High-throughput Protein Crystallography Research Articles

GIWAXS experimental methods at the NFPS-BL17B beamline at Shanghai Synchrotron Radiation Facility.

The BL17B beamline at the Shanghai Synchrotron Radiation Facility was first designed as a versatile high-throughput protein crystallography beamline and one of five beamlines affiliated to the National Facility for Protein Science in Shanghai. It was officially opened to users in July 2015. As a bending magnet beamline, BL17B has the advantages of high photon flux, brightness, energy resolution and continuous adjustable energy between 5 and 23 keV. The experimental station excels in crystal screening and structure determination, providing cost-effective routine experimental services to numerous users. Given the interdisciplinary and green energy research demands, BL17B beamline has undergone optimization, expanded its range of experimental methods and enhanced sample environments for a more user-friendly testing mode. Thesemethods include single-crystal X-ray diffraction, powder crystal X-ray diffraction, wide-angle X-ray scattering, grazing-incidence wide-angle X-ray scattering (GIWAXS), and fully scattered atom pair distribution function analysis, covering structure detection from crystalline to amorphous states. This paper primarily presents the performance of the BL17B beamline and the application of the GIWAXS methodology at the beamline in the field of perovskite materials.

Structure-Based Design of Inhibitors of the m6A-RNA Writer Enzyme METTL3.

Methyltransferase-like 3 (METTL3) and METTL14 form a heterodimeric complex that catalyzes the most abundant internal mRNA modification, N6-methyladenosine (m6A). METTL3 is the catalytic subunit that binds the co-substrate S-adenosyl methionine (SAM), while METTL14 is involved in mRNA binding. The m6A modification provides post-transcriptional level control over gene expression as it affects almost all stages of the mRNA life cycle, including splicing, nuclear export, translation, and decay. There is increasing evidence for an oncogenic role of METTL3 in acute myeloid leukemia. Here, we use structural and dynamic details of the catalytic subunit METTL3 for developing small-molecule inhibitors that compete with SAM. Starting from a hit identified by high-throughput docking, protein crystallography and molecular dynamics simulations were employed to guide the optimization of inhibitory activity. The potency was successfully improved by 8000-fold as measured by a homogeneous time-resolved fluorescence assay. The optimized compound is selective against the off-targets RNA methyltransferases METTL1 and METTL16.

X-ray Screening of an Electrophilic Fragment Library and Application toward the Development of a Novel ERK 1/2 Covalent Inhibitor.

Fragment-based drug discovery (FBDD) has become an established method for the identification of efficient starting points for drug discovery programs. In recent years, electrophilic fragment screening has garnered increased attention from both academia and industry to identify novel covalent hits for tool compound or drug development against challenging drug targets. Herein, we describe the design and characterization of an acrylamide-focused electrophilic fragment library and screening campaign against extracellular signal-regulated kinase 2 (ERK2) using high-throughput protein crystallography as the primary hit-finding technology. Several fragments were found to have covalently modified the adenosine triphosphate (ATP) binding pocket Cys166 residue. From these hits, 22, a covalent ATP-competitive inhibitor with improved potency (ERK2 IC50 = 7.8 μM), was developed.

DeepCentering: fully automated crystal centering using deep learning for macromolecular crystallography.

High-throughput protein crystallography using a synchrotron light source is an important method used in drug discovery. Beamline components for automated experiments including automatic sample changers have been utilized to accelerate the measurement of a number of macromolecular crystals. However, unlike cryo-loop centering, crystal centering involving automated crystal detection is a difficult process to automate fully. Here, DeepCentering, a new automated crystal centering system, is presented. DeepCentering works using a convolutional neural network, which is a deep learning operation. This system achieves fully automated accurate crystal centering without using X-ray irradiation of crystals, and can be used for fully automated data collection in high-throughput macromolecular crystallography.

Construction of a Shape-Diverse Fragment Set: Design, Synthesis and Screen against Aurora-A Kinase.

Historically, chemists have explored chemical space in a highly uneven and unsystematic manner. As an example, the shape diversity of existing fragment sets does not generally reflect that of all theoretically possible fragments. To assess experimentally the added value of increased three dimensionality, a shape-diverse fragment set was designed and collated. The set was assembled by both using commercially available fragments and harnessing unified synthetic approaches to sp3 -rich molecular scaffolds. The resulting set of 80 fragments was highly three-dimensional, and its shape diversity was significantly enriched by twenty synthesised fragments. The fragment set was screened by high-throughput protein crystallography against Aurora-A kinase, revealing four hits that targeted the binding site of allosteric regulators. In the longer term, it is envisaged that the fragment set could be screened against a range of functionally diverse proteins, allowing the added value of more shape-diverse screening collections to be more fully assessed.

