Single-particle cryo-EM at atomic resolution

A large-scale curated and filterable dataset for cryo-EM foundation model pre-training

Cryo-electron microscopy (cryo-EM) is a transformative imaging technology that enables near-atomic resolution 3D reconstruction of target biomolecule, playing a critical role in structural biology and drug discovery. Cryo-EM faces significant challenges due to its extremely low signal-to-noise ratio (SNR) where the complexity of data processing becomes particularly pronounced. To address this challenge, foundation models have shown great potential in other biological imaging domains. However, their application in cryo-EM has been limited by the lack of large-scale, high-quality datasets. To fill this gap, we introduce CryoCRAB, the first large-scale dataset for cryo-EM foundation models. CryoCRAB includes 746 proteins, comprising 152,385 sets of raw movie frames (116.8 TB in total). To tackle the high-noise nature of cryo-EM data, each movie is split into odd and even frames to generate paired micrographs for denoising tasks. The dataset is stored in HDF5 chunked format, significantly improving random sampling efficiency and training speed. CryoCRAB offers diverse data support for cryo-EM foundation models, enabling advancements in image denoising and general-purpose feature extraction for downstream tasks.

Non-uniform Fourier transform based image classification in single-particle Cryo-EM

In the single-particle Cryo-EM projection image classification, it is a common practice to apply the Fourier transform to the images and extract rotation-invariant features in the frequency domain. However, this process involves interpolation, which can reduce the accuracy of the results. In contrast, the non-uniform Fourier transform provides more direct and accurate computation of rotation-invariant features without the need for interpolation in the computation process. Leveraging the capabilities of the non-uniform discrete Fourier transform (NUDFT), we have developed an algorithm for the rotation-invariant classification. To highlight its potential and applicability in the field of single-particle Cryo-EM, we conducted a direct comparison with the traditional Fourier transform and other methods, demonstrating the superior performance of the NUDFT.

NMR-driven structure-based drug discovery by unveiling molecular interactions

High-resolution 3D structural information is crucial for drug discovery and routinely used in structure-guided optimization to improve initial hits from screening campaigns to clinical drug candidates. X-ray crystallography is commonly the method of choice to guide medicinal chemistry in the design process, but it has its limitations and shortcomings. Here, we discuss the use of solution-state NMR spectroscopy in combination with selective side-chain labeling and advanced computational workflows to generate protein-ligand ensembles. This provides reliable and accurate structural information about protein-ligand complexes for medicinal chemists that is also suitable for high-throughput.

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

Chemical Identification of [Fe(III)(OH)(H2O)]2+ Complex Ion at the Ferroxidase Active Site in Cryo-EM Maps

Cryo-EM generates images of the distribution of the electrostatic potential (ESP) in objects. The contributions to ESP maps made by atoms that are charged extend over distances far greater than their own diameters and thus make a disproportionately large contribution to the low-frequency terms in the Fourier transforms of these maps. For this reason, analysis of the frequency-dependence of the information in cryo-EM maps can distinguish hydroxyl anions from water molecules or ferric ions from ferrous ions. Here, this approach is used to show that the metal ion bound in the ferroxidase active site in a recently published cryo-EM map (emd-35984) of recombinant murine heavy-chain ferritin is Fe3+. It is coordinated by E27, E62, and H65 in a distorted square pyramidal geometry with its other two ligands being a hydroxyl anion and a water molecule. That metal ion was originally identified as a sodium ion. Additionally, it is found that there is a Cl- anion bound to the 4-fold axial gate formed by partially protonated H173 residues.

AI-driven de novo enzyme design: Strategies, applications, and future prospects

Enzymes are indispensable for biological processes and diverse applications across industries. While top-down modification strategies, such as directed evolution, have achieved remarkable success in optimizing existing enzymes, bottom-up de novo enzyme design has emerged as a transformative approach for engineering novel enzymes with customized catalytic functions, independent of natural templates. Recent advancements in artificial intelligence (AI) and computational power have significantly accelerated this field, enabling breakthroughs in enzyme engineering. These technologies facilitate the rapid generation of enzyme structures and amino acid sequences optimized for specific functions, thereby enhancing design efficiency. They also support functional validation and activity optimization, improving the catalytic performance, stability, and robustness of de novo designed enzymes. This review highlights recent advancements in AI-driven de novo enzyme design, discusses strategies for validation and optimization, and examines the challenges and future prospects of integrating these technologies into enzyme development.

A Foundational Shift in Models for Enzyme Function

This Perspective addresses the unresolved, and still hotly contested, question of how enzymes transition from stable enzyme-substrate (ES) complexes to successful, femtosecond barrier crossings. By extending Marcus theory to enzyme-catalyzed reactions, we argue that environmental reorganization of the protein scaffold, together with associated water molecules, achieves the intersection of reactant and product potential energy surfaces. After discussing the experimentally demonstrated importance of reduced activation enthalpy in enzyme-catalyzed transformations, we describe new methodologies that measure the temperature dependence of (i) time-averaged hydrogen/deuterium exchange into backbone amides and (ii) time-dependent Stokes shifts to longer emission wavelengths in appended chromophores at the protein/water interface. These methods not only identify specific pathways for the transfer of thermal energy from solvent to the reacting bonds of bound substrates but also suggest that collective thermally activated protein restructuring must occur very rapidly (on the ns-ps time scale) over long distances. Based on these findings, we introduce a comprehensive model for how barrier crossing takes place from the ES complex. This exploits the structural preorganization inherent in protein folding and subsequent conformational sampling, which optimally positions essential catalytic components within ES ground states and correctly places reactive bonds in the substrate(s) relative to embedded energy transfer networks connecting the protein surface to the active site. The existence of these anisotropic energy distribution pathways introduces a new dimension into the ongoing quest for improved de novo enzyme design.

