High-throughput Structure Determination Research Articles

Cell-free protein crystallization for nanocrystal structure determination

In-cell protein crystallization (ICPC) has been investigated as a technique to support the advancement of structural biology because it does not require protein purification and a complicated crystallization process. However, only a few protein structures have been reported because these crystals formed incidentally in living cells and are insufficient in size and quality for structure analysis. Here, we have developed a cell-free protein crystallization (CFPC) method, which involves direct protein crystallization using cell-free protein synthesis. We have succeeded in crystallization and structure determination of nano-sized polyhedra crystal (PhC) at a high resolution of 1.80 Å. Furthermore, nanocrystals were synthesized at a reaction scale of only 20 μL using the dialysis method, enabling structural analysis at a resolution of 1.95 Å. To further demonstrate the potential of CFPC, we attempted to determine the structure of crystalline inclusion protein A (CipA), whose structure had not yet been determined. We added chemical reagents as a twinning inhibitor to the CFPC solution, which enabled us to determine the structure of CipA at 2.11 Å resolution. This technology greatly expands the high-throughput structure determination method of unstable, low-yield, fusion, and substrate-biding proteins that have been difficult to analyze with conventional methods.

New tools for automated cryo-EM single-particle analysis in RELION-4.0.

We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a variable-metric gradient descent algorithm with adaptive moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on 12 publicly available cryo-EM data sets.

TranSPHIRE: automated and feedback-optimized on-the-fly processing for cryo-EM

Single particle cryo-EM requires full automation to allow high-throughput structure determination. Although software packages exist where parts of the cryo-EM pipeline are automated, a complete solution that offers reliable on-the-fly processing, resulting in high-resolution structures, does not exist. Here we present TranSPHIRE: A software package for fully-automated processing of cryo-EM datasets during data acquisition. TranSPHIRE transfers data from the microscope, automatically applies the common pre-processing steps, picks particles, performs 2D clustering, and 3D refinement parallel to image recording. Importantly, TranSPHIRE introduces a machine learning-based feedback loop to re-train its picking model to adapt to any given data set live during processing. This elegant approach enables TranSPHIRE to process data more effectively, producing high-quality particle stacks. TranSPHIRE collects and displays all metrics and microscope settings to allow users to quickly evaluate data during acquisition. TranSPHIRE can run on a single work station and also includes the automated processing of filaments.

Tidy up cryo-EM sample grids with 3D printed tools

Cryo-EM technology has developed to the point of high-throughput structure determination of biological macromolecules embedded in vitreous ice. Nonetheless, challenging targets need extensive sample screening, often of many cryo-EM sample grids prepared under various conditions. We have designed and made tools for manipulating sample grids in storage cases. These tools are made of a plastic fiber using a wide-use 3D printer, a fused deposition modeling type, and polished under acetone gas. A grid case stacker organizes many frozen-hydrated cryo-EM grids and the stackers can be piled up inside a standard 50 mL centrifuge tube. We have also introduced tools that facilitate handling of grid cases under liquid nitrogen and a stocker of the grid retainers contained in a CRYO ARM electron microscope. Blueprints of the tools named CryoGridTools are available from a GitHub site.

Microfluidic protein isolation and sample preparation for high-resolution cryo-EM

High-resolution structural information is essential to understand protein function. Protein-structure determination needs a considerable amount of protein, which can be challenging to produce, often involving harsh and lengthy procedures. In contrast, the several thousand to a few million protein particles required for structure determination by cryogenic electron microscopy (cryo-EM) can be provided by miniaturized systems. Here, we present a microfluidic method for the rapid isolation of a target protein and its direct preparation for cryo-EM. Less than 1 μL of cell lysate is required as starting material to solve the atomic structure of the untagged, endogenous human 20S proteasome. Our work paves the way for high-throughput structure determination of proteins from minimal amounts of cell lysate and opens more opportunities for the isolation of sensitive, endogenous protein complexes.

The expanding toolkit for structural biology: synchrotrons, X-ray lasers and cryoEM.

