20 years of crystal hits: progress and promise in ultrahigh-throughput crystallization screening

Diffraction-based structural methods contribute a large fraction of the biomolecular structural models available, providing a critical understanding of macromolecular architecture. These methods require crystallization of the target molecule, which remains a primary bottleneck in crystal-based structure determination. The National High-Throughput Crystallization Center at Hauptman-Woodward Medical Research Institute has focused on overcoming obstacles to crystallization through a combination of robotics-enabled high-throughput screening and advanced imaging to increase the success of finding crystallization conditions. This paper will describe the lessons learned from over 20 years of operation of our high-throughput crystallization services. The current experimental pipelines, instrumentation, imaging capabilities and software for image viewing and crystal scoring are detailed. New developments in the field and opportunities for further improvements in biomolecular crystallization are reflected on.

From Protein Design to the Energy Landscape of a Cold Unfolding Protein

Understanding protein folding is crucial for protein sciences. The conformational spaces and energy landscapes of cold (unfolded) protein states, as well as the associated transitions, are hardly explored. Furthermore, it is not known how structure relates to the cooperativity of cold transitions, if cold and heat unfolded states are thermodynamically similar, and if cold states play important roles for protein function. We created the cold unfolding 4-helix bundle DCUB1 with a de novo designed bipartite hydrophilic/hydrophobic core featuring a hydrogen bond network which extends across the bundle in order to study the relative importance of hydrophobic versus hydrophilic protein-water interactions for cold unfolding. Structural and thermodynamic characterization resulted in the discovery of a complex energy landscape for cold transitions, while the heat unfolded state is a random coil. Below ∼0 °C, the core of DCUB1 disintegrates in a largely cooperative manner, while a near-native helical content is retained. The resulting cold core-unfolded state is compact and features extensive internal dynamics. Below -5 °C, two additional cold transitions are seen, that is, (i) the formation of a water-mediated, compact, and highly dynamic dimer, and (ii) the onset of cold helix unfolding decoupled from cold core unfolding. Our results suggest that cold unfolding is initiated by the intrusion of water into the hydrophilic core network and that cooperativity can be tuned by varying the number of core hydrogen bond networks. Protein design has proven to be invaluable to explore the energy landscapes of cold states and to robustly test related theories.

A SAXS-based approach to rationally evaluate radical scavengers - toward eliminating radiation damage in solution and crystallographic studies

X-ray-based techniques are a powerful tool in structural biology but the radiation-induced chemistry that results can be detrimental and may mask an accurate structural understanding. In the crystallographic case, cryocooling has been employed as a successful mitigation strategy but also has its limitations including the trapping of non-biological structural states. Crystallographic and solution studies performed at physiological temperatures can reveal otherwise hidden but relevant conformations, but are limited by their increased susceptibility to radiation damage. In this case, chemical additives that scavenge the species generated by radiation can mitigate damage but are not always successful and the mechanisms are often unclear. Using a protein designed to undergo a large-scale structural change from breakage of a disulfide bond, radiation damage can be monitored with small-angle X-ray scattering. Using this, we have quantitatively evaluated how three scavengers commonly used in crystallographic experiments - sodium nitrate, cysteine, and ascorbic acid - perform in solution at 10°C. Sodium nitrate was the most effective scavenger and completely inhibited fragmentation of the disulfide bond at a lower concentration (500 µM) compared with cysteine (∼5 mM) while ascorbic acid performed best at 5 mM but could only reduce fragmentation by ∼75% after a total accumulated dose of 792 Gy. The relative effectiveness of each scavenger matches their reported affinities for solvated electrons. Saturating concentrations of each scavenger shifted fragmentation from first order to a zeroth-order process, perhaps indicating the direct contribution of photoabsorption. The SAXS-based method can detect damage at X-ray doses far lower than those accessible crystallographically, thereby providing a detailed picture of scavenger processes. The solution results are also in close agreement with what is known about scavenger performance and mechanism in a crystallographic setting and suggest that a link can be made between the damage phenomenon in the two scenarios. Therefore, our engineered approach might provide a platform for more systematic and comprehensive screening of radioprotectants that can directly inform mitigation strategies for both solution and crystallographic experiments, while also clarifying fundamental radiation damage mechanisms.