Cryo-EM of Mitochondrial Complex I and ATP Synthase

Cryo-electron microscopy (cryo-EM) is the method of choice for investigating the structures of membrane protein complexes at high resolution under near-native conditions. This review focuses on recent cryo-EM work on mitochondrial complex I and ATP synthase. Single-particle cryo-EM structures of complex I from mammals, plants, and fungi extending to a resolution of 2 Å show different functional states, indicating consistent conformational changes of loops near the Q binding site, clusters of internal water molecules in the membrane arm, and an α-π transition in a membrane-spanning helix that opens and closes the proton transfer path. Cryo-EM structures of ATP synthase dimers from mammalian, yeast, and Polytomella mitochondria show several rotary states at a resolution of 2.7 to 3.5 Å. The new structures of complex I and ATP synthase are important steps along the way toward understanding the detailed molecular mechanisms of both complexes. Cryo-electron tomography and subtomogram averaging have the potential to resolve their high-resolution structures in situ.

Commonsense and common nonsense opinions: PROSPECTS for further reducing beam damage in electron microscopy of radiation-sensitive specimens

Biological molecules are easily damaged by high-energy electrons, thus limiting the exposures that can be used to image such specimens by electron microscopy. It is argued here that many-electron, volume-plasmon excitations, which promptly transition into multiple types of single-electron ionization and excitation events, seem to be the predominant cause of damage in such materials. Although reducing the rate at which primary radiolysis occurs would allow one to record images that were much less noisy, many novel proposals for achieving this are unlikely to be realized in the near future, while others are manifestly ill-founded. As a result, the most realistic option currently is to more effectively use the available "budget" of electron exposure, i.e. to further improve the "dose efficiency" by which images are recorded. While progress in that direction is currently under way for both "conventional" (i.e. fixed-beam) and scanning EM, the former is expected to set a high standard for the latter to surpass.

Advances in research on mitochondrial dysfunction in neurodegenerative diseases

Given the high energy demand of the nervous system, mitochondrial dysfunction is a key factor in the pathogenesis of neurodegenerative diseases. Thus, a comprehensive understanding of its mechanisms and potential therapeutic targets is essential. This review discusses the roles of mitochondrial oxidative stress, mitochondrial dynamics alterations, and mtDNA damage in Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and multiple sclerosis (MS). In addition, it summarizes the contributions of novel technological approaches in detecting mitochondrial dysfunction, which assist in disease diagnosis. We also emphasize emerging therapeutic strategies and drugs aimed at enhancing mitochondrial quality control and reducing oxidative stress, thereby laying the groundwork for innovative therapeutic approaches in neurodegenerative disease treatment.

Molecular dynamics study on the mitigation of radiation damage caused by electron pulses

The reduction of radiation damage represents a long-term objective for electron microscopists, particularly those engaged in the study of biological and organic matter. Recently, electron pulses in ultrafast transmission electron microscopy have been demonstrated to serve as a damage mitigation technique for radiation-sensitive materials. Nevertheless, the underlying mechanism of the mitigation effects remains unclear. In this study, we investigate the radiation damage of graphene induced by pulsed electrons using molecular dynamics simulations within the framework of binary elastic collisions. For electron irradiation at 200 keV, it was found that the pulsed electron beam corresponds to a larger threshold angle (1.4 rad) than that for a random beam (1.0 rad). This is because two electrons can be prevented from briefly interacting with the same or a neighboring atom by the use of well-controlled electron pulses. While such a mitigation of radiation damage is only apparent near the threshold angle, and there are likely other reduction mechanisms, our results provide insight into the mitigated radiation damage of electron pulses.

Navigating the unstructured by evaluating alphafold's efficacy in predicting missing residues and structural disorder in proteins

The study investigated regions with undefined structures, known as "missing" segments in X-ray crystallography and cryo-electron microscopy (Cryo-EM) data, by assessing their predicted structural confidence and disorder scores. Utilizing a comprehensive dataset from the Protein Data Bank (PDB), residues were categorized as "modeled", "hard missing" and "soft missing" based on their visibility in structural datasets. Key features were determined, including a confidence score predicted local distance difference test (pLDDT) from AlphaFold2, an advanced structural prediction tool, and a disorder score from IUPred, a traditional disorder prediction method. To enhance prediction performance for unstructured residues, we employed a Long Short-Term Memory (LSTM) model, integrating both scores with amino acid sequences. Notable patterns such as composition, region lengths and prediction scores were observed in unstructured residues and regions identified through structural experiments over our studied period. Our findings also indicate that "hard missing" residues often align with low confidence scores, whereas "soft missing" residues exhibit dynamic behavior that can complicate predictions. The incorporation of pLDDT, IUPred scores, and sequence data into the LSTM model has improved the differentiation between structured and unstructured residues, particularly for shorter unstructured regions. This research elucidates the relationship between established computational predictions and experimental structural data, enhancing our ability to target structurally significant areas for research and guiding experimental designs toward functionally relevant regions.

Structural determinants of rotavirus proteolytic activation

The infectivity of rotavirus (RV), the leading cause of childhood diarrhea, hinges on the activation of viral particles through the proteolysis of the spike protein by trypsin-like proteases in the host intestinal lumen. Despite comprehensive structural characterization of the virus particle, the structural rationale behind the necessity of trypsin digestion of the VP4 protein for infectivity remains poorly understood. In this study, using cryo-electron microscopy (cryo-EM) and advanced image processing techniques, we compared uncleaved and cleaved RV virions and found that the conformation of the non-proteolyzed spike is constrained by the position of loops that surround its structure, linking the lectin domains of the spike head to its body. The proteolysis of these loops removes this structural constraint, thereby enabling the spike to undergo the necessary conformational changes required for cell membrane penetration. Thus, these loops function as regulatory elements to ensure that the spike protein is activated precisely when and where it is needed to facilitate a successful infection.

