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

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.

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.

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.

Ega3 from the fungal pathogen Aspergillus fumigatus is an endo-α-1,4-galactosaminidase that disrupts microbial biofilms

Aspergillus fumigatus is an opportunistic fungal pathogen that causes both chronic and acute invasive infections. Galactosaminogalactan (GAG) is an integral component of the A. fumigatus biofilm matrix and a key virulence factor. GAG is a heterogeneous linear α-1,4-linked exopolysaccharide of galactose and GalNAc that is partially deacetylated after secretion. A cluster of five co-expressed genes has been linked to GAG biosynthesis and modification. One gene in this cluster, ega3, is annotated as encoding a putative α-1,4-galactosaminidase belonging to glycoside hydrolase family 114 (GH114). Herein, we show that recombinant Ega3 is an active glycoside hydrolase that disrupts GAG-dependent A. fumigatus and Pel polysaccharide-dependent Pseudomonas aeruginosa biofilms at nanomolar concentrations. Using MS and functional assays, we demonstrate that Ega3 is an endo-acting α-1,4-galactosaminidase whose activity depends on the conserved acidic residues, Asp-189 and Glu-247. X-ray crystallographic structural analysis of the apo Ega3 and an Ega3-galactosamine complex, at 1.76 and 2.09 Å resolutions, revealed a modified (β/α)₈-fold with a deep electronegative cleft, which upon ligand binding is capped to form a tunnel. Our structural analysis coupled with in silico docking studies also uncovered the molecular determinants for galactosamine specificity and substrate binding at the -2 to +1 binding subsites. The findings in this study increase the structural and mechanistic understanding of the GH114 family, which has >600 members encoded by plant and opportunistic human pathogens, as well as in industrially used bacteria and fungi.

Structural basis of meiotic chromosome synapsis through SYCP1 self-assembly

Meiotic chromosomes adopt unique structures in which linear arrays of chromatin loops are bound together in homologous chromosome pairs by a supramolecular protein assembly, the synaptonemal complex. This three-dimensional scaffold provides the essential structural framework for genetic exchange by crossing over and subsequent homolog segregation. The core architecture of the synaptonemal complex is provided by SYCP1. Here we report the structure and self-assembly mechanism of human SYCP1 through X-ray crystallographic and biophysical studies. SYCP1 has an obligate tetrameric structure in which an N-terminal four-helical bundle bifurcates into two elongated C-terminal dimeric coiled-coils. This building block assembles into a zipper-like lattice through two self-assembly sites. N-terminal sites undergo cooperative head-to-head assembly in the midline, while C-terminal sites interact back to back on the chromosome axis. Our work reveals the underlying molecular structure of the synaptonemal complex in which SYCP1 self-assembly generates a supramolecular lattice that mediates meiotic chromosome synapsis.

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.

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.

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.