Interactive comparison and remediation of collections of macromolecular structures.

Often similar structures need to be compared to reveal local differences throughout the entire model or between related copies within the model. Therefore, a program to compare multiple structures and enable correction any differences not supported by the density map was written within the Phenix framework (Adams et al., Acta Cryst 2010; D66:213-221). This program, called Structure Comparison, can also be used for structures with multiple copies of the same protein chain in the asymmetric unit, that is, as a result of non-crystallographic symmetry (NCS). Structure Comparison was designed to interface with Coot(Emsley et al., Acta Cryst 2010; D66:486-501) and PyMOL(DeLano, PyMOL 0.99; 2002) to facilitate comparison of large numbers of related structures. Structure Comparison analyzes collections of protein structures using several metrics, such as the rotamer conformation of equivalent residues, displays the results in tabular form and allows superimposed protein chains and density maps to be quickly inspected and edited (via the tools in Coot) for consistency, completeness and correctness.

Structural and Biophysical Characterization of the Mycobacterium tuberculosis Protein Rv0577, a Protein Associated with Neutral Red Staining of Virulent Tuberculosis Strains and Homologue of the Streptomyces coelicolor Protein KbpA.

Mycobacterium tuberculosis protein Rv0577 is a prominent antigen in tuberculosis patients, the component responsible for neutral red staining of virulent strains of M. tuberculosis, a putative component in a methylglyoxal detoxification pathway, and an agonist of toll-like receptor 2. It also has an amino acid sequence that is 36% identical to that of Streptomyces coelicolor AfsK-binding protein A (KbpA), a component in the complex secondary metabolite pathways in the Streptomyces genus. To gain insight into the biological function of Rv0577 and the family of KpbA kinase regulators, the crystal structure for Rv0577 was determined to a resolution of 1.75 Å, binding properties with neutral red and deoxyadenosine were surveyed, backbone dynamics were measured, and thermal stability was assayed by circular dichroism spectroscopy. The protein is composed of four approximate repeats with a ßαßßß topology arranged radially in consecutive pairs to form two continuous eight-strand ß-sheets capped on both ends with an α-helix. The two ß-sheets intersect in the center at roughly a right angle and form two asymmetric deep "saddles" that may serve to bind ligands. Nuclear magnetic resonance chemical shift perturbation experiments show that neutral red and deoxyadenosine bind to Rv0577. Binding to deoxyadenosine is weaker with an estimated dissociation constants of 4.1 ± 0.3 mM for saddle 1. Heteronuclear steady-state {1H}-15N nuclear Overhauser effect, T1, and T2 values were generally uniform throughout the sequence with only a few modest pockets of differences. Circular dichroism spectroscopy characterization of the thermal stability of Rv0577 indicated irreversible unfolding upon heating with an estimated melting temperature of 56 °C.

RNA Structure Refinement Using the ERRASER-Phenix Pipeline.

The final step of RNA crystallography involves the fitting of coordinates into electron density maps. The large number of backbone atoms in RNA presents a difficult and tedious challenge, particularly when experimental density is poor. The ERRASER-Phenix pipeline can improve an initial set of RNA coordinates automatically based on a physically realistic model of atomic-level RNA interactions. The pipeline couples diffraction-based refinement in Phenix with the Rosetta-based real-space refinement protocol ERRASER (Enumerative Real-Space Refinement ASsisted by Electron density under Rosetta). The combination of ERRASER and Phenix can improve the geometrical quality of RNA crystallographic models while maintaining or improving the fit to the diffraction data (as measured by R free). Here we present a complete tutorial for running ERRASER-Phenix through the Phenix GUI, from the command-line, and via an application in the Rosetta On-line Server that Includes Everyone (ROSIE).

EMRinger: side chain-directed model and map validation for 3D cryo-electron microscopy.

Advances in high-resolution cryo-electron microscopy (cryo-EM) require the development of validation metrics to independently assess map quality and model geometry. We report EMRinger, a tool that assesses the precise fitting of an atomic model into the map during refinement and shows how radiation damage alters scattering from negatively charged amino acids. EMRinger (https://github.com/fraser-lab/EMRinger) will be useful for monitoring progress in resolving and modeling high-resolution features in cryo-EM.

Using support vector machines to improve elemental ion identification in macromolecular crystal structures.

In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific knowledge of metal-binding chemistry and scattering properties and is prone to error. A method has previously been described to identify ions based on manually chosen criteria for a number of elements. Here, the use of support vector machines (SVMs) to automatically classify isolated atoms as either solvent or one of various ions is described. Two data sets of protein crystal structures, one containing manually curated structures deposited with anomalous diffraction data and another with automatically filtered, high-resolution structures, were constructed. On the manually curated data set, an SVM classifier was able to distinguish calcium from manganese, zinc, iron and nickel, as well as all five of these ions from water molecules, with a high degree of accuracy. Additionally, SVMs trained on the automatically curated set of high-resolution structures were able to successfully classify most common elemental ions in an independent validation test set. This method is readily extensible to other elemental ions and can also be used in conjunction with previous methods based on a priori expectations of the chemical environment and X-ray scattering.