Molecular glues that inhibit deubiquitylase activity and inflammatory signaling

Deubiquitylases (DUBs) are crucial in cell signaling and are often regulated by interactions within protein complexes. The BRCC36 isopeptidase complex (BRISC) regulates inflammatory signaling by cleaving K63-linked polyubiquitin chains on type I interferon receptors (IFNAR1). As a Zn2+-dependent JAMM/MPN (JAB1, MOV34, MPR1, Pad1 N-terminal) DUB, BRCC36 is challenging to target with selective inhibitors. Here, we discover first-in-class inhibitors, termed BRISC molecular glues (BLUEs), which stabilize a 16-subunit human BRISC dimer in an autoinhibited conformation, blocking active sites and interactions with the targeting subunit, serine hydroxymethyltransferase 2. This unique mode of action results in selective inhibition of BRISC over related complexes with the same catalytic subunit, splice variants and other JAMM/MPN DUBs. BLUE treatment reduced interferon-stimulated gene expression in cells containing wild-type BRISC and this effect was abolished when using structure-guided, inhibitor-resistant BRISC mutants. Additionally, BLUEs increase IFNAR1 ubiquitylation and decrease IFNAR1 surface levels, offering a potential strategy to mitigate type I interferon-mediated diseases. Our approach also provides a template for designing selective inhibitors of large protein complexes by promoting rather than blocking protein-protein interactions.

DockEM: an enhanced method for atomic-scale protein-ligand docking refinement leveraging low-to-medium resolution cryo-EM density maps

Protein-ligand docking plays a pivotal role in virtual drug screening, and recent advancements in cryo-electron microscopy (cryo-EM) technology have significantly accelerated the progress of structure-based drug discovery. However, the majority of cryo-EM density maps are of medium to low resolution (3-10 Å), which presents challenges in effectively integrating cryo-EM data into molecular docking workflows. In this study, we present an updated protein-ligand docking method, DockEM, which leverages local cryo-EM density maps and physical energy refinement to precisely dock ligands into specific protein binding sites. Tested on a dataset of 121 protein-ligand compound, our results demonstrate that DockEM outperforms other advanced docking methods. The strength of DockEM lies in its ability to incorporate cryo-EM density map information, effectively leveraging the structural information of ligands embedded within these maps. This advancement enhances the use of cryo-EM density maps in virtual drug screening, offering a more reliable framework for drug discovery.

Extending the reach of single-particle cryoEM

Molecular structure determination using electron cryomicroscopy (cryoEM) is poised in early 2025 to surpass X-ray crystallography as the most used method for experimentally determining new structures. But the technique has not reached the physical limits set by radiation damage and the signal-to-noise ratio in individual images of molecules. By examining these limits and comparing the number and resolution of structures determined versus molecular weight, we identify opportunities for extending the application of single-particle cryoEM. This will help guide technology development to continue the exponential growth of structural biology.

Unraveling atomic complexity from frozen samples

Cryo-electron microscopy (cryo-EM) is a significant driver of recent advances in structural biology. Cryo-EM is comprised of several distinct and complementary methods, which include single particle analysis, cryo-electron tomography, and microcrystal electron diffraction. In this Perspective, we will briefly discuss the different branches of cryo-EM in structural biology and the current challenges in these areas.

Carboxysomes: The next frontier in biotechnology and sustainable solutions

Some bacteria possess microcompartments that function as protein-based organelles. Bacterial microcompartments (BMCs) sequester enzymes to optimize metabolic reactions. Several BMCs have been characterized to date, including carboxysomes and metabolosomes. Genomic analysis has identified novel BMCs and their loci, often including genes for signature enzymes critical to their function, but further characterization is needed to confirm their roles. Among the various BMCs, carboxysomes, which are found in cyanobacteria and some chemoautotrophic bacteria, and are most extensively investigated. These self-assembling polyhedral proteinaceous BMCs are essential for carbon fixation. Carboxysomes encapsulate the enzymes RuBisCo and carbonic anhydrase, which increase the carbon fixation rate in the cell and decrease the oxygenation rate by RuBisCo. The ability of carboxysomes to concentrate carbon dioxide in crops and industrially relevant microorganisms renders them attractive targets for carbon assimilation bioengineering. Thus, carboxysome characterization is the first step toward developing carboxysome-based applications. Therefore, this review comprehensively explores carboxysome morphology, physiology, and biochemistry. It also discusses recent advances in microscopy and complementary techniques for isolating and characterizing this versatile class of prokaryotic organelles.

Fast event-based electron counting for small-molecule structure determination by MicroED

Electron counting helped realize the resolution revolution in single-particle cryoEM and is now accelerating the determination of MicroED structures. Its advantages are best demonstrated by new direct electron detectors capable of fast (kilohertz) event-based electron counting (EBEC). This strategy minimizes the inaccuracies introduced by coincidence loss (CL) and promises rapid determination of accurate structures. We used the Direct Electron Apollo camera to leverage EBEC technology for MicroED data collection. Given its ability to count single electrons, the Apollo collects high-quality MicroED data from organic small-molecule crystals illuminated with incident electron beam flux densities as low as 0.01-0.045 e-/Å2/s. Under even the lowest flux density (0.01 e-/Å2/s) condition, fast EBEC data produced ab initio structures of a salen ligand (268 Da) and biotin (244 Da). Each structure was determined from a 100° wedge of data collected from a single crystal in as few as 50 s, with a delivered fluence of only ∼0.5 e-/Å2. Fast EBEC data collected with a fluence of 2.25 or 3.33 e-/Å2 also facilitated a 1.5 Å structure of thiostrepton (1665 Da). While refinement of these structures appeared unaffected by CL, a CL adjustment applied to EBEC data further improved the distribution of intensities measured from the salen ligand and biotin crystals. However, CL adjustment only marginally improved the refinement of their corresponding structures, signaling the already high counting accuracy of detectors with counting rates in the kilohertz range. Overall, by delivering low-dose structure-worthy data, fast EBEC collection strategies open new possibilities for high-throughput MicroED.

Retrieval of Phase Information from Low-Dose Electron Microscopy Experiments: Are We at the Limit Yet?

