Challenges and opportunities in cryo-EM single-particle analysis

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.

The CryoEM structure of human serum albumin in complex with ligands

Human serum albumin (HSA) is the most prevalent plasma protein in the human body, accounting for 60 % of the total plasma protein. HSA plays a major pharmacokinetic function, serving as a facilitator in the distribution of endobiotics and xenobiotics within the organism. In this paper we report the cryoEM structures of HSA in the apo form and in complex with two ligands (salicylic acid and teniposide) at a resolution of 3.5, 3.7 and 3.4 Å, respectively. We expand upon previously published work and further demonstrate that sub-4 Å maps of ∼60 kDa proteins can be routinely obtained using a 200 kV microscope, employing standard workflows. Most importantly, these maps allowed for the identification of small molecule ligands, emphasizing the practical applicability of this methodology and providing a starting point for subsequent computational modeling and in silico optimization.

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.

Structural biology and molecular pharmacology of voltage-gated ion channels

Voltage-gated ion channels (VGICs), including those for Na+, Ca2+ and K+, selectively permeate ions across the cell membrane in response to changes in membrane potential, thus participating in physiological processes involving electrical signalling, such as neurotransmission, muscle contraction and hormone secretion. Aberrant function or dysregulation of VGICs is associated with a diversity of neurological, psychiatric, cardiovascular and muscular disorders, and approximately 10% of FDA-approved drugs directly target VGICs. Understanding the structure-function relationship of VGICs is crucial for our comprehension of their working mechanisms and role in diseases. In this Review, we discuss how advances in single-particle cryo-electron microscopy have afforded unprecedented structural insights into VGICs, especially on their interactions with clinical and investigational drugs. We present a comprehensive overview of the recent advances in the structural biology of VGICs, with a focus on how prototypical drugs and toxins modulate VGIC activities. We explore how these structures elucidate the molecular basis for drug actions, reveal novel pharmacological sites, and provide critical clues to future drug discovery.

Bayesian reweighting of biomolecular structural ensembles using heterogeneous cryo-EM maps with the cryoENsemble method

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for the determination of structures of complex biological molecules. The accurate characterisation of the dynamics of such systems, however, remains a challenge. To address this problem, we introduce cryoENsemble, a method that applies Bayesian reweighting to conformational ensembles derived from molecular dynamics simulations to improve their agreement with cryo-EM data, thus enabling the extraction of dynamics information. We illustrate the use of cryoENsemble to determine the dynamics of the ribosome-bound state of the co-translational chaperone trigger factor (TF). We also show that cryoENsemble can assist with the interpretation of low-resolution, noisy or unaccounted regions of cryo-EM maps. Notably, we are able to link an unaccounted part of the cryo-EM map to the presence of another protein (methionine aminopeptidase, or MetAP), rather than to the dynamics of TF, and model its TF-bound state. Based on these results, we anticipate that cryoENsemble will find use for challenging heterogeneous cryo-EM maps for biomolecular systems encompassing dynamic components.

Correction of preferred orientation-induced distortion in cryo-electron microscopy maps

Reconstruction maps of cryo-electron microscopy (cryo-EM) exhibit distortion when the cryo-EM dataset is incomplete, usually caused by unevenly distributed orientations. Prior efforts had been attempted to address this preferred orientation problem using tilt-collection strategy and modifications to grids or to air-water interfaces. However, these approaches often require time-consuming experiments, and the effect was always protein dependent. Here, we developed a procedure containing removing misaligned particles and an iterative reconstruction method based on signal-to-noise ratio of Fourier component to correct this distortion by recovering missing data using a purely computational algorithm. This procedure called signal-to-noise ratio iterative reconstruction method (SIRM) was applied on incomplete datasets of various proteins to fix distortion in cryo-EM maps and to a more isotropic resolution. In addition, SIRM provides a better reference map for further reconstruction refinements, resulting in an improved alignment, which ultimately improves map quality and benefits model building.

Factors affecting macromolecule orientations in thin films formed in cryo-EM

The formation of a vitrified thin film embedded with randomly oriented macromolecules is an essential prerequisite for cryogenic sample electron microscopy. Most commonly, this is achieved using the plunge-freeze method first described nearly 40 years ago. Although this is a robust method, the behaviour of different macromolecules shows great variation upon freezing and often needs to be optimized to obtain an isotropic, high-resolution reconstruction. For a macromolecule in such a film, the probability of encountering the air-water interface in the time between blotting and freezing and adopting preferred orientations is very high. 3D reconstruction using preferentially oriented particles often leads to anisotropic and uninterpretable maps. Currently, there are no general solutions to this prevalent issue, but several approaches largely focusing on sample preparation with the use of additives and novel grid modifications have been attempted. In this study, the effect of physical and chemical factors on the orientations of macromolecules was investigated through an analysis of selected well studied macromolecules, and important parameters that determine the behaviour of proteins on cryo-EM grids were revealed. These insights highlight the nature of the interactions that cause preferred orientations and can be utilized to systematically address orientation bias for any given macromolecule and to provide a framework to design small-molecule additives to enhance sample stability and behaviour.