Automatic crystal centring procedure at the SSRF macromolecular crystallography beamline.

X-ray diffraction is a common technique for determining crystal structures. The average time needed for the solution of a protein structure has been drastically reduced by a number of recent experimental and theoretical developments. Since high-throughput protein crystallography benefits from full automation of all steps that are carried out on a synchrotron beamline, an automatic crystal centring procedure is important for crystallographic beamlines. Fully automatic crystal alignment involves the application of optical methods to identify the crystal and move it onto the rotation axis and into the X-ray beam. Crystal recognition has complex dependencies on the illumination, crystal size and viewing angles due to effects such as local shading, inter-reflections and the presence of antifreezing elements. Here, a rapid procedure for crystal centring with multiple cameras using region segment thresholding is reported. Firstly, a simple illumination-invariant loop recognition and classification model is used by slicing a low-magnification loop image into small region segments, then classifying the loop into different types and aligning it to the beam position using feature vectors of the region segments. Secondly, an edge detection algorithm is used to find the crystal sample in a high-magnification image using region segment thresholding. Results show that this crystal centring method is extremely successful under fluctuating light states as well as for poorly frozen and opaque samples. Moreover, this crystal centring procedure is successfully integrated into the enhanced Blu-Ice data collection system at beamline BL17U1 at the Shanghai Synchrotron Radiation Facility as a routine method for an automatic crystal screening procedure.

Some Aspects of Crystal Centering During X-ray High-throughput Protein Crystallography Experiment

A set of algorithms and procedures of a crystal loop centering during X-ray high-throughput protein crystallography experiment has been designed and developed. A simple algorithm of the crystal loop detection and preliminary recognition has been designed and developed. The crystal loop detection algorithm is based on finding out the crystal loop ending point (opposite to the crystal loop pin) using image cross section (digital image column) profile analysis. The crystal loop preliminary recognition procedure is based on finding out the crystal loop sizes and position using image cross section profile analysis. The crystal loop fine recognition procedure based on Hooke-Jeeves pattern search method with an ellipse as a fitting pattern has been designed and developed. The procedure of restoring missing coordinate of the crystal loop is described. Based on developed algorithms and procedures the optimal auto-centering procedure has been designed and developed. A procedure of optimal manual crystal centering (Two Clicks Procedure) has been designed and developed. Developed procedures have been integrated into control software system PCCS installed at crystallography beamlines Photon Factory BL5A and PF-AR NW12, KEK.

A geometrical approach for semi-automated crystal centering andin situX-ray diffraction data collection

High-throughput protein crystallography projects pushed forward the development of automated crystallization platforms that are now commonly used. This created an urgent need for adapted and automated equipment for crystal analysis. However, first these crystals have to be harvested, cryo-protected and flash-cooled, operations that can fail or negatively impact on the crystal.In situX-ray diffraction analysis has become a valid alternative to these operations, and a growing number of users apply it for crystal screening and to solve structures. Nevertheless, even this shortcut may require a significant amount of beam time. In thisin situhigh-throughput approach, the centering of crystals relative to the beam represents the bottleneck in the analysis process. In this article, a new method to accelerate this process, by recording accurately the local geometry coordinates for each crystal in the crystallization plate, is presented. Subsequently, the crystallization plate can be presented to the X-ray beam by an automated plate-handling device, such as a six-axis robot arm, for an automated crystal centering in the beam,in situscreening or data collection. Here the preliminary results of such a semi-automated pipeline are reported for two distinct test proteins.