The challenge of imaging low-density objects in an electron microscope without causing beam damage is significant in modern transmission electron microscopy. This is especially true for life science imaging, where the sample, rather than the instrument, still determines the resolution limit. Here, we explore whether we have to accept this or can progress further in this area. To do this, we use numerical simulations to see how much information we can obtain from a weak phase object at different electron doses. Starting from a model with four phase values, we compare Zernike phase contrast with measuring diffracted intensity under multiple random phase illuminations to solve the inverse problem. Our simulations have shown that diffraction-based methods perform better than the Zernike method, as we have found and addressed a normalization issue that, in some other studies, led to an overly optimistic representation of the Zernike setup. We further validated this using more realistic 2D objects and found that random phase illuminated diffraction can be up to five times more efficient than an ideal Zernike implementation. These findings suggest that diffraction-based methods could be a promising approach for imaging beam-sensitive materials and that current low-dose imaging methods are not yet at the quantum limit.

Few-shot learning for non-vitrified ice segmentation

This study introduces Ice Finder, a novel tool for quantifying crystalline ice in cryo-electron tomography, addressing a critical gap in existing methodologies. We present the first application of the meta-learning paradigm to this field, demonstrating that diverse tomographic tasks across datasets can be unified under a single meta-learning framework. By leveraging few-shot learning, our approach enhances domain generalization and adaptability to domain shifts, enabling rapid adaptation to new datasets with minimal examples. Ice Finder's performance is evaluated on a comprehensive set of in situ datasets from EMPIAR, showcasing its ease of use, fast processing capabilities, and millisecond inference times.

FoldX force field revisited, an improved version

MOTIVATION

The FoldX force field was originally validated with a database of 1000 mutants at a time when there were few high-resolution structures. Here, we have manually curated a database of 5556 mutants affecting protein stability, resulting in 2484 highly confident mutations denominated FoldX stability dataset (FSD), represented in non-redundant X-ray structures with <2.5 Å resolution, not involving duplicates, metals, or prosthetic groups. Using this database, we have created a new version of the FoldX force field by introducing pi stacking, pH dependency for all charged residues, improving aromatic-aromatic interactions, modifying the Ncap contribution and α-helix dipole, recalibrating the side-chain entropy of methionine, adjusting the H-bond parameters, and modifying the solvation contribution of tryptophan and others.

RESULTS

These changes have led to significant improvements for the prediction of specific mutants involving the above residues/interactions and a statistically significant increase of FoldX predictions, as well as for the majority of the 20 aa. Removing all training sets data from FSD [Validation FoldX Stability Dataset (VFSD) dataset] resulted in improved predictions from R = 0.693 (RMSE = 1.277 kcal/mol) to R = 0.706 (RMSE = 1.252 kcal/mol) when compared with the previously released version. FoldX achieves 95% accuracy considering an error of ±0.85 kcal/mol in prediction and an area under the curve = 0.78 for the VFSD, predicting the sign of the energy change upon mutation.

AVAILABILITY AND IMPLEMENTATION

FoldX versions 4.1 and 5.1 are freely available for academics at https://foldxsuite.crg.eu/.

AlphaFold and what is next: bridging functional, systems and structural biology

INTRODUCTION

The DeepMind's AlphaFold (AF) has revolutionized biomedical and biocience research by providing both experts and non-experts with an invaluable tool for predicting protein structures. However, while AF is highly effective for predicting structures of rigid and globular proteins, it is not able to fully capture the dynamics, conformational variability, and interactions of proteins with ligands and other biomacromolecules.

AREAS COVERED

In this review, we present a comprehensive overview of the latest advancements in 3D model predictions for biomacromolecules using AF. We also provide a detailed analysis its of strengths and limitations, and explore more recent iterations, modifications, and practical applications of this strategy. Moreover, we map the path forward for expanding the landscape of AF toward predicting structures of every protein and peptide, and their interactions in the proteome in the most physiologically relevant form. This discussion is based on an extensive literature search performed using PubMed and Google Scholar.

EXPERT OPINION

While significant progress has been made to enhance AF's modeling capabilities, we argue that a combined approach integrating both various in silico and in vitro methods will be most beneficial for the future of structural biology, bridging the gaps between static and dynamic features of proteins and their functions.

Structural glycobiology - from enzymes to organelles

Biological carbohydrate polymers represent some of the most complex molecules in life, enabling their participation in a huge range of physiological functions. The complexity of biological carbohydrates arises from an extensive enzymatic repertoire involved in their construction, deconstruction and modification. Over the past decades, structural studies of carbohydrate processing enzymes have driven major insights into their mechanisms, supporting associated applications across medicine and biotechnology. Despite these successes, our understanding of how multienzyme networks function to create complex polysaccharides is still limited. Emerging techniques such as super-resolution microscopy and cryo-electron tomography are now enabling the investigation of native biological systems at near molecular resolutions. Here, we review insights from classical in vitro studies of carbohydrate processing, alongside recent in situ studies of glycosylation-related processes. While considerable technical challenges remain, the integration of molecular mechanisms with true biological context promises to transform our understanding of carbohydrate regulation, shining light upon the processes driving functional complexity in these essential biomolecules.

DNA Nanotags for Multiplexed Single-Particle Electron Microscopy and In Situ Electron Cryotomography

DNA nanostructures present new opportunities as Nanotags for electron microscopy (EM) imaging, leveraging their high programmability, unique shapes, biomolecule conjugation capability, and stability compatible with standard cryogenic sample preparation protocols. This perspective highlights the potential of DNA Nanotags to enable high-throughput multiplexed EM analysis and facilitate in situ particle identification for cryogenic electron tomography (cryo-ET). Meanwhile, applying Nanotags in live-cell environments requires the efficient cellular uptake of intact structures and successful cytosolic migration. Promising strategies such as employing direct cytosolic delivery platforms and expressing RNA-based Nanotags in situ are discussed, while more systematic studies are needed to fully understand the intracellular trafficking and achieve precise localization of DNA Nanotags.