Time-resolved cryogenic electron tomography for the study of transient cellular processes

Cryogenic electron tomography (cryo-ET) is the highest resolution imaging technique applicable to the life sciences, enabling subnanometer visualization of specimens preserved in their near native states. The rapid plunge freezing process used to prepare samples lends itself to time-resolved studies, which researchers have pursued for in vitro samples for decades. Here, we focus on developing a freezing apparatus for time-resolved studies in situ. The device mixes cellular samples with solution-phase stimulants before spraying them directly onto an electron microscopy grid that is transiting into cryogenic liquid ethane. By varying the flow rates of cell and stimulant solutions within the device, we can control the reaction time from tens of milliseconds to over a second before freezing. In a proof-of-principle demonstration, the freezing method is applied to a model bacterium, Caulobacter crescentus, mixed with an acidic buffer. Through cryo-ET we resolved structural changes throughout the cell, including surface-layer protein dissolution, outer membrane deformation, and cytosolic rearrangement, all within 1.5 s of reaction time. This new approach, Time-Resolved cryo-ET (TR-cryo-ET), enhances the capabilities of cryo-ET by incorporating a subsecond temporal axis and enables the visualization of induced structural changes at the molecular, organelle, or cellular level.

An immobilized antibody-based affinity grid strategy for on-grid purification of target proteins enables high-resolution cryo-EM

In cryo-electron microscopy (cryo-EM), sample preparation poses a critical bottleneck, particularly for rare or fragile macromolecular assemblies and those suffering from denaturation and particle orientation distribution issues related to air-water interface. In this study, we develop and characterize an immobilized antibody-based affinity grid (IAAG) strategy based on the high-affinity PA tag/NZ-1 antibody epitope tag system. We employ Pyr-NHS as a linker to immobilize NZ-1 Fab on the graphene oxide or carbon-covered grid surface. Our results demonstrate that the IAAG grid effectively enriches PA-tagged target proteins and overcomes preferred orientation issues. Furthermore, we demonstrate the utility of our IAAG strategy for on-grid purification of low-abundance target complexes from cell lysates, enabling atomic resolution cryo-EM. This approach greatly streamlines the purification process, reduces the need for large quantities of biological samples, and addresses common challenges encountered in cryo-EM sample preparation. Collectively, our IAAG strategy provides an efficient and robust means for combined sample purification and vitrification, feasible for high-resolution cryo-EM. This approach holds potential for broader applicability in both cryo-EM and cryo-electron tomography (cryo-ET).

Mitigating the Blurring Effect of CryoEM Averaging on a Flexible and Highly Symmetric Protein Complex through Sub-Particle Reconstruction

Many macromolecules are inherently flexible as a feature of their structure and function. During single-particle CryoEM processing, flexible protein regions can be detrimental to high-resolution reconstruction as signals from thousands of particles are averaged together. This "blurring" effect can be difficult to overcome and is possibly more pronounced when averaging highly symmetric complexes. Approaches to mitigating flexibility during CryoEM processing are becoming increasingly critical as the technique advances and is applied to more dynamic proteins and complexes. Here, we detail the use of sub-particle averaging and signal subtraction techniques to precisely target and resolve flexible DARPin protein attachments on a designed tetrahedrally symmetric protein scaffold called DARP14. Particles are first aligned as full complexes, and then the symmetry is reduced by alignment and focused refinement of the constituent subunits. The final reconstructions we obtained were vastly improved over the fully symmetric reconstructions, with observable secondary structure and side-chain placement. Additionally, we were also able to reconstruct the core region of the scaffold to 2.7 Å. The data processing protocol outlined here is applicable to other dynamic and symmetric protein complexes, and our improved maps could allow for new structure-guided variant designs of DARP14.

Four-dimensional imaging for cryo-electron microscopy experiments using molecular simulations and manifold learning

Elucidating protein conformational changes is essential because conformational changes are closely related to the functions of proteins. Cryo-electron microscopy (cryo-EM) experiment can be used to reconstruct protein conformational changes via a method that involves using the experimental data (two-dimensional protein images). In this study, a reconstruction method, referred to as the "four-dimensional imaging," was proposed. In our four-dimensional imaging technique, the protein conformational change was obtained using the two-dimensional protein images (the three-dimensional electron density maps used in previously proposed techniques were not used). The protein conformation for each two-dimensional protein image was obtained using our original protocol with molecular dynamics simulations. Using a manifold-learning technique and two-dimensional protein images, the protein conformations were arranged according to the conformational change of the protein. By arranging the protein conformations according to the arrangement of the protein images, four-dimensional imaging is constructed. A simulation for a cryo-EM experiment demonstrated the validity of our four-dimensional imaging technique.