Near-physiological-temperature serial crystallography reveals conformations of SARS-CoV-2 main protease active site for improved drug repurposing

The COVID-19 pandemic has resulted in 198 million reported infections and more than 4 million deaths as of July 2021 (covid19.who.int). Research to identify effective therapies for COVID-19 includes: (1) designing a vaccine as future protection; (2) de novo drug discovery; and (3) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determine two apo structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease at ambient temperature by serial femtosecond X-ray crystallography. We employ detailed molecular simulations of selected known main protease inhibitors with the structures and compare binding modes and energies. The combined structural and molecular modeling studies not only reveal the dynamics of small molecules targeting the main protease but also provide invaluable opportunities for drug repurposing and structure-based drug design strategies against SARS-CoV-2.

Biological networks across scales

Many biological systems across scales of size and complexity exhibit a time-varying complex network structure that emerges and self-organizes as a result of interactions with the environment. Network interactions optimize some intrinsic cost functions that are unknown and involve for example energy efficiency, robustness, resilience, and frailty. A wide range of networks exist in biology, from gene regulatory networks important for organismal development, protein interaction networks that govern physiology and metabolism, and neural networks that store and convey information to networks of microbes that form microbiomes within hosts, animal contact networks that underlie social systems, and networks of populations on the landscape connected by migration. Increasing availability of extensive (big) data is amplifying our ability to quantify biological networks. Similarly, theoretical methods that describe network structure and dynamics are being developed. Beyond static networks representing snapshots of biological systems, collections of longitudinal data series can help either at defining and characterizing network dynamics over time or analyzing the dynamics constrained to networked architectures. Moreover, due to interactions with the environment and other biological systems, a biological network may not be fully observable. Also, subnetworks may emerge and disappear as a result of the need for the biological system to cope with for example invaders or new information flows. The confluence of these developments renders tractable the question of how the structure of biological networks predicts and controls network dynamics. In particular, there may be structural features that result in homeostatic networks with specific higher-order statistics (e.g., multifractal spectrum), which maintain stability over time through robustness and/or resilience to perturbation. Alternative, plastic networks may respond to perturbation by (adaptive to catastrophic) shifts in structure. Here, we explore the opportunity for discovering universal laws connecting the structure of biological networks with their function, positioning them on the spectrum of time-evolving network structure, i.e. dynamics of networks, from highly stable to exquisitely sensitive to perturbation. If such general laws exist, they could transform our ability to predict the response of biological systems to perturbations-an increasingly urgent priority in the face of anthropogenic changes to the environment that affect life across the gamut of organizational scales.

Structural biology in the time of COVID-19: perspectives on methods and milestones

The global COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has wreaked unprecedented havoc on global society, in terms of a huge loss of life and burden of morbidity, economic upheaval and social disruption. Yet the sheer magnitude and uniqueness of this event has also spawned a massive mobilization of effort in the scientific community to investigate the virus, to develop therapeutics and vaccines, and to understand the public health impacts. Structural biology has been at the center of these efforts, and so it is advantageous to take an opportunity to reflect on the status of structural science vis-à-vis its role in the fight against COVID-19, to register the unprecedented response and to contemplate the role of structural biology in addressing future outbreak threats. As the one-year anniversary of the World Health Organization declaration that COVID-19 is a pandemic has just passed, over 1000 structures of SARS-CoV-2 biomolecules have been deposited in the Worldwide Protein Data Bank (PDB). It is rare to obtain a snapshot of such intense effort in the structural biology arena and is of special interest as the 50th anniversary of the PDB is celebrated in 2021. It is additionally timely as it overlaps with a period that has been termed the 'resolution revolution' in cryoelectron microscopy (CryoEM). CryoEM has recently become capable of producing biomolecular structures at similar resolutions to those traditionally associated with macromolecular X-ray crystallo-graphy. Examining SARS-CoV-2 protein structures that have been deposited in the PDB since the virus was first identified allows a unique window into the power of structural biology and a snapshot of the advantages of the different techniques available, as well as insight into the complementarity of the structural methods.

SAXS studies of X-ray induced disulfide bond damage: Engineering high-resolution insight from a low-resolution technique

A significant problem in biological X-ray crystallography is the radiation chemistry caused by the incident X-ray beam. This produces both global and site-specific damage. Site specific damage can misdirect the biological interpretation of the structural models produced. Cryo-cooling crystals has been successful in mitigating damage but not eliminating it altogether; however, cryo-cooling can be difficult in some cases and has also been shown to limit functionally relevant protein conformations. The doses used for X-ray crystallography are typically in the kilo-gray to mega-gray range. While disulfide bonds are among the most significantly affected species in proteins in the crystalline state at both cryogenic and higher temperatures, there is limited information on their response to low X-ray doses in solution, the details of which might inform biomedical applications of X-rays. In this work we engineered a protein that dimerizes through a susceptible disulfide bond to relate the radiation damage processes seen in cryo-cooled crystals to those closer to physiologic conditions. This approach enables a low-resolution technique, small angle X-ray scattering (SAXS), to detect and monitor a residue specific process. A dose dependent fragmentation of the engineered protein was seen that can be explained by a dimer to monomer transition through disulfide bond cleavage. This supports the crystallographically derived mechanism and demonstrates that results obtained crystallographically can be usefully extrapolated to physiologic conditions. Fragmentation was influenced by pH and the conformation of the dimer, providing information on mechanism and pointing to future routes for investigation and potential mitigation. The novel engineered protein approach to generate a large-scale change through a site-specific interaction represents a promising tool for advancing radiation damage studies under solution conditions.

