Structure Determination Process Research Articles

CryoEM Workflow Acceleration with Feret Signatures.

Common challenges in cryogenic electron microscopy, such as orientation bias, conformational diversity, and 3D misclassification, complicate single particle analysis and lead to significant resource expenditure. We previously introduced an in silico method using the maximum Feret diameter distribution, the Feret signature, to characterize sample heterogeneity of disc-shaped samples. Here, we expanded the Feret signature methodology to identify preferred orientations of samples containing arbitrary shapes with only about 1000 particles required. This method enables real-time adjustments of data acquisition parameters for optimizing data collection strategies or aiding in decisions to discontinue ineffective imaging sessions. Beyond detecting preferred orientations, the Feret signature approach can serve as an early-warning system for inconsistencies in classification during initial image processing steps, a capability that allows for strategic adjustments in data processing. These features establish the Feret signature as a valuable auxiliary tool in the context of single particle analysis, significantly accelerating the structure determination process.

A database overview of metal-coordination distances in metalloproteins.

Metalloproteins are ubiquitous in all living organisms and take part in a very wide range of biological processes. For this reason, their experimental characterization is crucial to obtain improved knowledge of their structure and biological functions. The three-dimensional structure represents highly relevant information since it provides insight into the interaction between the metal ion(s) and the protein fold. Such interactions determine the chemical reactivity of the bound metal. The available PDB structures can contain errors due to experimental factors such as poor resolution and radiation damage. A lack of use of distance restraints during the refinement and validation process also impacts the structure quality. Here, the aim was to obtain a thorough overview of the distribution of the distances between metal ions and their donor atoms through the statistical analysis of a data set based on more than 115 000 metal-binding sites in proteins. This analysis not only produced reference data that can be used by experimentalists to support the structure-determination process, for example as refinement restraints, but also resulted in an improved insight into how protein coordination occurs for different metals and the nature of their binding interactions. In particular, the features of carboxylate coordination were inspected, which is the only type of interaction that is commonly present for nearly all metals.

Joint micrograph denoising and protein localization in cryo-electron microscopy

Abstract Cryo-electron microscopy (cryo-EM) is an imaging technique that allows the visualization of proteins and macromolecular complexes at near-atomic resolution. The low electron doses used to prevent radiation damage to the biological samples result in images where the power of noise is 100 times stronger than that of the signal. Accurate identification of proteins from these low signal-to-noise ratio (SNR) images is a critical task, as the detected positions serve as inputs for the downstream 3D structure determination process. Current methods either fail to identify all true positives or result in many false positives, especially when analyzing images from smaller-sized proteins that exhibit extremely low contrast, or require manual labeling that can take days to complete. Acknowledging the fact that accurate protein identification is dependent upon the visual interpretability of micrographs, we propose a framework that can perform denoising and detection in a joint manner and enable particle localization under extremely low SNR conditions using self-supervised denoising and particle identification from sparsely annotated data. We validate our approach on three challenging single-particle cryo-EM datasets and projection images from one cryo-electron tomography dataset with extremely low SNR, showing that it outperforms existing state-of-the-art methods used for cryo-EM image analysis by a significant margin. We also evaluate the performance of our algorithm under decreasing SNR conditions and show that our method is more robust to noise than competing methods.

Structural Study of the Cobetia marina Bacteriophage 1 (Carin-1) by Cryo-EM.