Phospholipid Complex Formulation Technology for Improved Drug Delivery in Oncological Settings: a Comprehensive Review

Addressing poor solubility and permeability issues associated with synthetic drugs and naturally occurring active compounds is crucial for improving bioavailability. This review explores the potential of phospholipid complex formulation technology to overcome these challenges. Phospholipids, as endogenous molecules, offer a viable solution, with drugs complexed with phospholipids demonstrating a similar absorption mechanism. The non-toxic and biodegradable nature of the phospholipid complex positions it as an ideal candidate for drug delivery. This article provides a comprehensive exploration of the mechanisms underlying phospholipid complexes. Special emphasis is placed on the solvent evaporation method, with meticulous scrutiny of formulation aspects such as the phospholipid ratio to the drug and solvent. Characterization techniques are employed to understand structural and functional attributes. Highlighting the adaptability of the phospholipid complex, the review discusses the loading of various nanoformulations and emulsion systems. These strategies aim to enhance drug delivery and efficacy in various malignancies, including breast, liver, lung, cervical, and pancreatic cancers. The broader application of the drug phospholipid complex is showcased, emphasizing its adaptability in diverse oncological settings. The review not only explores the mechanisms and formulation aspects of phospholipid complexes but also provides an overview of key clinical studies and patents. These insights contribute to the intellectual and translational advancements in drug phospholipid complexes.

Structural and quantum chemical basis for OCP-mediated quenching of phycobilisomes

Cyanobacteria use large antenna complexes called phycobilisomes (PBSs) for light harvesting. However, intense light triggers non-photochemical quenching, where the orange carotenoid protein (OCP) binds to PBS, dissipating excess energy as heat. The mechanism of efficiently transferring energy from phycocyanobilins in PBS to canthaxanthin in OCP remains insufficiently understood. Using cryo-electron microscopy, we unveiled the OCP-PBS complex structure at 1.6- to 2.1-angstrom resolution, showcasing its inherent flexibility. Using multiscale quantum chemistry, we disclosed the quenching mechanism. Identifying key protein residues, we clarified how canthaxanthin's transition dipole moment in its lowest-energy dark state becomes large enough for efficient energy transfer from phycocyanobilins. Our energy transfer model offers a detailed understanding of the atomic determinants of light harvesting regulation and antenna architecture in cyanobacteria.

EMinsight: a tool to capture cryoEM microscope configuration and experimental outcomes for analysis and deposition

The widespread adoption of cryoEM technologies for structural biology has pushed the discipline to new frontiers. A significant worldwide effort has refined the single-particle analysis (SPA) workflow into a reasonably standardized procedure. Significant investments of development time have been made, particularly in sample preparation, microscope data-collection efficiency, pipeline analyses and data archiving. The widespread adoption of specific commercial microscopes, software for controlling them and best practices developed at facilities worldwide has also begun to establish a degree of standardization to data structures coming from the SPA workflow. There is opportunity to capitalize on this moment in the maturation of the field, to capture metadata from SPA experiments and correlate the metadata with experimental outcomes, which is presented here in a set of programs called EMinsight. This tool aims to prototype the framework and types of analyses that could lead to new insights into optimal microscope configurations as well as to define methods for metadata capture to assist with the archiving of cryoEM SPA data. It is also envisaged that this tool will be useful to microscope operators and facilities looking to rapidly generate reports on SPA data-collection and screening sessions.

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

DeepQs: Local quality assessment of cryo-EM density map by deep learning map-model fit score

Cryogenic electron microscopy maps are valuable for determining macromolecule structures. A proper quality assessment method is essential for cryo-EM map selection or revision. This article presents DeepQs, a novel approach to estimate local quality for 3D cryo-EM density maps, using a deep-learning algorithm based on map-model fit score. DeepQs is a parameter-free method for users and incorporates structural information between map and its related atomic model into well-trained models by deep learning. More specifically, the DeepQs approach leverages the interplay between map and atomic model through predefined map-model fit score, Q-score. DeepQs can get close results to the ground truth map-model fit scores with only cryo-EM map as input. In experiments, DeepQs demonstrates the lowest root mean square error with standard method Fourier shell correlation metric and high correlation with map-model fit score, Q-score, when compared with other local quality estimation methods in high-resolution dataset (<=5 Å). DeepQs can also be applied to evaluate the quality of the post-processed maps. In both cases, DeepQs runs faster by using GPU acceleration. Our program is available at http://www.csbio.sjtu.edu.cn/bioinf/DeepQs for academic use.

Probing Molecular Packing of Lipid Nanoparticles from 31P Solution and Solid-State NMR

Lipid nanoparticles (LNPs) are intricate multicomponent systems widely recognized for their efficient delivery of oligonucleotide cargo to host cells. Gaining insights into the molecular properties of LNPs is crucial for their effective design and characterization. However, analysis of their internal structure at the molecular level presents a significant challenge. This study introduces 31P nuclear magnetic resonance (NMR) methods to acquire structural and dynamic information about the phospholipid envelope of LNPs. Specifically, we demonstrate that the 31P chemical shift anisotropy (CSA) parameters serve as a sensitive indicator of the molecular assembly of distearoylphosphatidylcholine (DSPC) lipids within the particles. An analytical protocol for measuring 31P CSA is developed, which can be implemented using either solution NMR or solid-state NMR, offering wide accessibility and adaptability. The capability of this method is demonstrated using both model DSPC liposomes and real-world pharmaceutical LNP formulations. Furthermore, our method can be employed to investigate the impact of formulation processes and composition on the assembly of specifically LNP particles or, more generally, phospholipid-based delivery systems. This makes it an indispensable tool for evaluating critical pharmaceutical properties such as structural homogeneity, batch-to-batch reproducibility, and the stability of the particles.