Indexing amyloid peptide diffraction from serial femtosecond crystallography: new algorithms for sparse patterns.

Still diffraction patterns from peptide nanocrystals with small unit cells are challenging to index using conventional methods owing to the limited number of spots and the lack of crystal orientation information for individual images. New indexing algorithms have been developed as part of the Computational Crystallography Toolbox (cctbx) to overcome these challenges. Accurate unit-cell information derived from an aggregate data set from thousands of diffraction patterns can be used to determine a crystal orientation matrix for individual images with as few as five reflections. These algorithms are potentially applicable not only to amyloid peptides but also to any set of diffraction patterns with sparse properties, such as low-resolution virus structures or high-throughput screening of still images captured by raster-scanning at synchrotron sources. As a proof of concept for this technique, successful integration of X-ray free-electron laser (XFEL) data to 2.5 Šresolution for the amyloid segment GNNQQNY from the Sup35 yeast prion is presented.

Macromolecular X-ray structure determination using weak, single-wavelength anomalous data.

We describe a likelihood-based method for determining the substructure of anomalously scattering atoms in macromolecular crystals that allows successful structure determination by single-wavelength anomalous diffraction (SAD) X-ray analysis with weak anomalous signal. With the use of partial models and electron density maps in searches for anomalously scattering atoms, testing of alternative values of parameters and parallelized automated model-building, this method has the potential to extend the applicability of the SAD method in challenging cases.

Improved crystal orientation and physical properties from single-shot XFEL stills.

X-ray diffraction patterns from still crystals are inherently difficult to process because the crystal orientation is not uniquely determined by measuring the Bragg spot positions. Only one of the three rotational degrees of freedom is directly coupled to spot positions; the other two rotations move Bragg spots in and out of the reflecting condition but do not change the direction of the diffracted rays. This hinders the ability to recover accurate structure factors from experiments that are dependent on single-shot exposures, such as femtosecond diffract-and-destroy protocols at X-ray free-electron lasers (XFELs). Here, additional methods are introduced to optimally model the diffraction. The best orientation is obtained by requiring, for the brightest observed spots, that each reciprocal-lattice point be placed into the exact reflecting condition implied by Bragg's law with a minimal rotation. This approach reduces the experimental uncertainties in noisy XFEL data, improving the crystallographic R factors and sharpening anomalous differences that are near the level of the noise.

dxtbx: the diffraction experiment toolbox.

Data formats for recording X-ray diffraction data continue to evolve rapidly to accommodate new detector technologies developed in response to more intense light sources. Processing the data from single-crystal X-ray diffraction experiments therefore requires the ability to read, and correctly interpret, image data and metadata from a variety of instruments employing different experimental representations. Tools that have previously been developed to address this problem have been limited either by a lack of extensibility or by inconsistent treatment of image metadata. The dxtbx software package provides a consistent interface to both image data and experimental models, while supporting a completely generic user-extensible approach to reading the data files. The library is written in a mixture of C++ and Python and is distributed as part of the cctbx under an open-source licence at http://cctbx.sourceforge.net.

Taking snapshots of photosynthetic water oxidation using femtosecond X-ray diffraction and spectroscopy.

The dioxygen we breathe is formed by light-induced oxidation of water in photosystem II. O2 formation takes place at a catalytic manganese cluster within milliseconds after the photosystem II reaction centre is excited by three single-turnover flashes. Here we present combined X-ray emission spectra and diffraction data of 2-flash (2F) and 3-flash (3F) photosystem II samples, and of a transient 3F' state (250 µs after the third flash), collected under functional conditions using an X-ray free electron laser. The spectra show that the initial O-O bond formation, coupled to Mn reduction, does not yet occur within 250 µs after the third flash. Diffraction data of all states studied exhibit an anomalous scattering signal from Mn but show no significant structural changes at the present resolution of 4.5 Å. This study represents the initial frames in a molecular movie of the structural changes during the catalytic reaction in photosystem II.

Flexible torsion-angle noncrystallographic symmetry restraints for improved macromolecular structure refinement.

