To automate or not to automate: this is the question

Continuous Validation Across Macromolecular Structure Determination Process

The overall quality of the experimentally determined structures contained in the PDB is exceptionally high, mainly due to the continuous improvement of model building and structural validation programs. Improving reproducibility on a large scale requires expanding the concept of validation in structural biology and all other disciplines to include a broader framework that encompasses the entire project. A successful approach to science requires diligent attention to detail and a focus on the future. An earnest commitment to data availability and reuse is essential for scientific progress, be that by human minds or artificial intelligence.

Optimal structure determination from sub-optimal diffraction data

Herein we present the newest version of the HKL-3000 system that integrates data collection, data reduction, phasing, model building, refinement, and validation. The system significantly accelerates the process of structure determination and has proven its high value for the determination of very high-quality structures. The heuristic for choosing the best approach for every step of structure determination for various quality samples and diffraction data has been optimized. The latest modifications increase the likelihood of a successful structure determination with challenging data. The HKL-3000 is a successor of HKL and HKL-2000 programs. The use of the HKL family of programs has been reported for over 73,000 PDB deposits, that is, almost 50% of macromolecular structures determined with X-ray diffraction.

State-of-the-Art Data Management: Improving the Reproducibility, Consistency, and Traceability of Structural Biology and in Vitro Biochemical Experiments

Efficient and comprehensive data management is an indispensable component of modern scientific research and requires effective tools for all but the most trivial experiments. The LabDB system developed and used in our laboratory was originally designed to track the progress of a structure determination pipeline in several large National Institutes of Health (NIH) projects. While initially designed for structural biology experiments, its modular nature makes it easily applied in laboratories of various sizes in many experimental fields. Over many years, LabDB has transformed into a sophisticated system integrating a range of biochemical, biophysical, and crystallographic experimental data, which harvests data both directly from laboratory instruments and through human input via a web interface. The core module of the system handles many types of universal laboratory management data, such as laboratory personnel, chemical inventories, storage locations, and custom stock solutions. LabDB also tracks various biochemical experiments, including spectrophotometric and fluorescent assays, thermal shift assays, isothermal titration calorimetry experiments, and more. LabDB has been used to manage data for experiments that resulted in over 1200 deposits to the Protein Data Bank (PDB); the system is currently used by the Center for Structural Genomics of Infectious Diseases (CSGID) and several large laboratories. This chapter also provides examples of data mining analyses and warnings about incomplete and inconsistent experimental data. These features, together with its capabilities for detailed tracking, analysis, and auditing of experimental data, make the described system uniquely suited to inspect potential sources of irreproducibility in life sciences research.

Advances in methods for atomic resolution macromolecular structure determination

Recent technical advances have dramatically increased the power and scope of structural biology. New developments in high-resolution cryo-electron microscopy, serial X-ray crystallography, and electron diffraction have been especially transformative. Here we highlight some of the latest advances and current challenges at the frontiers of atomic resolution methods for elucidating the structures and dynamical properties of macromolecules and their complexes.

Refining the macromolecular model - achieving the best agreement with the data from X-ray diffraction experiment

Refinement of macromolecular X-ray crystal structures involves using complex software with hundreds of different settings. The complexity of underlying concepts and the sheer amount sof instructions may make it difficult for less experienced crystallographers to achieve optimal results in their refinements. This tutorial review offers guidelines for choosing the best settings for the reciprocal-space refinement of macromolecular models and provides practical tips for manual model correction. To help aspiring crystallographers navigate the process, some of the most practically important concepts of protein structure refinement are described. Among the topics covered are the use and purpose of R-free, geometrical restraints, restraints on atomic displacement parameters (ADPs), refinement weights, various parametrizations of ADPs (full anisotropic refinement and TLS), and omit maps. We also give practical tips for manual model correction in Coot, modelling of side-chains with poor or missing density, and ligand identification, fitting, and refinement.