Integrative approaches for characterizing protein dynamics: NMR, CryoEM, and computer simulations

Proteins are inherently dynamic and their internal motions are essential for biological function. Protein motions cover a broad range of timescales: 10-14-10 s, spanning from sub-picosecond vibrational motions of atoms via microsecond loop conformational rearrangements to millisecond large amplitude domain reorientations. Observing protein dynamics over all timescales and connecting motions and structure to biological mechanisms requires integration of multiple experimental and computational techniques. This review reports on state-of-the-art approaches for assessing dynamics in biological systems using recent examples of virus assemblies, enzymes, and molecular machines. By integrating NMR spectroscopy in solution and the solid state, cryo electron microscopy, and molecular dynamics simulations, atomistic pictures of protein motions are obtained, not accessible from any single method in isolation. This information provides fundamental insights into protein behavior that can guide the development of future therapeutics.

A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction

Cryo-Electron Microscopy (cryo-EM) is a widely used and effective method for determining the three-dimensional (3D) structure of biological molecules. For ab-initio Cryo-EM 3D reconstruction using single particle analysis (SPA), estimating the projection direction of the projection image is a crucial step. However, the existing SPA methods based on common lines are sensitive to noise. The error in common line detection will lead to a poor estimation of the projection directions and thus may greatly affect the final reconstruction results. To improve the reconstruction results, multiple candidate common lines are estimated for each pair of projection images. The key problem then becomes a combination optimization problem of selecting consistent common lines from multiple candidates. To solve the problem efficiently, a physics-inspired method based on a kinetic model is proposed in this work. More specifically, hypothetical attractive forces between each pair of candidate common lines are used to calculate a hypothetical torque exerted on each projection image in the 3D reconstruction space, and the rotation under the hypothetical torque is used to optimize the projection direction estimation of the projection image. This way, the consistent common lines along with the projection directions can be found directly without enumeration of all the combinations of the multiple candidate common lines. Compared with the traditional methods, the proposed method is shown to be able to produce more accurate 3D reconstruction results from high noise projection images. Besides the practical value, the proposed method also serves as a good reference for solving similar combinatorial optimization problems.

Overcoming resolution attenuation during tilted cryo-EM data collection

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation, containing an unnatural nucleotide for studying novel base pair recognition. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle during data acquisition. These results reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

Metallo-supramolecular branched polymer protects particles from air-water interface in single-particle cryo-electron microscopy

Recent technological breakthroughs in single-particle cryo-electron microscopy (cryo-EM) enable rapid atomic structure determination of biological macromolecules. A major bottleneck in the current single particle cryo-EM pipeline is the preparation of good quality frozen cryo-EM grids, which is mostly a trial-and-error process. Among many issues, preferred particle orientation and sample damage by air-water interface (AWI) are common practical problems. Here we report a method of applying metallo-supramolecular branched polymer (MSBP) in the cryo-sample preparation for high-resolution single-particle cryo-EM. Our data shows that MSBP keeps a majority of particles away from air-water interface and mitigates preferred orientation as verified by the analyses of apoferritin, hemagglutinin) trimer and various sample proteins. The use of MSBP is a simple method to improve particle distribution for high-resolution structure determination in single-particle cryo-EM.

C-SPAM: an open-source time-resolved specimen vitrification device with light-activated molecules

Molecular structures can be determined in vitro and in situ with cryo-electron microscopy (cryo-EM). Specimen preparation is a major obstacle in cryo-EM. Typical sample preparation is orders of magnitude slower than biological processes. Time-resolved cryo-EM (TR-cryo-EM) can capture short-lived states. Here, Cryo-EM sample preparation with light-activated molecules (C-SPAM) is presented, an open-source, photochemistry-coupled device for TR-cryo-EM that enables millisecond resolution and tunable timescales across broad biological applications.

Preparation and characterization of inactivated tick-borne encephalitis virus samples for single-particle imaging at the European XFEL

X-ray imaging of virus particles at the European XFEL could eventually allow their complete structures to be solved, potentially approaching the resolution of other structural virology methods. To achieve this ambitious goal with today's technologies, about 1 ml of purified virus suspension containing at least 1012 particles per millilitre is required. Such large amounts of concentrated suspension have never before been obtained for enveloped viruses. Tick-borne encephalitis virus (TBEV) represents an attractive model system for the development of enveloped virus purification and concentration protocols, given the availability of large amounts of inactivated virus material provided by vaccine-manufacturing facilities. Here, the development of a TBEV vaccine purification and concentration scheme is presented combined with a quality-control protocol that allows substantial amounts of highly concentrated non-aggregated suspension to be obtained. Preliminary single-particle imaging experiments were performed for this sample at the European XFEL, showing distinct diffraction patterns.

