA, 114, 3637-3641] has given the crystallographer a powerful new tool to aid in making this decision. The eLLG is the log-likelihood gain on intensity [LLGI; Read & McCoy (2016), Acta Cryst. D72, 375-387] expected from a correctly placed model. It is calculated as a sum over the reflections of a function dependent on the fraction of the scattering for which the model accounts, the estimated model coordinate error and the measurement errors in the data. It is shown how the eLLG may be used to answer the question `can I solve my structure by molecular replacement?'. However, this is only the most obvious of the applications of the eLLG. It is also discussed how the eLLG may be used to determine the search order and minimal data requirements for obtaining a molecular-replacement solution using a given model, and for decision making in fragment-based molecular replacement, single-atom molecular replacement and likelihood-guided model pruning.

Gyre and gimble: a maximum-likelihood replacement for Patterson correlation refinement

Descriptions are given of the maximum-likelihood gyre method implemented in Phaser for optimizing the orientation and relative position of rigid-body fragments of a model after the orientation of the model has been identified, but before the model has been positioned in the unit cell, and also the related gimble method for the refinement of rigid-body fragments of the model after positioning. Gyre refinement helps to lower the root-mean-square atomic displacements between model and target molecular-replacement solutions for the test case of antibody Fab(26-10) and improves structure solution with ARCIMBOLDO_SHREDDER.

ARCIMBOLDO on coiled coils

ARCIMBOLDO solves the phase problem by combining the location of small model fragments using Phaser with density modification and autotracing using SHELXE. Mainly helical structures constitute favourable cases, which can be solved using polyalanine helical fragments as search models. Nevertheless, the solution of coiled-coil structures is often complicated by their anisotropic diffraction and apparent translational noncrystallographic symmetry. Long, straight helices have internal translational symmetry and their alignment in preferential directions gives rise to systematic overlap of Patterson vectors. This situation has to be differentiated from the translational symmetry relating different monomers. ARCIMBOLDO_LITE has been run on single workstations on a test pool of 150 coiled-coil structures with 15-635 amino acids per asymmetric unit and with diffraction data resolutions of between 0.9 and 3.0 Å. The results have been used to identify and address specific issues when solving this class of structures using ARCIMBOLDO. Features from Phaser v.2.7 onwards are essential to correct anisotropy and produce translation solutions that will pass the packing filters. As the resolution becomes worse than 2.3 Å, the helix direction may be reversed in the placed fragments. Differentiation between true solutions and pseudo-solutions, in which helix fragments were correctly positioned but in a reverse orientation, was found to be problematic at resolutions worse than 2.3 Å. Therefore, after every new fragment-placement round, complete or sparse combinations of helices in alternative directions are generated and evaluated. The final solution is once again probed by helix reversal, refinement and extension. To conclude, density modification and SHELXE autotracing incorporating helical constraints is also exploited to extend the resolution limit in the case of coiled coils and to enhance the identification of correct solutions. This study resulted in a specialized mode within ARCIMBOLDO for the solution of coiled-coil structures, which overrides the resolution limit and can be invoked from the command line (keyword coiled_coil) or ARCIMBOLDO_LITE task interface in CCP4i.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case.

Fragon: rapid high-resolution structure determination from ideal protein fragments

Correctly positioning ideal protein fragments by molecular replacement presents an attractive method for obtaining preliminary phases when no template structure for molecular replacement is available. This has been exploited in several existing pipelines. This paper presents a new pipeline, named Fragon, in which fragments (ideal α-helices or β-strands) are placed using Phaser and the phases calculated from these coordinates are then improved by the density-modification methods provided by ACORN. The reliable scoring algorithm provided by ACORN identifies success. In these cases, the resulting phases are usually of sufficient quality to enable automated model building of the entire structure. Fragon was evaluated against two test sets comprising mixed α/β folds and all-β folds at resolutions between 1.0 and 1.7 Å. Success rates of 61% for the mixed α/β test set and 30% for the all-β test set were achieved. In almost 70% of successful runs, fragment placement and density modification took less than 30 min on relatively modest four-core desktop computers. In all successful runs the best set of phases enabled automated model building with ARP/wARP to complete the structure.

Ensembles generated from crystal structures of single distant homologues solve challenging molecular-replacement cases in AMPLE

Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Although routine in many cases, it becomes more effortful and often impossible when the available experimental structures typically used as search models are only distantly homologous to the target. Nevertheless, with current powerful MR software, relatively small core structures shared between the target and known structure, of 20-40% of the overall structure for example, can succeed as search models where they can be isolated. Manual sculpting of such small structural cores is rarely attempted and is dependent on the crystallographer's expertise and understanding of the protein family in question. Automated search-model editing has previously been performed on the basis of sequence alignment, in order to eliminate, for example, side chains or loops that are not present in the target, or on the basis of structural features (e.g. solvent accessibility) or crystallographic parameters (e.g. B factors). Here, based on recent work demonstrating a correlation between evolutionary conservation and protein rigidity/packing, novel automated ways to derive edited search models from a given distant homologue over a range of sizes are presented. A variety of structure-based metrics, many readily obtained from online webservers, can be fed to the MR pipeline AMPLE to produce search models that succeed with a set of test cases where expertly manually edited comparators, further processed in diverse ways with MrBUMP, fail. Further significant performance gains result when the structure-based distance geometry method CONCOORD is used to generate ensembles from the distant homologue. To our knowledge, this is the first such approach whereby a single structure is meaningfully transformed into an ensemble for the purposes of MR. Additional cases further demonstrate the advantages of the approach. CONCOORD is freely available and computationally inexpensive, so these novel methods offer readily available new routes to solve difficult MR cases.