Unravelling complex mechanisms in materials processes with cryogenic electron microscopy

Investigating nanoscale structural variations, including heterogeneities, defects, and interfacial characteristics, is crucial for gaining insight into material properties and functionalities. Cryogenic electron microscopy (cryo-EM) is developing as a powerful tool in materials science particularly for non-invasively understanding nanoscale structures of materials. These advancements bring us closer to the ultimate goal of correlating nanoscale structures to bulk functional outcomes. However, while understanding mechanisms from structural information requires analysis that closely mimics operation conditions, current challenges in cryo-EM imaging and sample preparation hinder the extraction of detailed mechanistic insights. In this Perspective, we discuss the innovative strategies and the potential for using cryo-EM for revealing mechanisms in materials science, with examples from high-resolution imaging, correlative elemental analysis, and three-dimensional and time-resolved analysis. Furthermore, we propose improvements in cryo-sample preparation, optimized instrumentation setup for imaging, and data interpretation techniques to enable the wider use of cryo-EM and achieve deeper context into materials to bridge structural observations with mechanistic understanding.

Molecular mechanisms of the GABA type A receptor function

The GABA type A receptor (GABAAR) belongs to the family of pentameric ligand-gated ion channels and plays a key role in inhibition in adult mammalian brains. Dysfunction of this macromolecule may lead to epilepsy, anxiety disorders, autism, depression, and schizophrenia. GABAAR is also a target for multiple physiologically and clinically relevant modulators, such as benzodiazepines (BDZs), general anesthetics, and neurosteroids. The first GABAAR structure appeared in 2014, but the past years have brought a particularly abundant surge in structural data for these receptors with various ligands and modulators. Although the open conformation remains elusive, this novel information has pushed the structure-function studies to an unprecedented level. Electrophysiology, mutagenesis, photolabeling, and in silico simulations, guided by novel structural information, shed new light on the molecular mechanisms of receptor functioning. The main goal of this review is to present the current knowledge of GABAAR functional and structural properties. The review begins with an outline of the functional and structural studies of GABAAR, accompanied by some methodological considerations, especially biophysical methods, enabling the reader to follow how major breakthroughs in characterizing GABAAR features have been achieved. The main section provides a comprehensive analysis of the functional significance of specific structural elements in GABAARs. We additionally summarize the current knowledge on the binding sites for major GABAAR modulators, referring to the molecular underpinnings of their action. The final chapter of the review moves beyond examining GABAAR as an isolated macromolecule and describes the interactions of the receptor with other proteins in a broader context of inhibitory plasticity. In the final section, we propose a general conclusion that agonist binding to the orthosteric binding sites appears to rely on local interactions, whereas conformational transitions of bound macromolecule (gating) and allosteric modulation seem to reflect more global phenomena involving vast portions of the macromolecule.

Standardizing experimental approaches to investigate interactions between bacteria and ectomycorrhizal fungi

Bacteria and ectomycorrhizal fungi (EcMF) represent two of the most dominant plant root-associated microbial groups on Earth, and their interactions continue to gain recognition as significant factors that shape forest health and resilience. Yet, we currently lack a focused review that explains the state of bacteria-EcMF interaction research in the context of experimental approaches and technological advancements. To these ends, we illustrate the utility of studying bacteria-EcMF interactions, detail outstanding questions, outline research priorities in the field, and provide a suite of approaches that can be used to promote experimental reproducibility, field advancement, and collaboration. Though this review centers on the ecology of bacteria, EcMF, and trees, it by default offers experimental and conceptual insights that can be adapted to various subfields of microbiology and microbial ecology.

High-resolution cryo-EM using a common LaB6 120-keV electron microscope equipped with a sub-200-keV direct electron detector

High-resolution cryo-electron microscopy (cryo-EM) requires costly 200- to 300-keV cryo-transmission electron microscopes (cryo-TEMs) with field emission gun (FEG) sources, stable columns, constant-powered lenses, autoloader, and direct electron detectors (DED). Recent advances in 100-keV imaging with the emergence of sub-200-keV optimized DED technology promises the development of more affordable cryo-TEMs. So far, 100-keV imaging has required microscopes with FEG sources. We here explored whether a standard 120-keV TEMs with thermionic lanthanum hexaboride (LaB6) source can be upgraded with a sub-200-keV DED for high-resolution cryo-EM. Using this imaging configuration, we successfully obtained a 2.65 Å reconstruction for apoferritin, 4.33 Å for 64-kDa hemoglobin, and 4.4 Å for an asymmetric 153kDa membrane protein GPCR. All results were achieved using standard automated data collection with SerialEM, demonstrating the feasibility to collect large cryo-EM datasets with a side-entry cryo-holder. These results showcase a widely accessible solution to obtaining interpretable cryo-EM structures at low cost and contribute to the "democratization" of cryo-EM.

Epitope mapping via in vitro deep mutational scanning methods and its applications

Epitope mapping is a technique employed to define the region of an antigen that elicits an immune response, providing crucial insight into the structural architecture of the antigen as well as epitope-paratope interactions. With this breadth of knowledge, immunotherapies, diagnostics, and vaccines are being developed with a rational and data-supported design. Traditional epitope mapping methods are laborious, time-intensive, and often lack the ability to screen proteins in a high-throughput manner or provide high resolution. Deep mutational scanning (DMS), however, is revolutionizing the field as it can screen all possible single amino acid mutations and provide an efficient and high-throughput way to infer the structures of both linear and three-dimensional epitopes with high resolution. Currently, more than 50 publications take this approach to efficiently identify enhancing or escaping mutations, with many then employing this information to rapidly develop broadly neutralizing antibodies, T-cell immunotherapies, vaccine platforms, or diagnostics. We provide a comprehensive review of the approaches to accomplish epitope mapping while also providing a summation of the development of DMS technology and its impactful applications.