Most of studied bacteriophages (phages) are terrestrial viruses. However, marine phages are shown to be highly involved in all levels of oceanic regulation. They are, however, still largely overlooked by the scientific community. By inducing cell lysis on half of the bacterial population daily, their role and influence on the bacterial biomass and evolution, as well as their impact in the global biogeochemical cycles, is undeniable. Cobetia marina virus 1 (Carin-1) is a member of the Podoviridae family infecting the γ-protoabacteria C. marina. Here, we present the almost complete, nearly-atomic resolution structure of Carin-1 comprising capsid, portal, and tail machineries at 3.5 Å, 3.8 Å and 3.9 Å, respectively, determined by cryo-electron microscopy (cryo-EM). Our experimental results, combined with AlphaFold2 (AF), allowed us to obtain the nearly-atomic structure of Carin-1 by fitting and refining the AF atomic models in the high resolution cryo-EM map, skipping the bottleneck of de-novo manual building and speeding up the structure determination process. Our structural results highlighted the T7-like nature of Carin1, as well as several novel structural features like the presence of short spikes on the capsid, reminiscent those described for Rhodobacter capsulatus gene transfer agent (RcGTA). This is, to our knowledge, the first time such assembly is described for a bacteriophage, shedding light into the common evolution and shared mechanisms between gene transfer agents and phages. This first full structure determined for a marine podophage allowed to propose an infection mechanism different than the one proposed for the archetypal podophage T7. IMPORTANCE Oceans play a central role in the carbon cycle on Earth and on the climate regulation (half of the planet's CO2 is absorbed by phytoplankton photosynthesis in the oceans and just as much O2 is liberated). The understanding of the biochemical equilibriums of marine biology represents a major goal for our future. By lysing half of the bacterial population every day, marine bacteriophages are key actors of these equilibriums. Despite their importance, these marine phages have, so far, only been studied a little and, in particular, structural insights are currently lacking, even though they are fundamental for the understanding of the molecular mechanisms of their mode of infection. The structures described in our manuscript allow us to propose an infection mechanism that differs from the one proposed for the terrestrial T7 virus, and might also allow us to, in the future, better understand the way bacteriophages shape the global ecosystem.

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.

Characterization of heterogeneity in nanodisc samples using Feret signatures

Nanodiscs have become a popular tool in structure determination of membrane proteins using cryogenic electron microscopy and single particle analysis. However, the structure determination of small membrane proteins remains challenging. When the embedded protein is in the same size range as the nanodisc, the nanodisc can significantly contribute to the alignment and classification during the structure determination process. In those cases, it is crucial to minimize the heterogeneity in the nanodisc preparations to assure maximum accuracy in the classification and alignment steps of single particle analysis. Here, we introduce a new in-silico method for the characterization of nanodisc samples that is based on analyzing the Feret diameter distribution of their particle projection as imaged in the electron microscope. We validated the method with comprehensive simulation studies and show that Feret signatures can detect subtle differences in nanodisc morphologies and composition that might otherwise go unnoticed. We used the method to identify a specific biochemical nanodisc preparation with low size variations, allowing us to obtain a structure of the 23-kDa single-span membrane protein Bcl-xL while embedded in a nanodisc. Feret signature analysis can steer experimental data collection strategies, allowing more efficient use of high-end data collection hardware, as well as image analysis investments in studies where nanodiscs significantly contribute to the total volume of the full molecular species.

NMR Crystallography as a Vital Tool in Assisting Crystal Structure Determination from Powder XRD Data

Powder X-ray diffraction (XRD) and solid-state NMR spectroscopy are complementary techniques for investigating the structural properties of solids, and there are considerable opportunities and advantages to applying these techniques synergistically together in determining the structural properties of crystalline solids. This article provides an overview of the potential to exploit structural information derived from solid-state NMR data to assist and enhance the process of crystal structure determination from powder XRD data, focusing in particular on the structure determination of organic molecular materials.

Square-Pyramidal Fe-N4 with Defect-Modulated O-Coordination: Two-Tier Electronic Structure Fine-Tuning for Enhanced Oxygen Reduction

Engineering the structure of molecularly dispersed 3d-transition metal phthalocyanines is emerging as an effective avenue for developing low-cost and efficient atomically dispersed catalysts (ADC). The strategy of using axial coordination to adjust the electronic structure of the M-N4 active site is effective for improving the performance of the catalysts, but the question to be asked is how to go beyond that. In this study, we propose and demonstrate a two-tier electronic modulation strategy, for the first time using carbon defects to regulate the tuning power of O-coordination, which in turn provides a more desirable electronic modulation on the Fe center of FePc, as compared to that of bare O-coordination. Such FePc-O-defect ADC was achieved using a one-step wet-ball-milling process with ethylene glycol as liquid media. The mechanochemically constructed active site is a square-pyramidal Fe-N4, with the Fe atom located out of the N4-plane towards an axially coordinated O that is singly bonded to graphene at vacancy defects.The resulting FePc-O-defect ADC with defect-modulated O-coordination exhibits excellent ORR activity in alkaline media, in terms of E1/2 and mass-specific activity. Compared to the baseline with bare O-coordination whose performance is already among the best reported nonprecious metal electrocatalysts, the defect-modulated O-coordination further enhanced the halfwave potential and doubled the kinetic current density. Combining with theoretical investigations, we elucidate how defect-modulated O-coordination would adjust the electronicand geometric structures of the Fe center and thus affect the electrocatalytic ORR. Also, resolving the structural configuration of bilayer catalysts with axial coordination is very challenging. The existed literature on bilayer catalyst, which either relies on 2D FT-EXAFS fitting analysis or simply assumes a bilayer configuration to work on, is in our opinion far from unambiguous structural determination. In this study, we differentiate our work from the existed literature, through a systematic structural determination process by comparing the experimentalXANES with the simulated ones, based on various structural models predicted by DFT calculations. Such analysis is especially necessary for catalysts with a 3D atomistic arrangement, but only a handful of studies have used this step of analysis (e.g., Nature Catalysis 1, 63-72(2018)). We believe that our study presents significant advances regarding the atomistic structure of bilayer catalysts with complex axial coordination.Overall, this work demonstrates a conceptually advanced two-tier electronic modulation strategy, through defect-modulated O-coordination, to further optimize the electronic structure of the Fe center in FePc toward ORR. The concept can be extended to modulate the electrocatalytic properties of molecular catalysts toward other electrochemical processes. Moreover, our catalysts were prepared at room temperature using an industrially available ball milling process. Such a facile pyrolysis-free synthetic approach is ready for scaleup with potentially 100 % usage of the FePc and graphene precursors.

