Predicting the performance of automated crystallographic model-building pipelines

Proteins are macromolecules that perform essential biological functions which depend on their three-dimensional structure. Determining this structure involves complex laboratory and computational work. For the computational work, multiple software pipelines have been developed to build models of the protein structure from crystallographic data. Each of these pipelines performs differently depending on the characteristics of the electron-density map received as input. Identifying the best pipeline to use for a protein structure is difficult, as the pipeline performance differs significantly from one protein structure to another. As such, researchers often select pipelines that do not produce the best possible protein models from the available data. Here, a software tool is introduced which predicts key quality measures of the protein structures that a range of pipelines would generate if supplied with a given crystallographic data set. These measures are crystallographic quality-of-fit indicators based on included and withheld observations, and structure completeness. Extensive experiments carried out using over 2500 data sets show that the tool yields accurate predictions for both experimental phasing data sets (at resolutions between 1.2 and 4.0 Å) and molecular-replacement data sets (at resolutions between 1.0 and 3.5 Å). The tool can therefore provide a recommendation to the user concerning the pipelines that should be run in order to proceed most efficiently to a depositable model.

Guidelines for de novo phasing using multiple small-wedge data collection

Intense micro-focus X-ray beamlines available at synchrotron facilities have achieved high-quality data collection even from the microcrystals of membrane proteins. The automatic data collection system developed at SPring-8, named ZOO, has contributed to many structure determinations of membrane proteins using small-wedge synchrotron crystallography (SWSX) datasets. The `small-wedge' (5–20°) datasets are collected from multiple crystals and then merged to obtain the final structure factors. To our knowledge, no systematic investigation on the dose dependence of data accuracy has so far been reported for SWSX, which is between `serial crystallography' and `rotation crystallography'. Thus, herein, we investigated the optimal dose conditions for experimental phasing with SWSX. Phase determination using anomalous scattering signals was found to be more difficult at higher doses. Furthermore, merging more homogeneous datasets grouped by hierarchical clustering with controlled doses mildly reduced the negative factors in data collection, such as `lack of signal' and `radiation damage'. In turn, as more datasets were merged, more probable phases could be obtained across a wider range of doses. Therefore, our findings show that it is essential to choose a lower dose than 10 MGy for de novo structure determination by SWSX. In particular, data collection using a dose of 5 MGy proved to be optimal in balancing the amount of signal available while reducing the amount of damage as much as possible.

Simplified heavy-atom derivatization of protein structures via co-crystallization with the MAD tetragon tetrabromoterephthalic acid

The phase problem is a persistent bottleneck that impedes the structure-determination pipeline and must be solved to obtain atomic resolution crystal structures of macromolecules. Although molecular replacement has become the predominant method of solving the phase problem, many scenarios still exist in which experimental phasing is needed. Here, a proof-of-concept study is presented that shows the efficacy of using tetrabromoterephthalic acid (B4C) as an experimental phasing compound. Incorporating B4C into the crystal lattice using co-crystallization, the crystal structure of hen egg-white lysozyme was solved using MAD phasing. The strong anomalous signal generated by its four Br atoms coupled with its compatibility with commonly used crystallization reagents render B4C an effective experimental phasing compound that can be used to overcome the phase problem.

SHELIXIR: automation of experimental phasing procedures using SHELXC/D/E

The program SHELIXIR represents a simple and efficient tool for routine phase-problem solution using data for experimental phasing by the single-wavelength anomalous dispersion, multiwavelength anomalous dispersion, single isomorphous replacement with anomalous scattering and radiation-damage-induced phasing methods. As indicated in its name, all calculation procedures are performed with the SHELXC/D/E program package. SHELIXIR provides screening for alternative space groups, optimal solvent content, and high- and low-resolution limits. The procedures of SHELXE are parallelized to minimize the computational time. The automation and parallelization of such procedures are suitable for phasing at synchrotron beamlines directly or for finding the optimal parameters for further data processing. A simple graphical interface is designed to make use easier and to increase efficiency during beam time.