Structural biology continues to benefit from an expanding toolkit, which is helping to gain unprecedented insight into the assembly and organization of multi-protein machineries, enzyme mechanisms and ligand/inhibitor binding. The combination of results from X-ray free-electron lasers (XFELs), modern synchrotron crystallographic beamlines and cryo-electron microscopy (cryoEM) is proving to be particularly powerful. The highly brilliant undulator beamlines at modern synchrotron facilities have empowered the crystallographic revolution of high-throughput structure determination at high resolution. The brilliance of the X-rays at these crystallographic beamlines has enabled this to be achieved using microcrystals, but at the expense of an increased absorbed X-ray dose and a consequent vulnerability to radiation-induced changes. The advent of serial femtosecond crystallography (SFX) with X-ray free-electron lasers provides a new opportunity in which damage-free structures can be obtained from much smaller crystals (2 µm) and more complex macromolecules, including membrane proteins and multi-protein complexes. For redox enzymes, SFX provides a unique opportunity by providing damage-free structures at both cryogenic and ambient temperatures. The promise of being able to visualize macromolecular structures and complexes at high resolution without the need for crystals using X-rays has remained a dream, but recent technological advancements in cryoEM have made this come true and hardly a month goes by when the structure of a new/novel macromolecular assembly is not revealed. The uniqueness of cryoEM in providing structural information for multi-protein complexes, particularly membrane proteins, has been demonstrated by examples such as respirasomes. The synergistic use of cryoEM and crystallography in lead-compound optimization is highlighted by the example of the visualization of antimalarial compounds in cytochrome bc 1. In this short review, using some recent examples including our own work, we share the excitement of these powerful structural biology methods.

Ewald: an extended wide-angle Laue diffractometer for the second target station of the Spallation Neutron Source.

Visualizing hydrogen atoms in biological materials is one of the biggest remaining challenges in biophysical analysis. While X-ray techniques have unrivaled capacity for high-throughput structure determination, neutron diffraction is uniquely sensitive to hydrogen atom positions in crystals of biological materials and can provide a more complete picture of the atomic and electronic structures of biological macromolecules. This information can be essential in providing predictive understanding and engineering control of key biological processes, for example, in catalysis, ligand binding and light harvesting, and to guide bioengineering of enzymes and drug design. One very common and large capability gap for all neutron atomic resolution single-crystal diffractometers is the weak flux of available neutron beams, which results in limited signal-to-noise ratios giving a requirement for sample volumes of at least 0.1 mm3. The ability to operate on crystals an order of magnitude smaller (0.01 mm3) will open up new and more complex systems to studies with neutrons which will help in our understanding of enzyme mechanisms and enable us to improve drugs against multi resistant bacteria. With this is mind, an extended wide-angle Laue diffractometer, 'Ewald', has been designed, which can collect data using crystal volumes below 0.01 mm3.

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

NMR in structural genomics to increase structural coverage of the protein universe: Delivered by Prof. Kurt Wüthrich on 7 July 2013 at the 38th FEBS Congress in St. Petersburg, Russia.

For more than a decade, the Joint Center for Structural Genomics (JCSG; www.jcsg.org) worked toward increased three-dimensional structure coverage of the protein universe. This coordinated quest was one of the main goals of the four high-throughput (HT) structure determination centers of the Protein Structure Initiative (PSI; www.nigms.nih.gov/Research/specificareas/PSI). To achieve the goals of the PSI, the JCSG made use of the complementarity of structure determination by X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy to increase and diversify the range of targets entering the HT structure determination pipeline. The overall strategy, for both techniques, was to determine atomic resolution structures for representatives of large protein families, as defined by the Pfam database, which had no structural coverage and could make significant contributions to biological and biomedical research. Furthermore, the experimental structures could be leveraged by homology modeling to further expand the structural coverage of the protein universe and increase biological insights. Here, we describe what could be achieved by this structural genomics approach, using as an illustration the contributions from 20 NMR structure determinations out of a total of 98 JCSG NMR structures, which were selected because they are the first three-dimensional structure representations of the respective Pfam protein families. The information from this small sample is representative for the overall results from crystal and NMR structure determination in the JCSG. There are five new folds, which were classified as domains of unknown functions (DUF), three of the proteins could be functionally annotated based on three-dimensional structure similarity with previously characterized proteins, and 12 proteins showed only limited similarity with previous deposits in the Protein Data Bank (PDB) and were classified as DUFs.

The impact of structural genomics: the first quindecennial.

The period 2000-2015 brought the advent of high-throughput approaches to protein structure determination. With the overall funding on the order of $2 billion (in 2010 dollars), the structural genomics (SG) consortia established worldwide have developed pipelines for target selection, protein production, sample preparation, crystallization, and structure determination by X-ray crystallography and NMR. These efforts resulted in the determination of over 13,500 protein structures, mostly from unique protein families, and increased the structural coverage of the expanding protein universe. SG programs contributed over 4400 publications to the scientific literature. The NIH-funded Protein Structure Initiatives alone have produced over 2000 scientific publications, which to date have attracted more than 93,000 citations. Software and database developments that were necessary to handle high-throughput structure determination workflows have led to structures of better quality and improved integrity of the associated data. Organized and accessible data have a positive impact on the reproducibility of scientific experiments. Most of the experimental data generated by the SG centers are freely available to the community and has been utilized by scientists in various fields of research. SG projects have created, improved, streamlined, and validated many protocols for protein production and crystallization, data collection, and functional analysis, significantly benefiting biological and biomedical research.