Nuclear lipids in chromatin regulation: Biological roles, experimental approaches and existing challenges

Lipids are crucial for various cellular functions. Besides the storage of energy equivalents, these include forming membrane bilayers and serving as signaling molecules. While significant progress has been made in the comprehension of the molecular and cellular biology of lipids, their functions in the cell nucleus remain poorly understood. The main role of the eukaryotic cell nucleus is to provide an environment for the storage and regulation of chromatin which is a complex of DNA, histones, and associated proteins. Recent studies suggest that nuclear lipids play a role in chromatin regulation and epigenetics. Here, we discuss various experimental methods in lipid-chromatin research, including biophysical, structural, and cell biology approaches, pointing out their strengths and weaknesses. We take the view that nuclear lipids have a far more widespread impact on chromatin than is currently acknowledged. This gap in comprehension is mostly due to existing experimental challenges in the study of lipid-chromatin biology. Several new, interdisciplinary approaches are discussed that could aid in elucidating the roles of nuclear lipids in chromatin regulation and gene expression.

Exploiting fourth-generation synchrotron radiation for enzyme and photoreceptor characterization

The upgrade of the European Synchrotron Radiation Facility (ESRF) in Grenoble, France to an Extremely Brilliant Source (EBS) is expected to enable time-resolved synchrotron serial crystallography (SSX) experiments with sub-millisecond time resolution. ID29 is a new beamline dedicated to SSX experiments at ESRF-EBS. Here, we report experiments emerging from the initial phase of user operation at ID29. We first used microcrystals of photoactive yellow protein as a model system to exploit the potential of microsecond pulses for SSX. Subsequently, we investigated microcrystals of cytochrome c nitrite reductase (ccNiR) with microsecond X-ray pulses. CcNiR is a decaheme protein that is ideal for the investigation of radiation damage at the various heme-iron sites. Finally, we performed a proof-of-concept subsecond time-resolved SSX experiment by photoactivating microcrystals of a myxobacterial phytochrome.

Practical considerations for plunge freezing samples over 40 °C for Cryo-EM

Cryo-EM is now an established tool for examining samples in their native, hydrated states-a leap made possible by vitrification. Utilising this sample preparation method to directly visualise temperature-responsive samples allows for deeper insights into their structural behaviours under functional conditions. This requires samples to be plunge-frozen at elevated temperatures and presents additional challenges, including condensation within the blotting chamber and difficulties in maintaining a stable sample temperatures. Here, we address these challenges and suggest practical strategies to minimise condensation and reduce temperature fluctuations during the plunge-freezing of samples at elevated temperatures (>40 °C). By preheating equipment and reducing chamber humidity and blotting times, we can improve sample preservation and grid reproducibility. These considerations are then demonstrated on poly(N-isopropylacrylamide) microgels, which exhibit a volume phase transition due to temperature changes.

DiffFit: Visually-Guided Differentiable Fitting of Molecule Structures to a Cryo-EM Map

We introduce DiffFit, a differentiable algorithm for fitting protein atomistic structures into an experimental reconstructed Cryo-Electron Microscopy (cryo-EM) volume map. In structural biology, this process is necessary to semi-automatically composite large mesoscale models of complex protein assemblies and complete cellular structures that are based on measured cryo-EM data. The current approaches require manual fitting in three dimensions to start, resulting in approximately aligned structures followed by an automated fine-tuning of the alignment. The DiffFit approach enables domain scientists to fit new structures automatically and visualize the results for inspection and interactive revision. The fitting begins with differentiable three-dimensional (3D) rigid transformations of the protein atom coordinates followed by sampling the density values at the atom coordinates from the target cryo-EM volume. To ensure a meaningful correlation between the sampled densities and the protein structure, we proposed a novel loss function based on a multi-resolution volume-array approach and the exploitation of the negative space. This loss function serves as a critical metric for assessing the fitting quality, ensuring the fitting accuracy and an improved visualization of the results. We assessed the placement quality of DiffFit with several large, realistic datasets and found it to be superior to that of previous methods. We further evaluated our method in two use cases: automating the integration of known composite structures into larger protein complexes and facilitating the fitting of predicted protein domains into volume densities to aid researchers in identifying unknown proteins. We implemented our algorithm as an open-source plugin (github.com/nanovis/DiffFit) in ChimeraX, a leading visualization software in the field. All supplemental materials are available at osf. io/5tx4q.

Evaluating Cryo-TEM Reconstruction Accuracy of Self-Assembled Polymer Nanostructures

Cryogenic transmission electron microscopy (cryo-TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA-reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo-TEM 3D reconstructions of self-assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. These findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

Overcoming the preferred-orientation problem in cryo-EM with self-supervised deep learning

While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the 'preferred' orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep learning-based software to address map anisotropy and particle misalignment caused by the preferred-orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNet's ability to generate near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, β-galactosidases and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred-orientation problem.

Comparative Analysis of Symmetry Parameters in the E2 Inner Core of the Pyruvate Dehydrogenase Complex

Recent advances in cryo-electron microscopy (cryo-EM) have facilitated the high-resolution structural determination of macromolecular complexes in their native states, providing valuable insights into their dynamic behaviors. However, insufficient understanding or experience with the cryo-EM image processing parameters can result in the loss of biological meaning. In this paper, we investigate the dihydrolipoyl acetyltransferase (E2) inner core complex of the pyruvate dehydrogenase complex (PDC) and reconstruct the 3D maps using five different symmetry parameters. The results demonstrate that the reconstructions yield structurally identical 3D models even at a near-atomic structure. This finding underscores a crucial message for researchers engaging in single-particle analysis (SPA) with relatively user-friendly and convenient image processing software. This approach helps reduce the risk of missing critical biological details, such as the dynamic properties of macromolecules.