In-crystal affinity ranking of fragment hit compounds reveals a relationship with their inhibitory activities

Fragment-based drug discovery (FBDD), which is a molecular build-up strategy from small scaffolds, has recently become a promising approach for lead-compound generation. Although high-throughput protein crystallography is usually used to determine the protein–ligand complex structure and identify potential hit compounds, the relationship between the quality of theFo–Fcmaps of hit compounds and their inhibitory activities has rarely been examined. To address this issue, crystallographic competition experiments were carried out to determine the relative order of the in-crystal binding affinities using five hit compounds of bovine pancreatic trypsin inhibitors. Soaking experiments of all combinations of the five hit compounds were used to define the in-crystal affinity ranking. Based on characterization by a high-concentration bioassay, a clear correlation was observed between in-crystal binding affinities and the inhibitory activities in solution. Moreover, the correlation analysis revealed that X-ray-based screening can detect a weak hit compound with inhibitory activity below the limit of detection, even in a high-concentration assay. The proposed crystallographic competition method could function as a valuable tool, not only to select a plausible starting scaffold for subsequent synthetic efforts but also to access structure–activity relationships using fragment compounds with a wider detection limit than a biological assay. The crystallographic validation methodology described here will greatly accelerate the hit-to-lead process during fragment-based and structure-based drug design.

Advancement of Synchrotron Radiation Protein Crystallography Aimed by the Targeted Protein Research Program: Beamline Developments at the Photon Factory

The Targeted Protein Research Program (TPRP) started in 2007 as a sequel of the Protein 3000 Project which lasted from 2002 to 2007. In the new project, four cores, Protein Production, Structure Analysis, Control of Protein Functions with Compounds, and Informatics, have been established as focus of methodology developments critical for functional and structural studies by the target protein research teams. Within the "Analysis Core" synchrotron radiation plays a pivotal role providing X-ray beams for structural analyses of the target proteins. The two large Japanese synchrotron radiation facilities, SPring-8 and Photon Factory (PF), along with three protein crystallography groups from Hokkaido, Kyoto and Osaka Universities have teamed up to develop two complementary micro-beam beamlines, one on each synchrotron site, and associated technologies for cutting edge structural biology research. At the PF, there are 5 operational beamlines which are equipped with state-of-the-art instrumentation for high-throughput protein crystallography experiments. Within the TPRP framework, the PF is developing a micro-focus beamline optimized for a lower energy single anomalous diffraction (SAD) experiment. This will be particularly useful for structure determination of difficult protein targets for which heavy atom derivatives or selenomethionine substitution does not work and other standard phasing methods fail to give structure solutions. This will augment the capabilities of the PF structural biology beamlines with similar look-and-feel experimental environments.

Installation of high-throughput protein crystallography data collection at SPring-8 BL12B2

Installation of high-throughput protein crystallography data collection at SPring-8 BL12B2

Development of an X-ray HARP–FEA detector system for high-throughput protein crystallography

A new detector system for protein crystallography is now being developed based on an X-ray HARP-FEA (high-gain avalanche rushing amorphous photoconductor-field emitter array), which consists of an amorphous selenium membrane and a matrix field emitter array. The combination of the membrane avalanche effect with a single driven FEA has several advantages over currently available area detectors, including higher sensitivity, higher spatial resolution and a higher frame rate. Preliminary evaluation of the detector has been carried out and its effectiveness has been confirmed. Next, diffraction images were measured with continuous rotation of a protein crystal, and the images were compared with those measured by the existing CCD detector; the system successfully obtained high-spatial-resolution images. Using shutterless measurement, the total measurement time can be reduced significantly, making the method appropriate for high-throughput protein crystallography. The X-ray HARP-FEA detector is an attractive candidate for the next generation of X-ray area detectors.

Creating protein models from electron-density maps using particle-filtering methods

One bottleneck in high-throughput protein crystallography is interpreting an electron-density map, that is, fitting a molecular model to the 3D picture crystallography produces. Previously, we developed ACMI (Automatic Crystallographic Map Interpreter), an algorithm that uses a probabilistic model to infer an accurate protein backbone layout. Here, we use a sampling method known as particle filtering to produce a set of all-atom protein models. We use the output of ACMI to guide the particle filter's sampling, producing an accurate, physically feasible set of structures. We test our algorithm on 10 poor-quality experimental density maps. We show that particle filtering produces accurate all-atom models, resulting in fewer chains, lower sidechain RMS error and reduced R factor, compared to simply placing the best-matching sidechains on ACMI's trace. We show that our approach produces a more accurate model than three leading methods--Textal, Resolve and ARP/WARP--in terms of main chain completeness, sidechain identification and crystallographic R factor. Source code and experimental density maps available at http://ftp.cs.wisc.edu/machine-learning/shavlik-group/programs/acmi/

High-pressure cryocooling for capillary sample cryoprotection and diffraction phasing at long wavelengths

Crystal cryocooling is usually employed to reduce radiation damage during X-ray crystallography. Recently, a high-pressure cryocooling method has been developed which results in excellent diffraction-quality crystals without the use of penetrative cryoprotectants. Three new developments of the method are presented here: (i) Xe-He high-pressure cryocooling for Xe SAD phasing, (ii) native sulfur SAD phasing and (iii) successful cryopreservation of crystals in thick-walled capillaries without additional cryoprotectants other than the native mother liquor. These developments may be useful for structural solution of proteins without the need for selenomethionine incorporation and for high-throughput protein crystallography.