High-resolution structure determination using high-throughput electron cryo-tomography.

Tomographic reconstruction of frozen-hydrated specimens followed by extraction and averaging of sub-tomograms has successfully been used to determine the structure of macromolecules in their native environment at resolutions that are high enough to reveal molecular level interactions. The low throughput characteristic of tomographic data acquisition combined with the complex data-analysis pipeline that is required to obtain high-resolution maps, however, has limited the applicability of this technique to favorable samples or to resolutions that are too low to provide useful mechanistic information. Recently, beam image-shift electron cryo-tomography (BISECT), a strategy to significantly accelerate the acquisition of tilt series without sacrificing image quality, was introduced. The ability to produce thousands of high-quality tilt series during a single microscope session, however, introduces significant bottlenecks in the downstream data analysis, which has so far relied on specialized pipelines. Here, recent advances in accurate estimation of the contrast transfer function and self-tuning exposure-weighting routines that contribute to improving the resolution and streamlining the structure-determination process using sub-volume averaging are reviewed. Ultimately, the combination of automated data-driven techniques for image analysis together with high-throughput strategies for tilt-series acquisition will pave the way for tomography to become the technique of choice for in situ structure determination.

Beyond the Backbone: The Next Generation of Pathwalking Utilities for Model Building in CryoEM Density Maps.

Single-particle electron cryomicroscopy (cryoEM) has become an indispensable tool for studying structure and function in macromolecular assemblies. As an integral part of the cryoEM structure determination process, computational tools have been developed to build atomic models directly from a density map without structural templates. Nearly a decade ago, we created Pathwalking, a tool for de novo modeling of protein structure in near-atomic resolution cryoEM density maps. Here, we present the latest developments in Pathwalking, including the addition of probabilistic models, as well as a companion tool for modeling waters and ligands. This software was evaluated on the 2021 CryoEM Ligand Challenge density maps, in addition to identifying ligands in three IP3R1 density maps at ~3 Å to 4.1 Å resolution. The results clearly demonstrate that the Pathwalking de novo modeling pipeline can construct accurate protein structures and reliably localize and identify ligand density directly from a near-atomic resolution map.

De Novo Crystal Structure Determination from Machine Learned Chemical Shifts.

Determination of the three-dimensional atomic-level structure of powdered solids is one of the key goals in current chemistry. Solid-state NMR chemical shifts can be used to solve this problem, but they are limited by the high computational cost associated with crystal structure prediction methods and density functional theory chemical shift calculations. Here, we successfully determine the crystal structures of ampicillin, piroxicam, cocaine, and two polymorphs of the drug molecule AZD8329 using on-the-fly generated machine-learned isotropic chemical shifts to directly guide a Monte Carlo-based structure determination process starting from a random gas-phase conformation.

New 19F NMR methodology reveals structures of molecules in complex mixtures of fluorinated compounds.