Local structure based method for prediction of the biochemical function of proteins: Applications to glycoside hydrolases

Thousands of protein structures of unknown or uncertain function have been reported as a result of high-throughput structure determination techniques developed by Structural Genomics (SG) projects. However, many of the putative functional assignments of these SG proteins in the Protein Data Bank (PDB) are incorrect. While high-throughput biochemical screening techniques have provided valuable functional information for limited sets of SG proteins, the biochemical functions for most SG proteins are still unknown or uncertain. Therefore, computational methods for the reliable prediction of protein function from structure can add tremendous value to the existing SG data. In this article, we show how computational methods may be used to predict the function of SG proteins, using examples from the six-hairpin glycosidase (6-HG) and the concanavalin A-like lectin/glucanase (CAL/G) superfamilies. Using a set of predicted functional residues, obtained from computed electrostatic and chemical properties for each protein structure, it is shown that these superfamilies may be sorted into functional families according to biochemical function. Within these superfamilies, a total of 18 SG proteins were analyzed according to their predicted, local functional sites: 13 from the 6-HG superfamily, five from the CAL/G superfamily. Within the 6-HG superfamily, an uncharacterized protein BACOVA_03626 from Bacteroides ovatus (PDB 3ON6) and a hypothetical protein BT3781 from Bacteroides thetaiotaomicron (PDB 2P0V) are shown to have very strong active site matches with exo-α-1,6-mannosidases, thus likely possessing this function. Also in this superfamily, it is shown that protein BH0842, a putative glycoside hydrolase from Bacillus halodurans (PDB 2RDY), has a predicted active site that matches well with a known α-l-galactosidase. In the CAL/G superfamily, an uncharacterized glycosyl hydrolase family 16 protein from Mycobacterium smegmatis (PDB 3RQ0) is shown to have local structural similarity at the predicted active site with the known members of the GH16 family, with the closest match to the endoglucanase subfamily. The method discussed herein can predict whether an SG protein is correctly or incorrectly annotated and can sometimes provide a reliable functional annotation. Examples of application of the method across folds, comparing active sites between two proteins of different structural folds, are also given.

Possibilities for serial femtosecond crystallography sample delivery at future light sources.

Serial femtosecond crystallography (SFX) uses X-ray pulses from free-electron laser (FEL) sources that can outrun radiation damage and thereby overcome long-standing limits in the structure determination of macromolecular crystals. Intense X-ray FEL pulses of sufficiently short duration allow the collection of damage-free data at room temperature and give the opportunity to study irreversible time-resolved events. SFX may open the way to determine the structure of biological molecules that fail to crystallize readily into large well-diffracting crystals. Taking advantage of FELs with high pulse repetition rates could lead to short measurement times of just minutes. Automated delivery of sample suspensions for SFX experiments could potentially give rise to a much higher rate of obtaining complete measurements than at today's third generation synchrotron radiation facilities, as no crystal alignment or complex robotic motions are required. This capability will also open up extensive time-resolved structural studies. New challenges arise from the resulting high rate of data collection, and in providing reliable sample delivery. Various developments for fully automated high-throughput SFX experiments are being considered for evaluation, including new implementations for a reliable yet flexible sample environment setup. Here, we review the different methods developed so far that best achieve sample delivery for X-ray FEL experiments and present some considerations towards the goal of high-throughput structure determination with X-ray FELs.

Structural Genomics Support for Infectious Disease Drug Design.

Structural Genomics Support for Infectious Disease Drug Design.

Application of in situ diffraction in high-throughput structure determination platforms.

Macromolecular crystallography (MX) is the most powerful technique available to structural biologists to visualize in atomic detail the macromolecular machinery of the cell. Since the emergence of structural genomics initiatives, significant advances have been made in all key steps of the structure determination process. In particular, third-generation synchrotron sources and the application of highly automated approaches to data acquisition and analysis at these facilities have been the major factors in the rate of increase of macromolecular structures determined annually. A plethora of tools are now available to users of synchrotron beamlines to enable rapid and efficient evaluation of samples, collection of the best data, and in favorable cases structure solution in near real time. Here, we provide a short overview of the emerging use of collecting X-ray diffraction data directly from the crystallization experiment. These in situ experiments are now routinely available to users at a number of synchrotron MX beamlines. A practical guide to the use of the method on the MX suite of beamlines at Diamond Light Source is given.