Structural insights into conformational switching in latency-associated peptide between transforming growth factor β-1 bound and unbound states

Transforming growth factor β-1 (TGFβ-1) is a secreted signalling protein that directs many cellular processes and is an attractive target for the treatment of several diseases. The primary endogenous activity regulatory mechanism for TGFβ-1 is sequestration by its pro-peptide, latency-associated peptide (LAP), which sterically prohibits receptor binding by caging TGFβ-1. As such, recombinant LAP is promising as a protein-based therapeutic for modulating TGFβ-1 activity; however, the mechanism of binding is incompletely understood. Comparison of the crystal structure of unbound LAP (solved here to 3.5 Å resolution) with that of the bound complex shows that LAP is in a more open and extended conformation when unbound to TGFβ-1. Analysis suggests a mechanism of binding TGFβ-1 through a large-scale conformational change that includes contraction of the inter-monomer interface and caging by the 'straight-jacket' domain that may occur in partnership through a loop-to-helix transition in the core jelly-roll fold. This conformational change does not appear to include a repositioning of the integrin-binding motif as previously proposed. X-ray scattering-based modelling supports this mechanism and reveals possible orientations and ensembles in solution. Although native LAP is heavily glycosylated, solution scattering experiments show that the overall folding and flexibility of unbound LAP are not influenced by glycan modification. The combination of crystallography, solution scattering and biochemical experiments reported here provide insight into the mechanism of LAP sequestration of TGFβ-1 that is of fundamental importance for therapeutic development.

High-Throughput PIXE as an Essential Quantitative Assay for Accurate Metalloprotein Structural Analysis: Development and Application

Metalloproteins comprise over one-third of proteins, with approximately half of all enzymes requiring metal to function. Accurate identification of these metal atoms and their environment is a prerequisite to understanding biological mechanism. Using ion beam analysis through particle induced X-ray emission (PIXE), we have quantitatively identified the metal atoms in 30 previously structurally characterized proteins using minimal sample volume and a high-throughput approach. Over half of these metals had been misidentified in the deposited structural models. Some of the PIXE detected metals not seen in the models were explainable as artifacts from promiscuous crystallization reagents. For others, using the correct metal improved the structural models. For multinuclear sites, anomalous diffraction signals enabled the positioning of the correct metals to reveal previously obscured biological information. PIXE is insensitive to the chemical environment, but coupled with experimental diffraction data deposited alongside the structural model it enables validation and potential remediation of metalloprotein models, improving structural and, more importantly, mechanistic knowledge.

Structural consequences of transforming growth factor beta-1 activation from near-therapeutic X-ray doses

Dissociation of transforming growth factor beta-1 (TGFβ-1) from the inhibitory protein latency-associated peptide (LAP) can occur from low doses of X-ray irradiation of the LAP-TGFβ-1 complex, resulting in the activation of TGFβ-1, and can have health-related consequences. Using the tools and knowledge developed in the study of radiation damage in the crystallographic setting, small-angle X-ray scattering (SAXS) and complementary techniques suggest an activation process that is initiated but not driven by the initial X-ray exposure. LAP is revealed to be extended when not bound to TGFβ-1 and has a different structural conformation compared to the bound state. These studies pave the way for the structural understanding of systems impacted at therapeutic X-ray doses and show the potential impact of radiation damage studies beyond their original intent.