Emerging Trends in Cryo-EM-based Structural Studies of Neuropathological Amyloids

Tauopathies, synucleinopathies, Aβ amyloidosis, TDP-43 proteinopathies, and prion diseases- these neurodegenerative diseases have in common the formation of amyloid filaments rich in cross-β sheets. Cryo-electron microscopy now permits the visualization of amyloid assemblies at atomic resolution, ushering a wide range of structural studies on several of these poorly understood amyloidogenic proteins. Amyloids are polymorphic with minor modulations in reaction environment affecting the overall architecture of their assembly, making amyloids an extremely challenging venture for structure-based therapeutic intervention. In 2017, the first cryo-EM structure of tau filaments from an Alzheimer's disease-affected brain established that in vitro assemblies might not necessarily reflect the native amyloid fold. Since then, brain-derived amyloid structures for several proteins across many neurodegenerative diseases have uncovered the disease-relevant amyloid folds. It has now been shown for tauopathies, synucleinopathies and TDP-43 proteinopathies, that distinct amyloid folds of the same protein might be related to different diseases. Salient features of each of these brain-derived folds are discussed in detail. It was also recently observed that seeded aggregation does not necessarily replicate the brain-derived structural fold. Owing to high throughput structure determination, some of these native amyloid folds have also been successfully replicated in vitro. In vitro replication of disease-relevant filaments will aid development of imaging ligands and defibrillating drugs. Towards this direction, recent high-resolution structures of tau filaments with positron emission tomography tracers and a defibrillating drug are also discussed. This review summarizes and celebrates the recent advancements in structural understanding of neuropathological amyloid filaments using cryo-EM.

Scaling up cryo-EM for biology and chemistry: The journey from niche technology to mainstream method

Cryoelectron microscopy (cryo-EM) methods have made meaningful contributions in a wide variety of scientific research fields. In structural biology, cryo-EM routinely elucidates molecular structure from isolated biological macromolecular complexes or in a cellular context by harnessing the high-resolution power of the electron in order to image samples in a frozen, hydrated environment. For structural chemistry, the cryo-EM method popularly known as microcrystal electron diffraction (MicroED) has facilitated atomic structure generation of peptides and small molecules from their three-dimensional crystal forms. As cryo-EM has grown from an emerging technology, it has undergone modernization to enable multimodal transmission electron microscopy (TEM) techniques becoming more routine, reproducible, and accessible to accelerate research across multiple disciplines. We review recent advances in modern cryo-EM and assess how they are contributing to the future of the field with an eye to the past.

Mass spectrometers as cryoEM grid preparation instruments

Structure determination by single-particle cryoEM has matured into a core structural biology technique. Despite many methodological advancements, most cryoEM grids are still prepared using the plunge-freezing method developed ∼40 years ago. Embedding samples in thin films and exposing them to the air-water interface often leads to sample damage and preferential orientation of the particles. Using native mass spectrometry to create cryoEM samples, potentially avoids these problems and allows the use of mass spectrometry sample isolation techniques during EM grid creation. We review the recent publications that have demonstrated protein complexes can be ionized, flown through the mass spectrometer, gently landed onto EM grids, imaged, and reconstructed in 3D. Although many uncertainties and challenges remain, the combination of cryoEM and MS has great potential.

High Affinity Electrostatic Interactions Support the Formation of CdS Quantum Dot:Nitrogenase MoFe Protein Complexes

Nitrogenase MoFe protein can be coupled with CdS nanocrystals (NCs) to enable photocatalytic N2 reduction. The nature of interactions that support complex formation is of paramount importance in intermolecular electron transfer that supports catalysis. In this work we have employed microscale thermophoresis to examine binding interactions between 3-mercaptopropionate capped CdS quantum dots (QDs) and MoFe protein over a range of QD diameters (3.4-4.3 nm). The results indicate that the interactions are largely electrostatic, with the strength of interactions similar to that observed for the physiological electron donor. In addition, the strength of interactions is sensitive to the QD diameter, and the binding interactions are significantly stronger for QDs with smaller diameters. The ability to quantitatively assess NC protein interactions in biohybrid systems supports strategies for understanding properties and reaction parameters that are important for obtaining optimal rates of catalysis in biohybrid systems.

Liquid Transmission Electron Microscopy for Probing Collagen Biomineralization

Collagen biomineralization is fundamental to hard tissue assembly. While studied extensively, collagen mineralization processes are not fully understood, with the majority of theories derived from electron microscopy (EM) under static, dehydrated, or frozen conditions, unlike the liquid phase environment where mineralization occurs. Herein, novel liquid transmission EM (TEM) strategies are presented, in which collagen mineralization was explored in liquid for the first time via TEM. Custom thin-film enclosures were employed to visualize the mineralization of reconstituted collagen fibrils in a calcium phosphate and polyaspartic acid solution to promote intrafibrillar mineralization. TEM highlighted that at early time points precursor mineral particles attached to collagen and progressed to crystalline mineral platelets aligned with fibrils at later time points. This aligns with observations from other techniques and validates the liquid TEM approach. This work provides a new liquid imaging approach for exploring collagen biomineralization, advancing toward understanding disease pathogenesis and remineralization strategies for hard tissues.

Advanced Techniques for Detecting Protein Misfolding and Aggregation in Cellular Environments

Protein misfolding and aggregation, a key contributor to the progression of numerous neurodegenerative diseases, results in functional deficiencies and the creation of harmful intermediates. Detailed visualization of this misfolding process is of paramount importance for improving our understanding of disease mechanisms and for the development of potential therapeutic strategies. While in vitro studies using purified proteins have been instrumental in delivering significant insights into protein misfolding, the behavior of these proteins in the complex milieu of living cells often diverges significantly from such simplified environments. Biomedical imaging performed in cell provides cellular-level information with high physiological and pathological relevance, often surpassing the depth of information attainable through in vitro methods. This review highlights a variety of methodologies used to scrutinize protein misfolding within biological systems. This includes optical-based methods, strategies leaning on mass spectrometry, in-cell nuclear magnetic resonance, and cryo-electron microscopy. Recent advancements in these techniques have notably deepened our understanding of protein misfolding processes and the features of the resulting misfolded species within living cells. The progression in these fields promises to catalyze further breakthroughs in our comprehension of neurodegenerative disease mechanisms and potential therapeutic interventions.