Molstack-Interactive visualization tool for presentation, interpretation, and validation of macromolecules and electron density maps

Our understanding of the world of biomolecular structures is based upon the interpretation of macromolecular models, of which ∼90% are an interpretation of electron density maps. This structural information guides scientific progress and exploration in many biomedical disciplines. The Protein Data Bank's web portals have made these structures available for mass scientific consumption and greatly broaden the scope of information presented in scientific publications. The portals provide numerous quality metrics; however, the portion of the structure that is most vital for interpretation of the function may have the most difficult to interpret electron density and this ambiguity is not reflected by any single metric. The possible consequences of basing research on suboptimal models make it imperative to inspect the agreement of a model with its experimental evidence. Molstack, a web-based interactive publishing platform for structural data, allows users to present density maps and structural models by displaying a collection of maps and models, including different interpretation of one's own data, re-refinements, and corrections of existing structures. Molstack organizes the sharing and dissemination of these structural models along with their experimental evidence as an interactive session. Molstack was designed with three groups of users in mind; researchers can present the evidence of their interpretation, reviewers and readers can independently judge the experimental evidence of the authors' conclusions, and other researchers can present or even publish their new hypotheses in the context of prior results. The server is available at http://molstack.bioreproducibility.org.

Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations

Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/.

Combining 'dry' co-crystallization and in situ diffraction to facilitate ligand screening by X-ray crystallography

X-ray crystallography is an established technique for ligand screening in fragment-based drug-design projects, but the required manual handling steps - soaking crystals with ligand and the subsequent harvesting - are tedious and limit the throughput of the process. Here, an alternative approach is reported: crystallization plates are pre-coated with potential binders prior to protein crystallization and X-ray diffraction is performed directly 'in situ' (or in-plate). Its performance is demonstrated on distinct and relevant therapeutic targets currently being studied for ligand screening by X-ray crystallography using either a bending-magnet beamline or a rotating-anode generator. The possibility of using DMSO stock solutions of the ligands to be coated opens up a route to screening most chemical libraries.

100 Years later: Celebrating the contributions of x-ray crystallography to allergy and clinical immunology

Current knowledge of molecules involved in immunology and allergic disease results from the significant contributions of x-ray crystallography, a discipline that just celebrated its 100th anniversary. The histories of allergens and x-ray crystallography are intimately intertwined. The first enzyme structure to be determined was lysozyme, also known as the chicken food allergen Gal d 4. Crystallography determines the exact 3-dimensional positions of atoms in molecules. Structures of molecular complexes in the disciplines of immunology and allergy have revealed the atoms involved in molecular interactions and mechanisms of disease. These complexes include peptides presented by MHC class II molecules, cytokines bound to their receptors, allergen-antibody complexes, and innate immune receptors with their ligands. The information derived from crystallographic studies provides insights into the function of molecules. Allergen function is one of the determinants of environmental exposure, which is essential for IgE sensitization. Proteolytic activity of allergens or their capacity to bind LPSs can also contribute to allergenicity. The atomic positions define the molecular surface that is accessible to antibodies. In turn, this surface determines antibody specificity and cross-reactivity, which are important factors for the selection of allergen panels used for molecular diagnosis and the interpretation of clinical symptoms. This review celebrates the contributions of x-ray crystallography to clinical immunology and allergy, focusing on new molecular perspectives that influence the diagnosis and treatment of allergic diseases.

Approaches to automated protein crystal harvesting

The harvesting of protein crystals is almost always a necessary step in the determination of a protein structure using X-ray crystallographic techniques. However, protein crystals are usually fragile and susceptible to damage during the harvesting process. For this reason, protein crystal harvesting is the single step that remains entirely dependent on skilled human intervention. Automation has been implemented in the majority of other stages of the structure-determination pipeline, including cloning, expression, purification, crystallization and data collection. The gap in automation between crystallization and data collection results in a bottleneck in throughput and presents unfortunate opportunities for crystal damage. Several automated protein crystal harvesting systems have been developed, including systems utilizing microcapillaries, microtools, microgrippers, acoustic droplet ejection and optical traps. However, these systems have yet to be commonly deployed in the majority of crystallography laboratories owing to a variety of technical and cost-related issues. Automation of protein crystal harvesting remains essential for harnessing the full benefits of fourth-generation synchrotrons, free-electron lasers and microfocus beamlines. Furthermore, automation of protein crystal harvesting offers several benefits when compared with traditional manual approaches, including the ability to harvest microcrystals, improved flash-cooling procedures and increased throughput.