Cryo-EM reconstruction of helical polymers: Beyond the simple cases

Helices are one of the most frequently encountered symmetries in biological assemblies. Helical symmetry has been exploited in electron microscopic studies as a limited number of filament images, in principle, can provide all the information needed to do a three-dimensional reconstruction of a polymer. Over the past 25 years, three-dimensional reconstructions of helical polymers from cryo-EM images have shifted completely from Fourier-Bessel methods to single-particle approaches. The single-particle approaches have allowed people to surmount the problem that very few biological polymers are crystalline in order, and despite the flexibility and heterogeneity present in most of these polymers, reaching a resolution where accurate atomic models can be built has now become the standard. While determining the correct helical symmetry may be very simple for something like F-actin, for many other polymers, particularly those formed from small peptides, it can be much more challenging. This review discusses why symmetry determination can be problematic, and why trial-and-error methods are still the best approach. Studies of many macromolecular assemblies, such as icosahedral capsids, have usually found that not imposing symmetry leads to a great reduction in resolution while at the same time revealing possibly interesting asymmetric features. We show that for certain helical assemblies asymmetric reconstructions can sometimes lead to greatly improved resolution. Further, in the case of supercoiled flagellar filaments from bacteria and archaea, we show that the imposition of helical symmetry can not only be wrong, but is not necessary, and obscures the mechanisms whereby these filaments supercoil.

Advancing Single-Particle Analysis in Synthetic Chemical Systems: A Forward-Looking Discussion

Single-particle analysis (SPA) is a fundamental method of cryo-electron microscopy developed to resolve the structures of biological macromolecules. This method has seen significant success in structural biology, yet its potential applications in synthetic chemical systems remain underexplored. In this perspective article, SPA and associated electron microscopy techniques are first briefly introduced. It is then proposed that SPA is well-suited for structural analysis of chemical systems where discrete, identical macromolecules can be readily obtained. Applicable systems include various clusters such as coinage metal clusters, metal-oxo/sulfur clusters, metal-organic clusters, and supramolecular compounds like coordination cages and metallo-supramolecular cages. When high-quality large single crystals are unattainable, SPA provides an alternative method for determining their structures. Beyond these end products, it is suggested that SPA can be instrumental in studying synthetic intermediates of materials with specific building units, such as metal-organic frameworks and zeolites. Given that various intermediates coexist in the reaction system, a purification step is necessary before conducting SPA, which can be facilitated by soft-landing electrospray ionization mass spectrometry.

Cryo-EM phase-plate images reveal unexpected levels of apparent specimen damage

Apoferritin (apoF) is commonly used as a test specimen in single-particle electron cryo-microscopy (cryo-EM), since it consistently produces density maps that go to 3 Å resolution or higher. When we imaged apoF with a laser phase plate (LPP), however, we observed more severe particle-to-particle variation in the images than we had previously thought to exist. Similarly, we found that images of ribulose bisphosphate carboxylase/oxygenase (rubisco) also exhibited a much greater amount of heterogeneity than expected. By comparison to simulations of images, we verified that the heterogeneity is not explained by the known features of the LPP, shot noise, or differences in particle orientation. We also demonstrate that our specimens are comparable to those previously used in the literature, based on using the final-reconstruction resolution as the metric for evaluation. All of this leads us to the hypothesis that the heterogeneity is due to damage that has occurred either during purification of the specimen or during preparation of the grids. It is not, however, our goal to explain the causes of heterogeneity; rather, we report that using the LPP has made the apparent damage too obvious to be ignored. In hindsight, similar heterogeneity can be seen in images of apoF and the 20S proteasome which others had recorded with a Volta phase plate. We therefore conclude that the increased contrast of phase-plate images (at low spatial frequencies) should also make it possible to visualize, on a single-particle basis, various forms of biologically functional heterogeneity in structure that had previously gone unnoticed.

WUREN: Whole-modal union representation for epitope prediction

B-cell epitope identification plays a vital role in the development of vaccines, therapies, and diagnostic tools. Currently, molecular docking tools in B-cell epitope prediction are heavily influenced by empirical parameters and require significant computational resources, rendering a great challenge to meet large-scale prediction demands. When predicting epitopes from antigen-antibody complex, current artificial intelligence algorithms cannot accurately implement the prediction due to insufficient protein feature representations, indicating novel algorithm is desperately needed for efficient protein information extraction. In this paper, we introduce a multimodal model called WUREN (Whole-modal Union Representation for Epitope predictioN), which effectively combines sequence, graph, and structural features. It achieved AUC-PR scores of 0.213 and 0.193 on the solved structures and AlphaFold-generated structures, respectively, for the independent test proteins selected from DiscoTope3 benchmark. Our findings indicate that WUREN is an efficient feature extraction model for protein complexes, with the generalizable application potential in the development of protein-based drugs. Moreover, the streamlined framework of WUREN could be readily extended to model similar biomolecules, such as nucleic acids, carbohydrates, and lipids.

Revisiting sodium phosphotungstate and ammonium molybdate as nonradioactive negative-staining agents for single-particle analysis

This study reports the successful replacement of uranyl-based stains by either sodium phosphotungstate or ammonium molybdate in negative-staining electron microscopy. Using apoferritin as a test specimen, it is demonstrated that in combination with a facile on-grid fixation step, both stains yield comparable images to uranyl formate. Subsequently, using β-galactosidase, it is shown that both stains can also successfully be employed for single-particle analysis, yielding virtually indistinguishable results from uranyl formate. As both replacement stains are nonradioactive, they are not subjected to the same handling restrictions as uranyl-based stains. Therefore they are not only cheaper to use, but also make decentralized sample-grid preparation, directly after purification, accessible to a broader range of scientists.

Recent advances in correlative cryo-light and electron microscopy

Correlative light and electron microscopy (CLEM) pipelines serve to integrate the imaging modalities of fluorescence light microscopy (FLM) and cryogenic electron microscopy (cryo-EM) to produce contextually relevant high-resolution structural snapshots of biological systems. Innovations in sample preparation, instrumentation, imaging, and data processing have advanced the field of cryo-EM. This review focuses on prior work and recent developments in the field of cryo- EM that support further integration of technologies for correlative microscopy workflows.