Affinity and Structural Analysis of the U1A RNA Recognition Motif with Engineered Methionines to Improve Experimental Phasing

RNA plays a central role in all organisms and can fold into complex structures to orchestrate function. Visualization of such structures often requires crystallization, which can be a bottleneck in the structure-determination process. To promote crystallization, an RNA-recognition motif (RRM) of the U1A spliceosomal protein has been co-opted as a crystallization module. Specifically, the U1-snRNA hairpin II (hpII) single-stranded loop recognized by U1A can be transplanted into an RNA target to promote crystal contacts and to attain phase information via molecular replacement or anomalous diffraction methods using selenomethionine. Herein, we produced the F37M/F77M mutant of U1A to augment the phasing capability of this powerful crystallization module. Selenomethionine-substituted U1A(F37M/F77M) retains high affinity for hpII (KD of 59.7 ± 11.4 nM). The 2.20 Å resolution crystal structure reveals that the mutated sidechains make new S-π interactions in the hydrophobic core and are useful for single-wavelength anomalous diffraction. Crystals were also attained of U1A(F37M/F77M) in complex with a bacterial preQ1-II riboswitch. The F34M/F37M/F77M mutant was introduced similarly into a lab-evolved U1A variant (TBP6.9) that recognizes the internal bulged loop of HIV-1 TAR RNA. We envision that this short RNA sequence can be placed into non-essential duplex regions to promote crystallization and phasing of target RNAs. We show that selenomethionine-substituted TBP6.9(F34M/F37M/F77M) binds a TAR variant wherein the apical loop was replaced with a GNRA tetraloop (KD of 69.8 ± 2.9 nM), laying the groundwork for use of TBP6.9(F34M/F37M/F77M) as a crystallization module. These new tools are available to the research community.

Using a partial atomic model from medium-resolution cryo-EM to solve a large crystal structure

Medium-resolution cryo-electron microscopy maps, in particular when they include a significant number of α-helices, may allow the building of partial models that are useful for molecular-replacement searches in large crystallographic structures when the structures of homologs are not available and experimental phasing has failed. Here, as an example, the solution of the structure of a bacteriophage portal using a partial 30% model built into a 7.8 Å resolution cryo-EM map is shown. Inspection of the self-rotation function allowed the correct oligomerization state to be determined, and density-modification procedures using rotation matrices and a mask based on the cryo-EM structure were critical for solving the structure. A workflow is described that may be applicable to similar cases and this strategy is compared with direct use of the cryo-EM map for molecular replacement.

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.

The copper(II)-binding tripeptide GHK, a valuable crystallization and phasing tag for macromolecular crystallography

The growth of diffraction-quality crystals and experimental phasing remain two of the main bottlenecks in protein crystallography. Here, the high-affinity copper(II)-binding tripeptide GHK was fused to the N-terminus of a GFP variant and an MBP-FG peptide fusion. The GHK tag promoted crystallization, with various residues (His, Asp, His/Pro) from symmetry molecules completing the copper(II) square-pyramidal coordination sphere. Rapid structure determination by copper SAD phasing could be achieved, even at a very low Bijvoet ratio or after significant radiation damage. When collecting highly redundant data at a wavelength close to the copper absorption edge, residual S-atom positions could also be located in log-likelihood-gradient maps and used to improve the phases. The GHK copper SAD method provides a convenient way of both crystallizing and phasing macromolecular structures, and will complement the current trend towards native sulfur SAD and MR-SAD phasing.

Experimental phasing with vanadium and application to nucleotide-binding membrane proteins

The structure determination of soluble and membrane proteins can be hindered by the crystallographic phase problem, especially in the absence of a suitable homologous structure. Experimental phasing is the method of choice for novel structures; however, it often requires heavy-atom derivatization, which can be difficult and time-consuming. Here, a novel and rapid method to obtain experimental phases for protein structure determination by vanadium phasing is reported. Vanadate is a transition-state mimic of phosphoryl-transfer reactions and it has the advantage of binding specifically to the active site of numerous enzymes catalyzing this reaction. The applicability of vanadium phasing has been validated by determining the structures of three different protein–vanadium complexes, two of which are integral membrane proteins: the rabbit sarcoplasmic reticulum Ca2+-ATPase, the antibacterial peptide ATP-binding cassette transporter McjD from Escherichia coli and the soluble enzyme RNAse A from Bos taurus. Vanadium phasing was successful even at low resolution and despite severe anisotropy in the data. This method is principally applicable to a large number of proteins, representing six of the seven Enzyme Commission classes. It relies exclusively on the specific chemistry of the protein and it does not require any modifications, making it a very powerful addition to the phasing toolkit. In addition to the phasing power of this technique, the protein–vanadium complexes also provide detailed insights into the reaction mechanisms of the studied proteins.