Acknowledging Errors: Advanced Molecular Replacement with Phaser

Molecular replacement is a method for solving the crystallographic phase problem using an atomic model for the target structure. State-of-the-art methods have moved the field significantly from when it was first envisaged as a method for solving cases of high homology and completeness between a model and target structure. Improvements brought about by application of maximum likelihood statistics mean that various errors in the model and pathologies in the data can be accounted for, so that cases hitherto thought to be intractable are standardly solvable. As a result, molecular replacement phasing now accounts for the lion's share of structures deposited in the Protein Data Bank. However, there will always be cases at the fringes of solvability. I discuss here the approaches that will help tackle challenging molecular replacement cases.

Improving the efficiency of molecular replacement by utilizing a new iterative transform phasing algorithm

An iterative transform method proposed previously for direct phasing of high-solvent-content protein crystals is employed for enhancing the molecular-replacement (MR) algorithm in protein crystallography. Target structures that are resistant to conventional MR due to insufficient similarity between the template and target structures might be tractable with this modified phasing method. Trial calculations involving three different structures are described to test and illustrate the methodology. The relationship of the approach to PHENIX Phaser-MR and MR-Rosetta is discussed.

Using iterative fragment assembly and progressive sequence truncation to facilitate phasing and crystal structure determination of distantly related proteins

Molecular replacement (MR) often requires templates with high homology to solve the phase problem in X-ray crystallography. I-TASSER-MR has been developed to test whether the success rate for structure determination of distant-homology proteins could be improved by a combination of iterative fragmental structure-assembly simulations with progressive sequence truncation designed to trim regions with high variation. The pipeline was tested on two independent protein sets consisting of 61 proteins from CASP8 and 100 high-resolution proteins from the PDB. After excluding homologous templates, I-TASSER generated full-length models with an average TM-score of 0.773, which is 12% higher than the best threading templates. Using these as search models, I-TASSER-MR found correct MR solutions for 95 of 161 targets as judged by having a TFZ of >8 or with the final structure closer to the native than the initial search models. The success rate was 16% higher than when using the best threading templates. I-TASSER-MR was also applied to 14 protein targets from structure genomics centers. Seven of these were successfully solved by I-TASSER-MR. These results confirm that advanced structure assembly and progressive structural editing can significantly improve the success rate of MR for targets with distant homology to proteins of known structure.

An overview of heavy-atom derivatization of protein crystals

Heavy-atom derivatization is one of the oldest techniques for obtaining phase information for protein crystals and, although it is no longer the first choice, it remains a useful technique for obtaining phases for unknown structures and for low-resolution data sets. It is also valuable for confirming the chain trace in low-resolution electron-density maps. This overview provides a summary of the technique and is aimed at first-time users of the method. It includes guidelines on when to use it, which heavy atoms are most likely to work, how to prepare heavy-atom solutions, how to derivatize crystals and how to determine whether a crystal is in fact a derivative.

Combining phase information in reciprocal space for molecular replacement with partial models

ARCIMBOLDO allows ab initio phasing of macromolecular structures below atomic resolution by exploiting the location of small model fragments combined with density modification in a multisolution frame. The model fragments can be either secondary-structure elements predicted from the sequence or tertiary-structure fragments. The latter can be derived from libraries of typical local folds or from related structures, such as a low-homology model that is unsuccessful in molecular replacement. In all ARCIMBOLDO applications, fragments are searched for sequentially. Correct partial solutions obtained after each fragment-search stage but lacking the necessary phasing power can, if combined, succeed. Here, an analysis is presented of the clustering of partial solutions in reciprocal space and of its application to a set of different cases. In practice, the task of combining model fragments from an ARCIMBOLDO run requires their referral to a common origin and is complicated by the presence of correct and incorrect solutions as well as by their not being independent. The F-weighted mean phase difference has been used as a figure of merit. Clustering perfect, non-overlapping fragments dismembered from test structures in polar and nonpolar space groups shows that density modification before determining the relative origin shift enhances its discrimination. In the case of nonpolar space groups, clustering of ARCIMBOLDO solutions from secondary-structure models is feasible. The use of partially overlapping search fragments provides a more favourable circumstance and was assessed on a test case. Applying the devised strategy, a previously unknown structure was solved from clustered correct partial solutions.