GPU-based acceleration of an RNA tertiary structure prediction algorithm

Experimental techniques such as X-ray crystallography and nuclear magnetic resonance have been useful for the accurate determination of RNA tertiary structures. However, high-throughput structure determination using such methods often becomes difficult, due to the need for a large quantity of pure samples. Computational techniques for the prediction of RNA tertiary structures are thus becoming increasingly popular. Most of the existing prediction algorithms are computationally intensive, and there is a clear need for acceleration. In this paper, we propose a parallelization methodology for the fragment assembly of RNA (FARNA) algorithm, one of the most effective methods for computational prediction of RNA tertiary structure. The proposed parallelization scheme exploits multi-core CPUs and GPUs in harmony to maximize their utilization. We tested our approach with a number of RNA sequences and confirmed that it allows the time required for structure prediction to be significantly reduced. With respect to the baseline architecture equipped with a single CPU core, we achieved a speedup of up to approximately 24×(roughly 4× by multi-core CPUs and 20× by GPUs). Compared with a quad-core CPU setup, the proposed approach delivers an additional 12× speedup by utilizing GPU devices. Given that most PCs these days have a multi-core CPU and a GPU card, our methodology will be very helpful for accelerating algorithms in a cost-effective manner.

Structure of a Novel Winged-Helix Like Domain from Human NFRKB Protein

The human nuclear factor related to kappa-B-binding protein (NFRKB) is a 1299-residue protein that is a component of the metazoan INO80 complex involved in chromatin remodeling, transcription regulation, DNA replication and DNA repair. Although full length NFRKB is predicted to be around 65% disordered, comparative sequence analysis identified several potentially structured sections in the N-terminal region of the protein. These regions were targeted for crystallographic studies, and the structure of one of these regions spanning residues 370–495 was determined using the JCSG high-throughput structure determination pipeline. The structure reveals a novel, mostly helical domain reminiscent of the winged-helix fold typically involved in DNA binding. However, further analysis shows that this domain does not bind DNA, suggesting it may belong to a small group of winged-helix domains involved in protein-protein interactions.

Structural Biology of Post-translational Modifications of Proteins

A majority of proteins encoded in genomes of limited size are post-translationally diversified by covalent modifications such as glycosylation and ubiquitination. Although recent advances in structural proteomics have enabled high-throughput structure determination of proteins, structural analyses of post-translationally modified proteins remain challenging because of the lack of appropriate determination methods. Therefore, we developed methodologies for characterizing the post-translational modifications of proteins from the structural viewpoint, focusing especially on glycosylation and ubiquitination. For instance, we established a systematic method for structural glycomics to address broader issues, including glycosylation profiling and 3D structure analyses of glycoproteins. Our stable-isotope-assisted NMR techniques in conjunction with X-ray crystallographic approach provide valuable information at the atomic level on conformations, dynamics, and interactions of glycoproteins such as antibody and proteins involved in the ubiquitin-proteasome system. These studies provide the structural basis for improved efficacy of therapeutic antibodies on defucosylation of their Fc glycans and mechanistic insights into ubiquitination reactions in glycoprotein-fate determination in cells. These approaches will allow new possibilities for structural studies on post-translationally modified proteins of clinical, pathological, and pharmaceutical interests.

The 2010 Rosetta Developers Meeting: Macromolecular Prediction and Design Meets Reproducible Publishing

The 2010 Rosetta Developers Meeting: Macromolecular Prediction and Design Meets Reproducible Publishing

A simplified recipe for assigning amide NMR signals using combinatorial 14N amino acid inverse-labeling

Assignment of backbone amide proton resonances is one of the most time-consuming stages of any protein NMR study when the protein samples behave non-ideally. A robust and convenient NMR procedure for analyzing spectra of marginal-to-low quality is helpful for high-throughput structure determination. The 14N selective- and inverse-labeling method is a candidate solution. Here, we present a simplified protocol for assigning protein backbone amide NMR signals. When 14N inversely labeled residues are present in a protein, their backbone NH cross peaks vanish from the protein's 1H-(15)N HSQC spectrum, and thus, their chemical shifts can be readily identified by a process of elimination. Some metabolically related amino acids, for example, Ile, Leu, and Val, cannot be individually incorporated but can be inversely labeled together. We optimized and simplified the protocol and M9-based medium formula for the 14N selective- and inverse-labeling method without any additives. Our approach should be cost-effective, because the method could be additively applied stepwise, even when the proteins of interest were found to be non-ideal.

The Scottish Structural Proteomics Facility: targets, methods and outputs

The Scottish Structural Proteomics Facility was funded to develop a laboratory scale approach to high throughput structure determination. The effort was successful in that over 40 structures were determined. These structures and the methods harnessed to obtain them are reported here. This report reflects on the value of automation but also on the continued requirement for a high degree of scientific and technical expertise. The efficiency of the process poses challenges to the current paradigm of structural analysis and publication. In the 5 year period we published ten peer-reviewed papers reporting structural data arising from the pipeline. Nevertheless, the number of structures solved exceeded our ability to analyse and publish each new finding. By reporting the experimental details and depositing the structures we hope to maximize the impact of the project by allowing others to follow up the relevant biology.Electronic supplementary materialThe online version of this article (doi:10.1007/s10969-010-9090-y) contains supplementary material, which is available to authorized users.