Theoretical framework and experimental solution for the air-water interface adsorption problem in cryoEM

As cryogenic electron microscopy (cryoEM) gains traction in the structural biology community as a method of choice for determining atomic structures of biological complexes, it has been increasingly recognized that many complexes that behave well under conventional negative-stain electron microscopy tend to have preferential orientation, aggregate or simply mysteriously "disappear" on cryoEM grids, but the reasons for such misbehavior are not well understood, limiting systematic approaches to solving the problem. Here, we have developed a theoretical formulation that explains these observations. Our formulation predicts that all particles migrate to the air-water interface (AWI) to lower the total potential surface energy - rationalizing the use of surfactant, which is a direct solution to reducing the surface tension of the aqueous solution. By conducting cryogenic electron tomography (cryoET) with the widely-tested sample, GroEL, we demonstrate that, in a standard buffer solution, nearly all particles migrate to the AWI. Gradual reduction of the surface tension by introducing surfactants decreased the percentage of particles exposed to the surface. By conducting single-particle cryoEM, we confirm that applicable surfactants do not damage the biological complex, thus suggesting that they might offer a practical, simple, and general solution to the problem for high-resolution cryoEM. Application of this solution to a real-world AWI adsorption problem with a more challenging membrane protein, namely, the ClC-1 channel, has led to its first near-atomic structure using cryoEM.

Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics

In eukaryotic cells, membrane proteins play a crucial role. They fall into three categories: intrinsic proteins, extrinsic proteins, and proteins that are essential to the human genome (30% of which is devoted to encoding them). Hydrophobic interactions inside the membrane serve to stabilize integral proteins, which span the lipid bilayer. This review investigates a number of computational and experimental methods used to study membrane proteins. It encompasses a variety of technologies, including electrophoresis, X-ray crystallography, cryogenic electron microscopy (cryo-EM), nuclear magnetic resonance spectroscopy (NMR), biophysical methods, computational methods, and artificial intelligence. The link between structure and function of membrane proteins has been better understood thanks to these approaches, which also hold great promise for future study in the field. The significance of fusing artificial intelligence with experimental data to improve our comprehension of membrane protein biology is also covered in this paper. This effort aims to shed light on the complexity of membrane protein biology by investigating a variety of experimental and computational methods. Overall, the goal of this review is to emphasize how crucial it is to understand the functions of membrane proteins in eukaryotic cells. It gives a general review of the numerous methods used to look into these crucial elements and highlights the demand for multidisciplinary approaches to advance our understanding.

Improving the quality of co-evolution intermolecular contact prediction with DisVis

The steep rise in protein sequences and structures has paved the way for bioinformatics approaches to predict residue-residue interactions in protein complexes. Multiple sequence alignments are commonly used in contact predictions to identify co-evolving residues. These contacts, however, often include false positives (FPs), which may impair their use to predict three dimensional structures of biomolecular complexes and affect the accuracy of the generated models. Previously, we have developed DisVis to identify FP in mass spectrometry cross-linking data. DisVis allows to assess the accessible interaction space between two proteins consistent with a set of distance restraints. Here, we investigate if a similar approach could be applied to co-evolution predicted contacts in order to improve their precision prior to using them for modeling. We analyze co-evolution contact predictions with DisVis for a set of 26 protein-protein complexes. The DisVis-reranked and the original co-evolution contacts are then used to model the complexes with our integrative docking software HADDOCK using different filtering scenarios. Our results show that HADDOCK is robust with respect to the precision of the predicted contacts due to the 50% random contact removal during docking and can enhance the quality of docking predictions when combined with DisVis filtering for low precision contact data. DisVis can thus have a beneficial effect on low quality data, but overall HADDOCK can accommodate FP restraints without negatively impacting the quality of the resulting models. Other more precision-sensitive docking protocols might, however, benefit from the increased precision of the predicted contacts after DisVis filtering.

SLC12A cryo-EM: analysis of relevant ion binding sites, structural domains, and amino acids

The solute carrier family 12A (SLC12A) superfamily of membrane transporters modulates the movement of cations coupled with chloride across the membrane. In doing so, these cotransporters are involved in numerous aspects of human physiology: cell volume regulation, ion homeostasis, blood pressure regulation, and neurological action potential via intracellular chloride concentration modulation. Their physiological characterization has been largely studied; however, understanding the mechanics of their function and the relevance of structural domains or specific amino acids has been a pending task. In recent years, single-particle cryogenic electron microscopy (cryo-EM) has been successfully applied to members of the SLC12A family including all K+:Cl- cotransporters (KCCs), Na+:K+:2Cl- cotransporter NKCC1, and recently Na+:Cl- cotransporter (NCC); revealing structural elements that play key roles in their function. The present review analyzes the data provided by these cryo-EM reports focusing on structural domains and specific amino acids involved in ion binding, domain interactions, and other important SCL12A structural elements. A comparison of cryo-EM data from NKCC1 and KCCs is presented in the light of the two recent NCC cryo-EM studies, to propose insight into structural elements that might also be found in NCC and are necessary for its proper function. In the final sections, the importance of key coordination residues for substrate specificity and their implication on various pathophysiological conditions and genetic disorders is reviewed, as this could provide the basis to correlate structural elements with the development of novel and selective treatments, as well as mechanistic insight into the function and regulation of cation-coupled chloride cotransporters (CCCs).