SPINE high-throughput crystallization, crystal imaging and recognition techniques: current state, performance analysis, new technologies and future aspects

This paper reviews the developments in high-throughput and nanolitre-scale protein crystallography technologies within the remit of workpackage 4 of the Structural Proteomics In Europe (SPINE) project since the project's inception in October 2002. By surveying the uptake, use and experience of new technologies by SPINE partners across Europe, a picture emerges of highly successful adoption of novel working methods revolutionizing this area of structural biology. Finally, a forward view is taken of how crystallization methodologies may develop in the future.

DNA & e-HTPX: high throughput and remote access protein crystallography

DNA & e-HTPX: high throughput and remote access protein crystallography

E-science technologies in synchrotron radiation beamline — remote access and automation (A case study for high throughput protein crystallography)

E-science refers to the large-scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. The Grid is a service-oriented architecture proposed to provide access to very large data collections, very large scale computing resources and remote facilities. Web services, which are server applications, enable online access to service providers. Web portal interfaces can further hide the complexity of accessing facility’s services. The main use of synchrotron radiation (SR) facilities by protein crystallographers is to collect the best possible diffraction data for reasonably well defined problems. Significant effort is therefore being made throughout the world to automate SR protein crystallography facilities so scientists can achieve high throughput, even if they are not expert in all the techniques. By applying the above technologies, the e-HTPX project, a distributed computing infrastructure, was designed to help scientists remotely plan, initiate and monitor experiments for protein crystallographic structure determination. A description of both the hardware and control software is given together in this paper.

RIKEN structural genomics beamlines at the SPring-8; high throughput protein crystallography with automated beamline operation

RIKEN Structural Genomics Beamlines, BL26B1 & BL26B2 at the SPring-8, have been constructed for the structural genomics research. The main feature of the beamline is full automation of the successive data collections to maximize the beam-time efficiency. The beamline optics adopted a standard design commonly used for the SPring-8 bending magnet beamlines. Beamline instruments are operated by centralized control system through the computer network to achieve the automatic operation. The core part of the beamline development is a sample management system composed of sample changer robots for laboratory and beamline, and a networked sample database. BL26B1 has started user operation, and the automatic operation with the sample management system has been implemented at BL26B2.

Automated classification of protein crystallization images using support vector machines with scale-invariant texture and Gabor features

Protein crystallography laboratories are performing an increasing number of experiments to obtain crystals of good diffraction quality. Better automation has enabled researchers to prepare and run more experiments in a shorter time. However, the problem of identifying which experiments are successful remains difficult. In fact, most of this work is still performed manually by humans. Automating this task is therefore an important goal. As part of a project to develop a new and automated high-throughput capillary-based protein crystallography instrument, a new image-classification subsystem has been developed to greatly reduce the number of images that require human viewing. This system must have low rates of false negatives (missed crystals), possibly at the cost of raising the number of false positives. The image-classification system employs a support vector machine (SVM) learning algorithm to classify the blocks making up each image. A new algorithm to find the area within the image that contains the drop is employed. The SVM uses numerical features, based on texture and the Gabor wavelet decomposition, that are calculated for each block. If a block within an image is classified as containing a crystal, then the entire image is classified as containing a crystal. In a study of 375 images, 87 of which contained crystals, a false-negative rate of less than 4% with a false-positive rate of about 40% was consistently achieved.

High-Throughput Protein Crystallography

An automated platform for low-volume, highthroughput protein crystallization by the sitting drop vapor diffusion has been developed. This platform consists of a novel Society of Biomolecular Screening standard microplate technology, standard automation liquid handling equipment, a software to design customizable, random crystallization buffers, an in-house designed scanner, a crystal recognition software, and Laboratory Information Management Systems. These technologies are designed to eliminate obstacles to the production of protein crystals and to address a number of critical issues faced by crystallography laboratories, namely precision and accuracy, ease of integration and use, speed, and cost.