Structural knowledge or X-ray damage? A case study on xylose isomerase illustrating both

Xylose isomerase (XI) is an industrially important metalloprotein studied for decades. Its reaction mechanism has been postulated to involve movement of the catalytic metal cofactor to several different conformations. Here, a dose-dependent approach was used to investigate the radiation damage effects on XI and their potential influence on the reaction mechanism interpreted from the X-ray derived structures. Radiation damage is still one of the major challenges for X-ray diffraction experiments and causes both global and site-specific damage. In this study, consecutive high-resolution data sets from a single XI crystal from the same wedge were collected at 100 K and the progression of radiation damage was tracked over increasing dose (0.13-3.88 MGy). The catalytic metal and its surrounding amino acid environment experience a build-up of free radicals, and the results show radiation-damage-induced structural perturbations ranging from an absolute metal positional shift to specific residue motions in the active site. The apparent metal movement is an artefact of global damage and the resulting unit-cell expansion, but residue motion appears to be driven by the dose. Understanding and identifying radiation-induced damage is an important factor in accurately interpreting the biological conclusions being drawn.

Protein and RNA dynamical fingerprinting

Protein structural vibrations impact biology by steering the structure to functional intermediate states; enhancing tunneling events; and optimizing energy transfer. Strong water absorption and a broad continuous vibrational density of states have prevented optical identification of these vibrations. Recently spectroscopic signatures that change with functional state were measured using anisotropic terahertz microscopy. The technique however has complex sample positioning requirements and long measurement times, limiting access for the biomolecular community. Here we demonstrate that a simplified system increases spectroscopic structure to dynamically fingerprint biomacromolecules with a factor of 6 reduction in data acquisition time. Using this technique, polarization varying anisotropy terahertz microscopy, we show sensitivity to inhibitor binding and unique vibrational spectra for several proteins and an RNA G-quadruplex. The technique’s sensitivity to anisotropic absorbance and birefringence provides rapid assessment of macromolecular dynamics that impact biology.

The characterization of biomacromolecule structural vibrations has been impeded by a broad continuous vibrational density of states obscuring molecule specific vibrations. A terahertz microscopy system using polarization control produces signatures to dynamically fingerprint proteins and a RNA G-quadruplex.

Classification of crystallization outcomes using deep convolutional neural networks

The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups. Here, state-of-the-art machine learning algorithms are trained and tested on different parts of this data set. We find that more than 94% of the test images can be correctly labeled, irrespective of their experimental origin. Because crystal recognition is key to high-density screening and the systematic analysis of crystallization experiments, this approach opens the door to both industrial and fundamental research applications.

Moving in the Right Direction: Protein Vibrations Steering Function

Nearly all protein functions require structural change, such as enzymes clamping onto substrates, and ion channels opening and closing. These motions are a target for possible new therapies; however, the control mechanisms are under debate. Calculations have indicated protein vibrations enable structural change. However, previous measurements found these vibrations only weakly depend on the functional state. By using the novel technique of anisotropic terahertz microscopy, we find that there is a dramatic change to the vibrational directionality with inhibitor binding to lysozyme, whereas the vibrational energy distribution, as measured by neutron inelastic scattering, is only slightly altered. The anisotropic terahertz measurements provide unique access to the directionality of the intramolecular vibrations, and immediately resolve the inconsistency between calculations and previous measurements, which were only sensitive to the energy distribution. The biological importance of the vibrational directions versus the energy distribution is revealed by our calculations comparing wild-type lysozyme with a higher catalytic rate double deletion mutant. The vibrational energy distribution is identical, but the more efficient mutant shows an obvious reorientation of motions. These results show that it is essential to characterize the directionality of motion to understand and control protein dynamics to optimize or inhibit function.

The use of haptic interfaces and web services in crystallography: an application for a 'screen to beam' interface

Haptic interfaces have become common in consumer electronics. They enable easy interaction and information entry without the use of a mouse or keyboard. The work presented here illustrates the application of a haptic interface to crystallization screening in order to provide a natural means for visualizing and selecting results. By linking this to a cloud-based database and web-based application program interface, the same application shifts the approach from 'point and click' to 'touch and share', where results can be selected, annotated and discussed collaboratively. In the crystallographic application, given a suitable crystallization plate, beamline and robotic end effector, the resulting information can be used to close the loop between screening and X-ray analysis, allowing a direct and efficient 'screen to beam' approach. The application is not limited to the area of crystallization screening; 'touch and share' can be used by any information-rich scientific analysis and geographically distributed collaboration.

The structure of the PanD/PanZ protein complex reveals negative feedback regulation of pantothenate biosynthesis by coenzyme A

Coenzyme A (CoA) is an ubiquitous and essential cofactor, synthesized from the precursor pantothenate. Vitamin biosynthetic pathways are normally tightly regulated, including the pathway from pantothenate to CoA. However, no regulation of pantothenate biosynthesis has been identified. We have recently described an additional component in the pantothenate biosynthetic pathway, PanZ, which promotes the activation of the zymogen, PanD, to form aspartate α-decarboxylase (ADC) in a CoA-dependent manner. Here we report the structure of PanZ in complex with PanD, which reveals the structural basis for the CoA dependence of this interaction and activation. In addition, we show that PanZ acts as a CoA-dependent inhibitor of ADC catalysis. This inhibitory effect can effectively regulate the biosynthetic pathway to pantothenate, and thereby also regulate CoA biosynthesis. This represents a previously unobserved mode of metabolic regulation whereby a cofactor-utilizing protein negatively regulates the biosynthesis of the same cofactor.