One of the great challenges in refining macromolecular crystal structures is a low data-to-parameter ratio. Historically, knowledge from chemistry has been used to help to improve this ratio. When a macromolecule crystallizes with more than one copy in the asymmetric unit, the noncrystallographic symmetry relationships can be exploited to provide additional restraints when refining the working model. However, although globally similar, NCS-related chains often have local differences. To allow for local differences between NCS-related molecules, flexible torsion-based NCS restraints have been introduced, coupled with intelligent rotamer handling for protein chains, and are available in phenix.refine for refinement of models at all resolutions.

Automated identification of elemental ions in macromolecular crystal structures.

Many macromolecular model-building and refinement programs can automatically place solvent atoms in electron density at moderate-to-high resolution. This process frequently builds water molecules in place of elemental ions, the identification of which must be performed manually. The solvent-picking algorithms in phenix.refine have been extended to build common ions based on an analysis of the chemical environment as well as physical properties such as occupancy, B factor and anomalous scattering. The method is most effective for heavier elements such as calcium and zinc, for which a majority of sites can be placed with few false positives in a diverse test set of structures. At atomic resolution, it is observed that it can also be possible to identify tightly bound sodium and magnesium ions. A number of challenges that contribute to the difficulty of completely automating the process of structure completion are discussed.

Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers.

X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

Ligand placement based on prior structures: the guided ligand-replacement method.

The process of iterative structure-based drug design involves the X-ray crystal structure determination of upwards of 100 ligands with the same general scaffold (i.e. chemotype) complexed with very similar, if not identical, protein targets. In conjunction with insights from computational models and assays, this collection of crystal structures is analyzed to improve potency, to achieve better selectivity and to reduce liabilities such as absorption, distribution, metabolism, excretion and toxicology. Current methods for modeling ligands into electron-density maps typically do not utilize information on how similar ligands bound in related structures. Even if the electron density is of sufficient quality and resolution to allow de novo placement, the process can take considerable time as the size, complexity and torsional degrees of freedom of the ligands increase. A new module, Guided Ligand Replacement (GLR), was developed in Phenix to increase the ease and success rate of ligand placement when prior protein-ligand complexes are available. At the heart of GLR is an algorithm based on graph theory that associates atoms in the target ligand with analogous atoms in the reference ligand. Based on this correspondence, a set of coordinates is generated for the target ligand. GLR is especially useful in two situations: (i) modeling a series of large, flexible, complicated or macrocyclic ligands in successive structures and (ii) modeling ligands as part of a refinement pipeline that can automatically select a reference structure. Even in those cases for which no reference structure is available, if there are multiple copies of the bound ligand per asymmetric unit GLR offers an efficient way to complete the model after the first ligand has been placed. In all of these applications, GLR leverages prior knowledge from earlier structures to facilitate ligand placement in the current structure.

Automating crystallographic structure solution and refinement of protein-ligand complexes.

High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation.

Phaser.MRage: automated molecular replacement.

Phaser.MRage is a molecular-replacement automation framework that implements a full model-generation workflow and provides several layers of model exploration to the user. It is designed to handle a large number of models and can distribute calculations efficiently onto parallel hardware. In addition, phaser.MRage can identify correct solutions and use this information to accelerate the search. Firstly, it can quickly score all alternative models of a component once a correct solution has been found. Secondly, it can perform extensive analysis of identified solutions to find protein assemblies and can employ assembled models for subsequent searches. Thirdly, it is able to use a priori assembly information (derived from, for example, homologues) to speculatively place and score molecules, thereby customizing the search procedure to a certain class of protein molecule (for example, antibodies) and incorporating additional biological information into molecular replacement.

Improved low-resolution crystallographic refinement with Phenix and Rosetta.

Refinement of macromolecular structures against low-resolution crystallographic data is limited by the ability of current methods to converge on a structure with realistic geometry. We developed a low-resolution crystallographic refinement method that combines the Rosetta sampling methodology and energy function with reciprocal-space X-ray refinement in Phenix. On a set of difficult low-resolution cases, the method yielded improved model geometry and lower free R factors than alternate refinement methods.

New Python-based methods for data processing.

Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h(-1)) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in real time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units.

Simultaneous femtosecond X-ray spectroscopy and diffraction of photosystem II at room temperature.

Intense femtosecond x-ray pulses produced at the Linac Coherent Light Source (LCLS) were used for simultaneous x-ray diffraction (XRD) and x-ray emission spectroscopy (XES) of microcrystals of photosystem II (PS II) at room temperature. This method probes the overall protein structure and the electronic structure of the Mn4CaO5 cluster in the oxygen-evolving complex of PS II. XRD data are presented from both the dark state (S1) and the first illuminated state (S2) of PS II. Our simultaneous XRD-XES study shows that the PS II crystals are intact during our measurements at the LCLS, not only with respect to the structure of PS II, but also with regard to the electronic structure of the highly radiation-sensitive Mn4CaO5 cluster, opening new directions for future dynamics studies.