Determining subunit-subunit interaction from statistics of cryo-EM images: observation of nearest-neighbor coupling in a circadian clock protein complex

Biological processes are typically actuated by dynamic multi-subunit molecular complexes. However, interactions between subunits, which govern the functions of these complexes, are hard to measure directly. Here, we develop a general approach combining cryo-EM imaging technology and statistical modeling and apply it to study the hexameric clock protein KaiC in Cyanobacteria. By clustering millions of KaiC monomer images, we identify two major conformational states of KaiC monomers. We then classify the conformational states of (>160,000) KaiC hexamers by the thirteen distinct spatial arrangements of these two subunit states in the hexamer ring. We find that distributions of the thirteen hexamer conformational patterns for two KaiC phosphorylation mutants can be fitted quantitatively by an Ising model, which reveals a significant cooperativity between neighboring subunits with phosphorylation shifting the probability of subunit conformation. Our results show that a KaiC hexamer can respond in a switch-like manner to changes in its phosphorylation level.

A robust normalized local filter to estimate compositional heterogeneity directly from cryo-EM maps

Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated. Current processing paradigms nevertheless exert great effort to reduce flexibility and heterogeneity to improve the quality of the reconstruction. Clustering algorithms are typically employed to identify populations of data with reduced variability, but lack assessment of remaining heterogeneity. Here we develope a fast and simple algorithm based on spatial filtering to estimate the heterogeneity of a reconstruction. In the absence of flexibility, this estimate approximates macromolecular component occupancy. We show that our implementation can derive reasonable input parameters, that composition heterogeneity can be estimated based on contrast loss, and that the reconstruction can be modified accordingly to emulate altered constituent occupancy. This stands to benefit conventionally employed maximum-likelihood classification methods, whereas we here limit considerations to cryo-EM map interpretation, quantification, and particle-image signal subtraction.

Geometric phase correction: A direct phase correction method to register low contrast noisy TEM images

A major challenge in the emerging field of low-dose electron microscopy lies in the development of drift correction algorithms against beam-induced specimen motion and compatible with highly noisy transmission electron microscopy (TEM) images. We report here a new drift correction method, namely geometric phase correlation (GPC), to correlate the specimen motion in real space by directly measuring the unwrapped geometric phase shift in the spatial frequency domain of the TEM image (especially from the intensive Bragg spots for crystalline materials) with sub-pixel precision. The GPC method outperforms cross-correlation-based methods in both accuracy of specimen motion prediction from highly noisy TEM movies and computational efficiency of drift calculation from abundant image frames, which holds great promise for diverse applications in low-dose TEM imaging of beam-sensitive materials, such as metal-organic frameworks (MOFs) and covalent organic frameworks (COFs).

Development of Single Molecule Techniques for Sensing and Manipulation of CRISPR and Polymerase Enzymes

Clustered regularly interspaced short palindromic repeats (CRISPR) and polymerases are powerful enzymes and their diverse applications in genomics, proteomics, and transcriptomics have revolutionized the biotechnology industry today. CRISPR has been widely adopted for genomic editing applications and Polymerases can efficiently amplify genomic transcripts via polymerase chain reaction (PCR). Further investigations into these enzymes can reveal specific details about their mechanisms that greatly expand their use. Single-molecule techniques are an effective way to probe enzymatic mechanisms because they may resolve intermediary conformations and states with greater detail than ensemble or bulk biosensing techniques. This review discusses various techniques for sensing and manipulation of single biomolecules that can help facilitate and expedite these discoveries. Each platform is categorized as optical, mechanical, or electronic. The methods, operating principles, outputs, and utility of each technique are briefly introduced, followed by a discussion of their applications to monitor and control CRISPR and Polymerases at the single molecule level, and closing with a brief overview of their limitations and future prospects.

Theoretical framework and experimental solution for the air-water interface adsorption problem in cryoEM

As cryogenic electron microscopy (cryoEM) gains traction in the structural biology community as a method of choice for determining atomic structures of biological complexes, it has been increasingly recognized that many complexes that behave well under conventional negative-stain electron microscopy tend to have preferential orientation, aggregate or simply mysteriously "disappear" on cryoEM grids. However, the reasons for such misbehavior are not well understood, which limits systematic approaches to solving the problem. Here, we have developed a theoretical formulation that explains these observations. Our formulation predicts that all particles migrate to the air-water interface (AWI) to lower the total potential surface energy-rationalizing the use of surfactant, which is a direct solution to reduce the surface tension of the aqueous solution. By performing cryogenic electron tomography (cryoET) on the widely-tested sample, GroEL, we demonstrate that, in a standard buffer solution, nearly all particles migrate to the AWI. Gradually reducing the surface tension by introducing surfactants decreased the percentage of particles exposed to the surface. By conducting single-particle cryoEM, we confirm that suitable surfactants do not damage the biological complex, thus suggesting that they might provide a practical, simple, and general solution to the problem for high-resolution cryoEM. Applying this solution to a real-world AWI adsorption problem involving a more challenging membrane protein, namely, the ClC-1 channel, has resulted in its near-atomic structure determination using cryoEM.