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Structure of the PanD-PanZ.AcCoA complex is reported at a resolution of 1.6 Å

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Binding of AcCoA to PanZ is required to form the PanZ/PanD interface

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PanZ.AcCoA activates PanD via selection of a reactive conformation of PanD

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PanZ.AcCoA inhibits the activated enzyme, regulating pantothenate biosynthesis

Computational crystallization

Crystallization is a key step in macromolecular structure determination by crystallography. While a robust theoretical treatment of the process is available, due to the complexity of the system, the experimental process is still largely one of trial and error. In this article, efforts in the field are discussed together with a theoretical underpinning using a solubility phase diagram. Prior knowledge has been used to develop tools that computationally predict the crystallization outcome and define mutational approaches that enhance the likelihood of crystallization. For the most part these tools are based on binary outcomes (crystal or no crystal), and the full information contained in an assembly of crystallization screening experiments is lost. The potential of this additional information is illustrated by examples where new biological knowledge can be obtained and where a target can be sub-categorized to predict which class of reagents provides the crystallization driving force. Computational analysis of crystallization requires complete and correctly formatted data. While massive crystallization screening efforts are under way, the data available from many of these studies are sparse. The potential for this data and the steps needed to realize this potential are discussed.

Optical measurements of long-range protein vibrations

Protein biological function depends on structural flexibility and change. From cellular communication through membrane ion channels to oxygen uptake and delivery by haemoglobin, structural changes are critical. It has been suggested that vibrations that extend through the protein play a crucial role in controlling these structural changes. While nature may utilize such long-range vibrations for optimization of biological processes, bench-top characterization of these extended structural motions for engineered biochemistry has been elusive. Here we show the first optical observation of long-range protein vibrational modes. This is achieved by orientation-sensitive terahertz near-field microscopy measurements of chicken egg white lysozyme single crystals. Underdamped modes are found to exist for frequencies >10 cm(-1). The existence of these persisting motions indicates that damping and intermode coupling are weaker than previously assumed. The methodology developed permits protein engineering based on dynamical network optimization.

The detection and subsequent volume optimization of biological nanocrystals

Identifying and then optimizing initial crystallization conditions is a prerequisite for macromolecular structure determination by crystallography. Improved technologies enable data collection on crystals that are difficult if not impossible to detect using visible imaging. The application of second-order nonlinear imaging of chiral crystals and ultraviolet two-photon excited fluorescence detection is shown to be applicable in a high-throughput manner to rapidly verify the presence of nanocrystals in crystallization screening conditions. It is noted that the nanocrystals are rarely seen without also producing microcrystals from other chemical conditions. A crystal volume optimization method is described and associated with a phase diagram for crystallization.

A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta

Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.

The accurate assessment of small-angle X-ray scattering data

A set of quantitative techniques is suggested for assessing SAXS data quality. These are applied in the form of a script, SAXStats, to a test set of 27 proteins, showing that these techniques are more sensitive than manual assessment of data quality.

Small-angle X-ray scattering (SAXS) has grown in popularity in recent times with the advent of bright synchrotron X-ray sources, powerful computational resources and algorithms enabling the calculation of increasingly complex models. However, the lack of standardized data-quality metrics presents difficulties for the growing user community in accurately assessing the quality of experimental SAXS data. Here, a series of metrics to quantitatively describe SAXS data in an objective manner using statistical evaluations are defined. These metrics are applied to identify the effects of radiation damage, concentration dependence and interparticle interactions on SAXS data from a set of 27 previously described targets for which high-resolution structures have been determined via X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The studies show that these metrics are sufficient to characterize SAXS data quality on a small sample set with statistical rigor and sensitivity similar to or better than manual analysis. The development of data-quality analysis strategies such as these initial efforts is needed to enable the accurate and unbiased assessment of SAXS data quality.

Identifying, studying and making good use of macromolecular crystals

As technology advances, the crystal volume that can be used to collect useful X-ray diffraction data decreases. The technologies available to detect and study growing crystals beyond the optical resolution limit and methods to successfully place the crystal into the X-ray beam are discussed.