Data management in the modern structural biology and biomedical research environment

Modern high-throughput structural biology laboratories produce vast amounts of raw experimental data. The traditional method of data reduction is very simple-results are summarized in peer-reviewed publications, which are hopefully published in high-impact journals. By their nature, publications include only the most important results derived from experiments that may have been performed over the course of many years. The main content of the published paper is a concise compilation of these data, an interpretation of the experimental results, and a comparison of these results with those obtained by other scientists.Due to an avalanche of structural biology manuscripts submitted to scientific journals, in many recent cases descriptions of experimental methodology (and sometimes even experimental results) are pushed to supplementary materials that are only published online and sometimes may not be reviewed as thoroughly as the main body of a manuscript. Trouble may arise when experimental results are contradicting the results obtained by other scientists, which requires (in the best case) the reexamination of the original raw data or independent repetition of the experiment according to the published description of the experiment. There are reports that a significant fraction of experiments obtained in academic laboratories cannot be repeated in an industrial environment (Begley CG & Ellis LM, Nature 483(7391):531-3, 2012). This is not an indication of scientific fraud but rather reflects the inadequate description of experiments performed on different equipment and on biological samples that were produced with disparate methods. For that reason the goal of a modern data management system is not only the simple replacement of the laboratory notebook by an electronic one but also the creation of a sophisticated, internally consistent, scalable data management system that will combine data obtained by a variety of experiments performed by various individuals on diverse equipment. All data should be stored in a core database that can be used by custom applications to prepare internal reports, statistics, and perform other functions that are specific to the research that is pursued in a particular laboratory.This chapter presents a general overview of the methods of data management and analysis used by structural genomics (SG) programs. In addition to a review of the existing literature on the subject, also presented is experience in the development of two SG data management systems, UniTrack and LabDB. The description is targeted to a general audience, as some technical details have been (or will be) published elsewhere. The focus is on "data management," meaning the process of gathering, organizing, and storing data, but also briefly discussed is "data mining," the process of analysis ideally leading to an understanding of the data. In other words, data mining is the conversion of data into information. Clearly, effective data management is a precondition for any useful data mining. If done properly, gathering details on millions of experiments on thousands of proteins and making them publicly available for analysis-even after the projects themselves have ended-may turn out to be one of the most important benefits of SG programs.

Structural and bioinformatic analysis of the kiwifruit allergen Act d 11, a member of the family of ripening-related proteins

The allergen Act d 11, also known as kirola, is a 17 kDa protein expressed in large amounts in ripe green and yellow-fleshed kiwifruit. Ten percent of all kiwifruit-allergic individuals produce IgE specific for the protein. Using X-ray crystallography, we determined the first three-dimensional structures of Act d 11, produced from both recombinant expression in Escherichia coli and from the natural source (kiwifruit). While Act d 11 is immunologically correlated with the birch pollen allergen Bet v 1 and other members of the pathogenesis-related protein family 10 (PR-10), it has low sequence similarity to PR-10 proteins. By sequence Act d 11 appears instead to belong to the major latex/ripening-related (MLP/RRP) family, but analysis of the crystal structures shows that Act d 11 has a fold very similar to that of Bet v 1 and other PR-10 related allergens regardless of the low sequence identity. The structures of both the natural and recombinant protein include an unidentified ligand, which is relatively small (about 250 Da by mass spectrometry experiments) and most likely contains an aromatic ring. The ligand-binding cavity in Act d 11 is also significantly smaller than those in PR-10 proteins. The binding of the ligand, which we were not able to unambiguously identify, results in conformational changes in the protein that may have physiological and immunological implications. Interestingly, the residue corresponding to Glu45 in Bet v 1 (Glu46), which is important for IgE binding to the birch pollen allergen, is conserved in Act d 11, even though it is not in other allergens with significantly higher sequence identity to Bet v 1. We suggest that the so-called Gly-rich loop (or P-loop), which is conserved in all PR-10 allergens, may be responsible for IgE cross-reactivity between Bet v 1 and Act d 11.