Laser Flash Melting Cryo-EM Samples to Overcome Preferred Orientation

Sample preparation remains a bottleneck for protein structure determination by cryo-electron microscopy. A frequently encountered issue is that proteins adsorb to the air-water interface of the sample in a limited number of orientations. This makes it challenging to obtain high-resolution reconstructions or may even cause projects to fail altogether. We have previously observed that laser flash melting and revitrification of cryo samples reduces preferred orientation for large, symmetric particles. Here, we demonstrate that our method can in fact be used to scramble the orientation of proteins of a range of sizes and symmetries. The effect can be enhanced for some proteins by increasing the heating rate during flash melting or by depositing amorphous ice onto the sample prior to revitrification. This also allows us to shed light onto the underlying mechanism. Our experiments establish a set of tools for overcoming preferred orientation that can be easily integrated into existing workflows.

Automated identification of small molecules in cryo-electron microscopy data with density- and energy-guided evaluation

Methodological improvements in cryo-electron microscopy (cryoEM) have made it a useful tool in ligand-bound structure determination for biology and drug design. However, determining the conformation and identity of bound ligands is still challenging at the resolutions typical for cryoEM. Automated methods can aid in ligand conformational modeling, but current ligand identification tools - developed for X-ray crystallography data - perform poorly at resolutions common for cryoEM. Here, we present EMERALD-ID, a method capable of docking and evaluating small molecule conformations for ligand identification. EMERALD-ID identifies 43% of common ligands exactly and identifies closely related ligands in 66% of cases. We then use this tool to discover possible ligand identification errors, as well as previously unidentified ligands. Furthermore, we show EMERALD-ID is capable of identifying ligands from custom ligand libraries of various small molecule types, including human metabolites and drug fragments. Our method provides a valuable addition to cryoEM modeling tools to improve small molecule model accuracy and quality.

Gatekeepers of the brain: Identifying hidden mechanisms of type A GABA receptor signaling and assembly

Identifying hidden mechanisms of type A GABA receptor signaling and assembly.

Molecular glues that inhibit deubiquitylase activity and inflammatory signalling

Deubiquitylases (DUBs) are crucial in cell signalling and are often regulated by interactions within protein complexes. The BRCC36 isopeptidase complex (BRISC) regulates inflammatory signalling by cleaving K63-linked polyubiquitin chains on Type I interferon receptors (IFNAR1). As a Zn2+-dependent JAMM/MPN DUB, BRCC36 is challenging to target with selective inhibitors. We discovered first-in-class inhibitors, termed BRISC molecular glues (BLUEs), which stabilise a 16-subunit BRISC dimer in an autoinhibited conformation, blocking active sites and interactions with the targeting subunit SHMT2. This unique mode of action results in selective inhibition of BRISC over related complexes with the same catalytic subunit, splice variants and other JAMM/MPN DUBs. BLUE treatment reduced interferon-stimulated gene expression in cells containing wild type BRISC, and this effect was absent when using structure-guided, inhibitor-resistant BRISC mutants. Additionally, BLUEs increase IFNAR1 ubiquitylation and decrease IFNAR1 surface levels, offering a potential new strategy to mitigate Type I interferon-mediated diseases. Our approach also provides a template for designing selective inhibitors of large protein complexes by promoting, rather than blocking, protein-protein interactions.

3D Cryo-Electron Microscopy Reveals the Structure of a 3-Fluorenylmethyloxycarbonyl Zipper Motif Ensuring the Self-Assembly of Tripeptide Nanofibers

Short peptide-based supramolecular hydrogels appeared as highly interesting materials for applications in many fields. The optimization of their properties relies mainly on the design of a suitable hydrogelator through an empirical trial-and-error strategy based on the synthesis of various types of peptides. This approach is in part due to the lack of prior structural knowledge of the molecular architecture of the various families of nanofibers. The 3D structure of the nanofibers determines their ability to interact with entities present in their surrounding environment. Thus, it is important to resolve the internal structural organization of the material. Herein, using Fmoc-FFY tripeptide as a model amphiphilic hydrogelator and cryo-EM reconstruction approach, we succeeded to obtain a 3.8 Å resolution 3D structure of a self-assembled nanofiber with a diameter of approximately 4.1 nm and with apparently "infinite" length. The elucidation of the spatial organization of such nano-objects addresses fundamental questions about the way short amphiphilic N-Fmoc peptides lacking secondary structure can self-assemble and ensure the cohesion of such a lengthy nanostructure. This nanofiber is organized into a triple-stranded helix with an asymmetric unit composed of two Fmoc-FFY peptides per strand. The three identical amphiphilic strands are maintained together by strong lateral interactions coming from a 3-Fmoc zipper motif. This hydrophobic core of the nanofiber is surrounded by 12 phenyl groups from phenylalanine residues, nonplanar with the six Fmoc groups. Polar tyrosine residues at the C-term position constitute the hydrophilic shell and are exposed all around the external part of the assembly. This fiber has a highly hydrophobic central core with an internal diameter of only 2.4 Å. Molecular dynamics simulations highlight van der Waals and hydrogen bonds between peptides placed on top of each other. We demonstrate that the self-assembly of Fmoc-FFY, whether induced by annealing or by the action of a phosphatase on the phosphorylated precursor Fmoc-FFpY, results in two nanostructures with minor differences that we are unable to distinguish.

Orientation Determination of Cryo-EM Projection Images Using Reliable Common Lines and Spherical Embeddings

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a critical technique for recovering and studying the fine 3D structure of proteins and other biological macromolecules, where the primary issue is to determine the orientations of projection images with high levels of noise. This paper proposes a method to determine the orientations of cryo-EM projection images using reliable common lines and spherical embeddings. First, the reliability of common lines between projection images is evaluated using a weighted voting algorithm based on an iterative improvement technique and binarized weighting. Then, the reliable common lines are used to calculate the normal vectors and local -axis vectors of projection images after two spherical embeddings. Finally, the orientations of projection images are determined by aligning the results of the two spherical embeddings using an orthogonal constraint. Experimental results on both synthetic and real cryo-EM projection image datasets demonstrate that the proposed method can achieve higher accuracy in estimating the orientations of projection images and higher resolution in reconstructing preliminary 3D structures than some common line-based methods, indicating that the proposed method is effective in single-particle cryo-EM 3D reconstruction.