Structural biology has contributed tremendous knowledge to the understanding of life on the molecular scale. The Protein Data Bank, a depository of this structural knowledge, currently contains over 100 000 protein structures, with the majority stemming from X-ray crystallography. As the name might suggest, crystallography requires crystals. As detectors become more sensitive and X-ray sources more intense, the notion of a crystal is gradually changing from one large enough to embellish expensive jewellery to objects that have external dimensions of the order of the wavelength of visible light. Identifying these crystals is a prerequisite to their study. This paper discusses developments in identifying these crystals during crystallization screening and distinguishing them from other potential outcomes. The practical aspects of ensuring that once a crystal is identified it can then be positioned in the X-ray beam for data collection are also addressed.

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

Crystallization screening: the influence of history on current practice

While crystallization historically predates crystallography, it is a critical step for the crystallographic process. The rich history of crystallization and how that history influences current practices is described. The tremendous impact of crystallization screens on the field is discussed.

Comparing chemistry to outcome: the development of a chemical distance metric, coupled with clustering and hierarchal visualization applied to macromolecular crystallography

Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails) is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192) overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CD_coeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the potential applications related to crystallography appear promising and the distance coefficient, clustering, and hierarchal visualization of results undoubtedly have applications in wider fields.

A new view on crystal harvesting

X-ray crystallography typically requires the mounting of crystals, which can make the sample difficult to manipulate when it is small and the microscope objective is close to the crystallization plate. By simply moving the objective to the bottom of a clear crystallization plate (inverting the normal view), crystals were able to be manipulated and harvested from wells having a 0.9 mm diameter and 5.0 mm depth. The mounting system enabled the structural solution of the 187 amino acid N-terminal domain of Saccharomyces cerevisiae glutaminyl-tRNA synthetase from crystals that appeared during high-throughput screening but proved recalcitrant to scale-up and optimization. While not a general mounting solution, the simple expedient of removing the objective lens from the area where manipulation and harvesting occur greatly facilitates the manual, or even automated, process.

Neutron structure of the cyclic glucose-bound xylose isomerase E186Q mutant

Ketol-isomerases catalyze the reversible isomerization between aldoses and ketoses. D-Xylose isomerase carries out the first reaction in the catabolism of D-xylose, but is also able to convert D-glucose to D-fructose. The first step of the reaction is an enzyme-catalyzed ring opening of the cyclic substrate. The active-site amino-acid acid/base pair involved in ring opening has long been investigated and several models have been proposed. Here, the structure of the xylose isomerase E186Q mutant with cyclic glucose bound at the active site, refined against joint X-ray and neutron diffraction data, is reported. Detailed analysis of the hydrogen-bond networks at the active site of the enzyme suggests that His54, which is doubly protonated, is poised to protonate the glucose O5 position, while Lys289, which is neutral, promotes deprotonation of the glucose O1H hydroxyl groupviaan activated water molecule. The structure also reveals an extended hydrogen-bonding network that connects the conserved residues Lys289 and Lys183 through three structurally conserved water molecules and residue 186, which is a glutamic acid to glutamine mutation.

Insights into the mechanism of X-ray-induced disulfide-bond cleavage in lysozyme crystals based on EPR, optical absorption and X-ray diffraction studies

Electron paramagnetic resonance (EPR) and online UV–visible absorption microspectrophotometry with X-ray crystallography have been used in a complementary manner to follow X-ray-induced disulfide-bond cleavage, to confirm a multi-track radiation-damage process and to develop a model of that process.

Electron paramagnetic resonance (EPR) and online UV–visible absorption microspectrophotometry with X-ray crystallography have been used in a complementary manner to follow X-ray-induced disulfide-bond cleavage. Online UV–visible spectroscopy showed that upon X-irradiation, disulfide radicalization appeared to saturate at an absorbed dose of approximately 0.5–0.8 MGy, in contrast to the saturating dose of ∼0.2 MGy observed using EPR at much lower dose rates. The observations suggest that a multi-track model involving product formation owing to the interaction of two separate tracks is a valid model for radiation damage in protein crystals. The saturation levels are remarkably consistent given the widely different experimental parameters and the range of total absorbed doses studied. The results indicate that even at the lowest doses used for structural investigations disulfide bonds are already radicalized. Multi-track considerations offer the first step in a comprehensive model of radiation damage that could potentially lead to a combined computational and experimental approach to identifying when damage is likely to be present, to quantitate it and to provide the ability to recover the native unperturbed structure.