Alternaria alternata allergen Alt a 1: a unique β-barrel protein dimer found exclusively in fungi

BACKGROUND

Alternaria species is one of the most common molds associated with allergic diseases, and 80% of Alternaria species-sensitive patients produce IgE antibodies to a major protein allergen, Alt a 1. The structure and function of Alt a 1 is unknown.

OBJECTIVE

We sought to obtain a high-resolution structure of Alt a 1 using x-ray crystallography and to investigate structural relationships between Alt a 1 and other allergens and proteins reported in the Protein Data Bank.

METHODS

X-ray crystallography was used to determine the structure of Alt a 1 by using a custom-designed set of crystallization conditions. An initial Alt a 1 model was determined by the application of a Ta(6)Br(12)(2+) cluster and single-wavelength anomalous diffraction. Bioinformatic analyses were used to compare the Alt a 1 sequence and structure with that of other proteins.

RESULTS

Alt a 1 is a unique β-barrel comprising 11 β-strands and forms a "butterfly-like" dimer linked by a single disulfide bond with a large (1345 Å(2)) dimer interface. Intramolecular disulfide bonds are conserved among Alt a 1 homologs. Currently, the Alt a 1 structure has no equivalent in the Protein Data Bank. Bioinformatics analyses suggest that the structure is found exclusively in fungi. Four previously reported putative IgE-binding peptides have been located on the Alt a 1 structure.

CONCLUSIONS

Alt a 1 has a unique, dimeric β-barrel structure that appears to define a new protein family with unknown function found exclusively in fungi. The location of IgE antibody-binding epitopes is in agreement with the structural analysis of Alt a 1. The Alt a 1 structure will allow mechanistic structure/function studies and immunologic studies directed toward new forms of immunotherapy for Alternaria species-sensitive allergic patients.

Graphical tools for macromolecular crystallography in PHENIX

A new Python-based graphical user interface for the PHENIX suite of crystallography software is described. This interface unifies the command-line programs and their graphical displays, simplifying the development of new interfaces and avoiding duplication of function. With careful design, graphical interfaces can be displayed automatically, instead of being manually constructed. The resulting package is easily maintained and extended as new programs are added or modified.

Structural characterization of Helicobacter pylori dethiobiotin synthetase reveals differences between family members

Dethiobiotin synthetase (DTBS) is involved in the biosynthesis of biotin in bacteria, fungi, and plants. As humans lack this pathway, DTBS is a promising antimicrobial drug target. We determined structures of DTBS from Helicobacter pylori (hpDTBS) bound with cofactors and a substrate analog, and described its unique characteristics relative to other DTBS proteins. Comparison with bacterial DTBS orthologs revealed considerable structural differences in nucleotide recognition. The C-terminal region of DTBS proteins, which contains two nucleotide-recognition motifs, differs greatly among DTBS proteins from different species. The structure of hpDTBS revealed that this protein is unique and does not contain a C-terminal region containing one of the motifs. The single nucleotide-binding motif in hpDTBS is similar to its counterpart in GTPases; however, isothermal titration calorimetry binding studies showed that hpDTBS has a strong preference for ATP. The structural determinants of ATP specificity were assessed with X-ray crystallographic studies of hpDTBS·ATP and hpDTBS·GTP complexes. The unique mode of nucleotide recognition in hpDTBS makes this protein a good target for H. pylori-specific inhibitors of the biotin synthesis pathway.

Molecular determinants for antibody binding on group 1 house dust mite allergens

House dust mites produce potent allergens, Der p 1 and Der f 1, that cause allergic sensitization and asthma. Der p 1 and Der f 1 are cysteine proteases that elicit IgE responses in 80% of mite-allergic subjects and have proinflammatory properties. Their antigenic structure is unknown. Here, we present crystal structures of natural Der p 1 and Der f 1 in complex with a monoclonal antibody, 4C1, which binds to a unique cross-reactive epitope on both allergens associated with IgE recognition. The 4C1 epitope is formed by almost identical amino acid sequences and contact residues. Mutations of the contact residues abrogate mAb 4C1 binding and reduce IgE antibody binding. These surface-exposed residues are molecular targets that can be exploited for development of recombinant allergen vaccines.