ARCIMBOLDO_LITE: single-workstation implementation and use

ARCIMBOLDO solves the phase problem at resolutions of around 2 Å or better through massive combination of small fragments and density modification. For complex structures, this imposes a need for a powerful grid where calculations can be distributed, but for structures with up to 200 amino acids in the asymmetric unit a single workstation may suffice. The use and performance of the single-workstation implementation, ARCIMBOLDO_LITE, on a pool of test structures with 40-120 amino acids and resolutions between 0.54 and 2.2 Å is described. Inbuilt polyalanine helices and iron cofactors are used as search fragments. ARCIMBOLDO_BORGES can also run on a single workstation to solve structures in this test set using precomputed libraries of local folds. The results of this study have been incorporated into an automated, resolution- and hardware-dependent parameterization. ARCIMBOLDO has been thoroughly rewritten and three binaries are now available: ARCIMBOLDO_LITE, ARCIMBOLDO_SHREDDER and ARCIMBOLDO_BORGES. The programs and libraries can be downloaded from http://chango.ibmb.csic.es/ARCIMBOLDO_LITE.

Structure and mechanism of a bacterial host-protein citrullinating virulence factor, Porphyromonas gingivalis peptidylarginine deiminase

Citrullination is a post-translational modification of higher organisms that deiminates arginines in proteins and peptides. It occurs in physiological processes but also pathologies such as multiple sclerosis, fibrosis, Alzheimer’s disease and rheumatoid arthritis (RA). The reaction is catalyzed by peptidylarginine deiminases (PADs), which are found in vertebrates but not in lower organisms. RA has been epidemiologically associated with periodontal disease, whose main infective agent is Porphyromonas gingivalis. Uniquely among microbes, P. gingivalis secretes a PAD, termed PPAD (Porphyromonas peptidylarginine deiminase), which is genetically unrelated to eukaryotic PADs. Here, we studied function of PPAD and its substrate-free, substrate-complex, and substrate-mimic-complex structures. It comprises a flat cylindrical catalytic domain with five-fold α/β-propeller architecture and a C-terminal immunoglobulin-like domain. The PPAD active site is a funnel located on one of the cylinder bases. It accommodates arginines from peptide substrates after major rearrangement of a “Michaelis loop” that closes the cleft. The guanidinium and carboxylate groups of substrates are tightly bound, which explains activity of PPAD against arginines at C-termini but not within peptides. Catalysis is based on a cysteine-histidine-asparagine triad, which is shared with human PAD1-PAD4 and other guanidino-group modifying enzymes. We provide a working mechanism hypothesis based on 18 structure-derived point mutants.

Structure of a 13-fold superhelix (almost) determined from first principles

Nuclear hormone receptors are cytoplasm-based transcription factors that bind a ligand, translate to the nucleus and initiate gene transcription in complex with a co-activator such as TIF2 (transcriptional intermediary factor 2). For structural studies the co-activator is usually mimicked by a peptide of circa 13 residues, which for the largest part forms an α-helix when bound to the receptor. The aim was to co-crystallize the glucocorticoid receptor in complex with a ligand and the TIF2 co-activator peptide. The 1.82 Å resolution diffraction data obtained from the crystal could not be phased by molecular replacement using the known receptor structures. HPLC analysis of the crystals revealed the absence of the receptor and indicated that only the co-activator peptide was present. The self-rotation function displayed 13-fold rotational symmetry, which initiated an exhaustive but unsuccessful molecular-replacement approach using motifs of 13-fold symmetry such as α- and β-barrels in various geometries. The structure was ultimately determined by using a single α-helix and the software ARCIMBOLDO, which assembles fragments placed by PHASER before using them as seeds for density modification model building in SHELXE. Systematic variation of the helix length revealed upper and lower size limits for successful structure determination. A beautiful but unanticipated structure was obtained that forms superhelices with left-handed twist throughout the crystal, stabilized by ligand interactions. Together with the increasing diversity of structural elements in the Protein Data Bank the results from TIF2 confirm the potential of fragment-based molecular replacement to significantly accelerate the phasing step for native diffraction data at around 2 Å resolution.

A fragmentation and reassembly method for ab initio phasing

Ab initio phasing with de novo models has become a viable approach for structural solution from protein crystallographic diffraction data. This approach takes advantage of the known protein sequence information, predicts de novo models and uses them for structure determination by molecular replacement. However, even the current state-of-the-art de novo modelling method has a limit as to the accuracy of the model predicted, which is sometimes insufficient to be used as a template for successful molecular replacement. A fragment-assembly phasing method has been developed that starts from an ensemble of low-accuracy de novo models, disassembles them into fragments, places them independently in the crystallographic unit cell by molecular replacement and then reassembles them into a whole structure that can provide sufficient phase information to enable complete structure determination by automated model building. Tests on ten protein targets showed that the method could solve structures for eight of these targets, although the predicted de novo models cannot be used as templates for successful molecular replacement since the best model for each target is on average more than 4.0 Å away from the native structure. The method has extended the applicability of the ab initio phasing by de novo models approach. The method can be used to solve structures when the best de novo models are still of low accuracy.