Although the number of natural fluorinated compounds is very small, fluorinated pharmaceuticals and agrochemicals are numerous. 19F NMR spectroscopy has a great potential for the structure elucidation of fluorinated organic molecules, starting with their production by chemical or chemoenzymatic reactions, through monitoring their structural integrity, to their biotic and abiotic transformation and ultimate degradation in the environment. Additionally, choosing to incorporate 19F into any organic molecule opens a convenient route to study reaction mechanisms and kinetics. Addressing limitations of the existing 19F NMR techniques, we have developed methodology that uses 19F as a powerful spectroscopic spy to study mixtures of fluorinated molecules. The proposed 19F-centred NMR analysis utilises the substantial resolution and sensitivity of 19F to obtain a large number of NMR parameters, which enable structure determination of fluorinated compounds without the need for their separation or the use of standards. Here we illustrate the 19F-centred structure determination process and demonstrate its power by successfully elucidating the structures of chloramination disinfectant by-products of a single mono-fluorinated phenolic compound, which would have been impossible otherwise. This novel NMR approach for the structure elucidation of molecules in complex mixtures represents a major contribution towards the analysis of chemical and biological processes involving fluorinated compounds.

A retrospect of the structure determination of Taka-amylase A.

The 3D structure of Taka-amylase A was determined by X-ray crystal analysis at 3Å resolution by Masao Kakudo's laboratory at the Institute for Protein Research, Osaka University, in 1980. Seven kinds of heavy atom derivatives were used for phase determination. There are three copies of Taka-amylase molecules in the asymmetric unit, which improved the quality of electron density maps, leading to the completion of a molecular model with 478 amino acids. The structure determination process in those days is described briefly.

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.

Analytical tools in protein structure determination

Three-dimensional protein structure prediction from amino acid sequence has been a thought-provoking task for decades, but it of pivotal importance as it provides a better understanding of its function. In recent years, the methods for prediction of protein structures have advanced considerably. Computational techniques and increase in protein sequence and structure databases have influence the laborious protein structure determination process. Still there is no single method which can predict all the protein structures. In this review, we describe the four stages of protein structure determination. We have also explored the currenttechniques used to uncover the protein structure and highpoint best suitable method for a given protein.

Advancements in macromolecular crystallography: from past to present.

Protein Crystallography or Macromolecular Crystallography (MX) started as a new discipline of science with the pioneering work on the determination of the protein crystal structures by John Kendrew in 1958 and Max Perutz in 1960. The incredible achievements in MX are attributed to the development of advanced tools, methodologies, and automation in every aspect of the structure determination process, which have reduced the time required for solving protein structures from years to a few days, as evident from the tens of thousands of crystal structures of macromolecules available in PDB. The advent of brilliant synchrotron sources, fast detectors, and novel sample delivery methods has shifted the paradigm from static structures to understanding the dynamic picture of macromolecules; further propelled by X-ray Free Electron Lasers (XFELs) that explore the femtosecond regime. The revival of the Laue diffraction has also enabled the understanding of macromolecules through time-resolved crystallography. In this review, we present some of the astonishing method-related and technological advancements that have contributed to the progress of MX. Even with the rapid evolution of several methods for structure determination, the developments in MX will keep this technique relevant and it will continue to play a pivotal role in gaining unprecedented atomic-level details as well as revealing the dynamics of biological macromolecules. With many exciting developments awaiting in the upcoming years, MX has the potential to contribute significantly to the growth of modern biology by unraveling the mechanisms of complex biological processes as well as impacting the area of drug designing.

Automated picking of amyloid fibrils from cryo-EM images for helical reconstruction with RELION

Cryogenic electron microscopy (cryo-EM) is an important tool for determining the molecular structure of proteins and protein assemblies, including helical assemblies such as amyloid fibrils. In reconstruction of amyloid fibril structures from cryo-EM images, an important early step is the selection of fibril locations. This fibril picking step is typically done by hand, a tedious process when thousands of images need to be analyzed. Here we present a computer program called FibrilFinder that identifies the locations and directions of fibril segments in cryo-EM images, by using the properties that the fibrils should be linear objects and have widths within a specified range. The program outputs the fibril locations in text files compatible with the RELION density reconstruction program. After RELION is used to extract the particle image boxes contained in the fibril segments identified by FibrilFinder, a second program called FibrilFixer removes boxes that contain more than one fibril, for instance because two fibrils cross each other. As concrete and realistic examples, we describe the application of the two programs to cryo-EM images of two different amyloid fibrils, namely 40-residue amyloid-β fibrils derived from human brain tissue by seeded growth and fibrils formed by the C-terminal half of the low-complexity domain of the RNA-binding protein FUS. Both examples of amyloid fibrils can be picked from cryo-EM images using the same set of FibrilFinder and FibrilFixer parameters, showing that this software does not require re-optimization for each sample. A set of 1337 cryo-EM images was analyzed in 17 min with one multi-core computer. The new fibril picking software should enable the rapid analysis and comparison of more helical structures using cryo-EM, and perhaps serve as part of the greater automation of the entire structure determination process.