Structural and immunologic characterization of Ara h 1, a major peanut allergen

Allergic reactions to peanuts and tree nuts are major causes of anaphylaxis in the United States. We compare different properties of natural and recombinant versions of Ara h 1, a major peanut allergen, through structural, immunologic, and bioinformatics analyses. Small angle x-ray scattering studies show that natural Ara h 1 forms higher molecular weight aggregates in solution. In contrast, the full-length recombinant protein is partially unfolded and exists as a monomer. The crystal structure of the Ara h 1 core (residues 170-586) shows that the central part of the allergen has a bicupin fold, which is in agreement with our bioinformatics analysis. In its crystalline state, the core region of Ara h 1 forms trimeric assemblies, while in solution the protein exists as higher molecular weight assemblies. This finding reveals that the residues forming the core region of the protein are sufficient for formation of Ara h 1 trimers and higher order oligomers. Natural and recombinant variants of proteins tested in in vitro gastric and duodenal digestion assays show that the natural protein is the most stable form, followed by the recombinant Ara h 1 core fragment and the full-length recombinant protein. Additionally, IgE binding studies reveal that the natural and recombinant allergens have different patterns of interaction with IgE antibodies. The molecular basis of cross-reactivity between vicilin allergens is also elucidated.

The Protein Maker: an automated system for high-throughput parallel purification

The Protein Maker is an automated purification system developed by Emerald BioSystems for high-throughput parallel purification of proteins and antibodies. This instrument allows multiple load, wash and elution buffers to be used in parallel along independent lines for up to 24 individual samples. To demonstrate its utility, its use in the purification of five recombinant PB2 C-terminal domains from various subtypes of the influenza A virus is described. Three of these constructs crystallized and one diffracted X-rays to sufficient resolution for structure determination and deposition in the Protein Data Bank. Methods for screening lysis buffers for a cytochrome P450 from a pathogenic fungus prior to upscaling expression and purification are also described. The Protein Maker has become a valuable asset within the Seattle Structural Genomics Center for Infectious Disease (SSGCID) and hence is a potentially valuable tool for a variety of high-throughput protein-purification applications.

In-plate protein crystallization, in situ ligand soaking and X-ray diffraction

X-ray crystallography is now a recognized technique for ligand screening, especially for fragment-based drug design. However, protein crystal handling is still tedious and limits further automation. An alternative method for the solution of crystal structures of proteins in complex with small ligands is proposed. Crystallization drops are directly exposed to an X-ray beam after cocrystallization or soaking with the desired ligands. The use of dedicated plates in connection with an optimal parametrization of the G-rob robot allows efficient data collection. Three proteins currently under study in our laboratory for ligand screening by X-ray crystallography were used as validation test cases. The protein crystals belonged to different space groups, including a challenging monoclinic case. The resulting diffraction data can lead to clear ligand recognition, including indication of alternating conformations. These results demonstrate a possible method for automation of ligand screening by X-ray crystallography.

X-ray crystallography: Assessment and validation of protein-small molecule complexes for drug discovery

INTRODUCTION: Crystallography is the key initial component for structure-based and fragment-based drug design and can often generate leads that can be developed into high potency drugs. Therefore, huge sums of money are committed based on the outcome of crystallography experiments and their interpretation. AREAS COVERED: This review discusses how to evaluate the correctness of an X-ray structure, focusing on the validation of small molecule-protein complexes. Various types of inaccuracies found within the PDB are identified and the ramifications of these errors are discussed. The reader will gain an understanding of the key parameters that need to be inspected before a structure can be used in drug discovery efforts, as well as an appreciation of the difficulties of correctly interpreting electron density for small molecules. The reader will also be introduced to methods for validating small molecules within the context of a macromolecular structure. EXPERT OPINION: One of the reasons that ligand identification and positioning, within a macromolecular crystal structure, is so difficult is that the quality of small molecules widely varies in the PDB. For this reason, the PDB can not always be considered a reliable repository of structural information pertaining to small molecules, and this makes the derivation of general principles that govern small molecule-protein interactions more difficult.