The structure of yeast glutaminyl-tRNA synthetase and modeling of its interaction with tRNA

Eukaryotic glutaminyl-tRNA synthetase (GlnRS) contains an appended N-terminal domain (NTD) whose precise function is unknown. Although GlnRS structures from two prokaryotic species are known, no eukaryotic GlnRS structure has been reported. Here we present the first crystallographic structure of yeast GlnRS, finding that the structure of the C-terminal domain is highly similar to Escherichia coli GlnRS but that 214 residues, including the NTD, are crystallographically disordered. We present a model of the full-length enzyme in solution, using the structures of the C-terminal domain, and the isolated NTD, with small-angle X-ray scattering data of the full-length molecule. We proceed to model the enzyme bound to tRNA, using the crystallographic structures of GatCAB and GlnRS-tRNA complex from bacteria. We contrast the tRNA-bound model with the tRNA-free solution state and perform molecular dynamics on the full-length GlnRS-tRNA complex, which suggests that tRNA binding involves the motion of a conserved hinge in the NTD.

On the need for an international effort to capture, share and use crystallization screening data

Development of an ontology for the description of crystallization experiments and results is proposed.

When crystallization screening is conducted many outcomes are observed but typically the only trial recorded in the literature is the condition that yielded the crystal(s) used for subsequent diffraction studies. The initial hit that was optimized and the results of all the other trials are lost. These missing results contain information that would be useful for an improved general understanding of crystallization. This paper provides a report of a crystallization data exchange (XDX) workshop organized by several international large-scale crystallization screening laboratories to discuss how this information may be captured and utilized. A group that administers a significant fraction of the world’s crystallization screening results was convened, together with chemical and structural data informaticians and computational scientists who specialize in creating and analysing large disparate data sets. The development of a crystallization ontology for the crystallization community was proposed. This paper (by the attendees of the workshop) provides the thoughts and rationale leading to this conclusion. This is brought to the attention of the wider audience of crystallographers so that they are aware of these early efforts and can contribute to the process going forward.

Structural conservation of an ancient tRNA sensor in eukaryotic glutaminyl-tRNA synthetase

In all organisms, aminoacyl tRNA synthetases covalently attach amino acids to their cognate tRNAs. Many eukaryotic tRNA synthetases have acquired appended domains, whose origin, structure and function are poorly understood. The N-terminal appended domain (NTD) of glutaminyl-tRNA synthetase (GlnRS) is intriguing since GlnRS is primarily a eukaryotic enzyme, whereas in other kingdoms Gln-tRNA^Gln is primarily synthesized by first forming Glu-tRNA^Gln, followed by conversion to Gln-tRNA^Gln by a tRNA-dependent amidotransferase. We report a functional and structural analysis of the NTD of Saccharomyces cerevisiae GlnRS, Gln4. Yeast mutants lacking the NTD exhibit growth defects, and Gln4 lacking the NTD has reduced complementarity for tRNA^Gln and glutamine. The 187-amino acid Gln4 NTD, crystallized and solved at 2.3 Å resolution, consists of two subdomains, each exhibiting an extraordinary structural resemblance to adjacent tRNA specificity-determining domains in the GatB subunit of the GatCAB amidotransferase, which forms Gln-tRNA^Gln. These subdomains are connected by an apparent hinge comprised of conserved residues. Mutation of these amino acids produces Gln4 variants with reduced affinity for tRNA^Gln, consistent with a hinge-closing mechanism proposed for GatB recognition of tRNA. Our results suggest a possible origin and function of the NTD that would link the phylogenetically diverse mechanisms of Gln-tRNA^Gln synthesis.

Small angle X-ray scattering as a complementary tool for high-throughput structural studies

Structural crystallography and nuclear magnetic resonance (NMR) spectroscopy are the predominant techniques for understanding the biological world on a molecular level. Crystallography is constrained by the ability to form a crystal that diffracts well and NMR is constrained to smaller proteins. Although powerful techniques, they leave many soluble, purified structurally uncharacterized protein samples. Small angle X-ray scattering (SAXS) is a solution technique that provides data on the size and multiple conformations of a sample, and can be used to reconstruct a low-resolution molecular envelope of a macromolecule. In this study, SAXS has been used in a high-throughput manner on a subset of 28 proteins, where structural information is available from crystallographic and/or NMR techniques. These crystallographic and NMR structures were used to validate the accuracy of molecular envelopes reconstructed from SAXS data on a statistical level, to compare and highlight complementary structural information that SAXS provides, and to leverage biological information derived by crystallographers and spectroscopists from their structures. All the ab initio molecular envelopes calculated from the SAXS data agree well with the available structural information. SAXS is a powerful albeit low-resolution technique that can provide additional structural information in a high-throughput and complementary manner to improve the functional interpretation of high-resolution structures.