Structure Determination of Multicomponent Crystalline Phases of (S)-Ibuprofen and l-Proline from Powder X-ray Diffraction Data, Augmented by Complementary Experimental and Computational Techniques

Two multicomponent crystalline phases of (S)-ibuprofen and l-proline with 1:1 stoichiometry are reported, specifically a nonsolvate phase (Ibu-Pro) and a quarter-hydrate phase (Ibu-Pro-QH). Ibu-Pro was prepared only by solid-state mechanochemical synthesis, while Ibu-Pro-QH was obtained both by solution-state crystallization and by solid-state mechanochemistry. The crystal structures of Ibu-Pro and Ibu-Pro-QH were determined directly from powder X-ray diffraction (XRD) data, with structure solution carried out using the direct-space strategy (implemented with a genetic algorithm search procedure) and structure refinement carried out using the Rietveld method. The process of structure determination from powder XRD data was augmented by information from other complementary techniques, specifically solid-state NMR spectroscopy, thermal analysis methods, and periodic DFT-D calculations. A preliminary powder XRD study of the dehydration behavior of Ibu-Pro-QH at elevated temperature is also reported.

Affinity and Structural Analysis of the U1A RNA Recognition Motif with Engineered Methionines to Improve Experimental Phasing.

RNA plays a central role in all organisms and can fold into complex structures to orchestrate function. Visualization of such structures often requires crystallization, which can be a bottleneck in the structure-determination process. To promote crystallization, an RNA-recognition motif (RRM) of the U1A spliceosomal protein has been co-opted as a crystallization module. Specifically, the U1-snRNA hairpin II (hpII) single-stranded loop recognized by U1A can be transplanted into an RNA target to promote crystal contacts and to attain phase information via molecular replacement or anomalous diffraction methods using selenomethionine. Herein, we produced the F37M/F77M mutant of U1A to augment the phasing capability of this powerful crystallization module. Selenomethionine-substituted U1A(F37M/F77M) retains high affinity for hpII (KD of 59.7 ± 11.4 nM). The 2.20 Å resolution crystal structure reveals that the mutated sidechains make new S-π interactions in the hydrophobic core and are useful for single-wavelength anomalous diffraction. Crystals were also attained of U1A(F37M/F77M) in complex with a bacterial preQ1-II riboswitch. The F34M/F37M/F77M mutant was introduced similarly into a lab-evolved U1A variant (TBP6.9) that recognizes the internal bulged loop of HIV-1 TAR RNA. We envision that this short RNA sequence can be placed into non-essential duplex regions to promote crystallization and phasing of target RNAs. We show that selenomethionine-substituted TBP6.9(F34M/F37M/F77M) binds a TAR variant wherein the apical loop was replaced with a GNRA tetraloop (KD of 69.8 ± 2.9 nM), laying the groundwork for use of TBP6.9(F34M/F37M/F77M) as a crystallization module. These new tools are available to the research community.

Rapid Structural Analysis of a Synthetic Non-canonical Amino Acid by Microcrystal Electron Diffraction.

Structural characterization of small molecules is a crucial component of organic synthesis. In this work, we applied microcrystal electron diffraction (MicroED) to analyze the structure of the product of an enzymatic reaction that was intended to produce the unnatural amino acid 2,4-dihydroxyphenylalanine (24DHF). Characterization of our isolated product with nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) suggested that an isomer of 24DHF had been formed. Microcrystals present in the isolated product were then used to determine its structure to 0.62 Å resolution, which confirmed its identity as 2-amino-2-(2,4-dihydroxyphenyl)propanoic acid (24DHPA). Moreover, the MicroED structural model indicated that both enantiomeric forms of 24DHPA were present in the asymmetric unit. Notably, the entire structure determination process including setup, data collection, and refinement was completed in ~1 h. The MicroED data not only bolstered previous results obtained using NMR and MS but also immediately provided information about the stereoisomers present in the product, which is difficult to achieve using NMR and MS alone. Our results therefore demonstrate that MicroED methods can provide useful structural information on timescales that are similar to many commonly used analytical methods and can be added to the existing suite of small molecule structure determination tools in future studies.