Lessons from high-throughput protein crystallization screening: 10 years of practical experience

INTRODUCTION

X-ray crystallography provides the majority of our structural biological knowledge at a molecular level and, in terms of pharmaceutical design, is a valuable tool to accelerate discovery. It is the premier technique in the field, but its usefulness is significantly limited by the need to grow well-diffracting crystals. It is for this reason that high-throughput crystallization has become a key technology that has matured over the past 10 years through the field of structural genomics. Areas covered : The authors describe their experiences in high-throughput crystallization screening in the context of structural genomics and the general biomedical community. They focus on the lessons learnt from the operation of a high-throughput crystallization-screening laboratory, which to date has screened over 12,500 biological macromolecules. They also describe the approaches taken to maximize the success while minimizing the effort. Through this, the authors hope that the reader will gain an insight into the efficient design of a laboratory and protocols to accomplish high-throughput crystallization on a single-, multiuser laboratory or industrial scale. Expert opinion : High-throughput crystallization screening is readily available but, despite the power of the crystallographic technique, getting crystals is still not a solved problem. High-throughput approaches can help when used skillfully; however, they still require human input in the detailed analysis and interpretation of results to be more successful.

What's in a drop? Correlating observations and outcomes to guide macromolecular crystallization experiments

Observations of crystallization experiments are classified as specific outcomes and integrated through a phase diagram to visualize solubility and thereby direct subsequent experiments. Specific examples are taken from our high-throughput crystallization laboratory which provided a broad scope of data from 20 million crystallization experiments on 12,500 different biological macromolecules. The methods and rationale are broadly and generally applicable in any crystallization laboratory. Through a combination of incomplete factorial sampling of crystallization cocktails, standard outcome classifications, visualization of outcomes as they relate chemically and application of a simple phase diagram approach we demonstrate how to logically design subsequent crystallization experiments.

Crystal cookery - using high-throughput technologies and the grocery store as a teaching tool

Crystallography is a multidisciplinary field that links divergent areas of mathematics, science and engineering to provide knowledge of life on an atomic scale. Crystal growth, a key component of the field, is an ideal vehicle for education. Crystallization has been used with a 'grocery store chemistry' approach and linked to high-throughput remote-access screening technologies. This approach provides an educational opportunity that can effectively teach the scientific method, readily accommodate different levels of educational experience, and reach any student with access to a grocery store, a post office and the internet. This paper describes the formation of the program through the students who helped develop and prototype the procedures. A summary is presented of the analysis and preliminary results and a description given of how the program could be linked with other aspects of crystallography. This approach has the potential to bridge the gap between students in remote locations and with limited funding, and access to scientific resources, providing students with an international-level research experience.

The application and use of chemical space mapping to interpret crystallization screening results

Macromolecular crystallization screening is an empirical process. It often begins by setting up experiments with a number of chemically diverse cocktails designed to sample chemical space known to promote crystallization. Where a potential crystal is seen a refined screen is set up, optimizing around that condition. By using an incomplete factorial sampling of chemical space to formulate the cocktails and presenting the results graphically, it is possible to readily identify trends relevant to crystallization, coarsely sample the phase diagram and help guide the optimization process. In this paper, chemical space mapping is applied to both single macromolecules and to a diverse set of macromolecules in order to illustrate how visual information is more readily understood and assimilated than the same information presented textually.

Establishing a training set through the visual analysis of crystallization trials. Part I: approximately 150,000 images

As part of a training set for automated image analysis, ∼150 000 images of crystallization experiments from 96 diverse macromolecules have been visually classified within seven categories. Outcomes and trends are analyzed.

Structural crystallography aims to provide a three-dimensional representation of macromolecules. Many parts of the multistep process to produce the three-dimensional structural model have been automated, especially through various structural genomics projects. A key step is the production of crystals for diffraction. The target macromolecule is combined with a large and chemically diverse set of cocktails with some leading ideally, but infrequently, to crystallization. A variety of outcomes will be observed during these screening experiments that typically require human interpretation for classification. Human interpretation is neither scalable nor objective, highlighting the need to develop an automatic computer-based image classification. As a first step towards automated image classification, 147 456 images representing crystallization experiments from 96 different macromolecular samples were manually classified. Each image was classified by three experts into seven predefined categories or their combinations. The resulting data where all three observers are in agreement provides one component of a truth set for the development and rigorous testing of automated image-classification systems and provides information about the chemical cocktails used for crystallization. In this paper, the details of this study are presented.