Modeling conformational states of proteins with AlphaFold

Many proteins exert their function by switching among different structures. Knowing the conformational ensembles affiliated with these states is critical to elucidate key mechanistic aspects that govern protein function. While experimental determination efforts are still bottlenecked by cost, time, and technical challenges, the machine-learning technology AlphaFold showed near experimental accuracy in predicting the three-dimensional structure of monomeric proteins. However, an AlphaFold ensemble of models usually represents a single conformational state with minimal structural heterogeneity. Consequently, several pipelines have been proposed to either expand the structural breadth of an ensemble or bias the prediction toward a desired conformational state. Here, we analyze how those pipelines work, what they can and cannot predict, and future directions.

Advantages and potential limitations of applying AFM kymograph analysis to pharmaceutically relevant membrane proteins in lipid bilayers

Membrane proteins play critical roles in disease and in the disposition of many pharmaceuticals. A prime example is P-glycoprotein (Pgp) which moves a diverse range of drugs across membranes and out of the cell before a therapeutic payload can be delivered. Conventional structural biology methods have provided a valuable framework for comprehending the complex conformational changes underlying Pgp function, which also includes ATPase activity, but the lack of real-time information hinders understanding. Atomic force microscopy (AFM) is a single-molecule technique that is well-suited for studying active membrane proteins in bilayers and is poised to advance the field beyond static snapshots. After verifying Pgp activity in surface-support bilayers, we used kymograph analysis in conjunction with AFM imaging and simulations to study structural transitions at the 100 ms timescale. Though kymographs are frequently employed to boost temporal resolution, the limitations of the method have not been well characterized, especially for sparse non-crystalline distributions of pharmaceutically relevant membrane proteins like Pgp. Common experimental challenges are analyzed, including protein orientation, instrument noise, and drift. Surprisingly, a lateral drift of 75% of the protein dimension leads to only a 12% probability of erroneous state transition detection; average dwell time error achieves a maximum value of 6%. Rotational drift of proteins like Pgp, with azimuthally-dependent maximum heights, can lead to artifactual transitions. Torsional constraints can alleviate this potential pitfall. Confidence in detected transitions can be increased by adding conformation-altering ligands such as non-hydrolysable analogs. Overall, the data indicate that AFM kymographs are a viable method to access conformational dynamics for Pgp, but generalizations of the method should be made with caution.

Overcoming Resolution Attenuation During Tilted Cryo-EM Data Collection

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle for dataset acquisition. These data reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

Label-free microscopy for virus infections

Microscopy has been essential to elucidate micro- and nano-scale processes in space and time and has provided insights into cell and organismic functions. It is widely employed in cell biology, microbiology, physiology, clinical sciences and virology. While label-dependent microscopy, such as fluorescence microscopy, provides molecular specificity, it has remained difficult to multiplex in live samples. In contrast, label-free microscopy reports on overall features of the specimen at minimal perturbation. Here, we discuss modalities of label-free imaging at the molecular, cellular and tissue levels, including transmitted light microscopy, quantitative phase imaging, cryogenic electron microscopy or tomography and atomic force microscopy. We highlight how label-free microscopy is used to probe the structural organization and mechanical properties of viruses, including virus particles and infected cells across a wide range of spatial scales. We discuss the working principles of imaging procedures and analyses and showcase how they open new avenues in virology. Finally, we discuss orthogonal approaches that enhance and complement label-free microscopy techniques.

3DFlex: determining structure and motion of flexible proteins from cryo-EM

Modeling flexible macromolecules is one of the foremost challenges in single-particle cryogenic-electron microscopy (cryo-EM), with the potential to illuminate fundamental questions in structural biology. We introduce Three-Dimensional Flexible Refinement (3DFlex), a motion-based neural network model for continuous molecular heterogeneity for cryo-EM data. 3DFlex exploits knowledge that conformational variability of a protein is often the result of physical processes that transport density over space and tend to preserve local geometry. From two-dimensional image data, 3DFlex enables the determination of high-resolution 3D density, and provides an explicit model of a flexible protein's motion over its conformational landscape. Experimentally, for large molecular machines (tri-snRNP spliceosome complex, translocating ribosome) and small flexible proteins (TRPV1 ion channel, αVβ8 integrin, SARS-CoV-2 spike), 3DFlex learns nonrigid molecular motions while resolving details of moving secondary structure elements. 3DFlex can improve 3D density resolution beyond the limits of existing methods because particle images contribute coherent signal over the conformational landscape.

Signal enhancement for two-dimensional cryo-EM data processing

Different tasks in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM) require enhancing the quality of the highly noisy raw images. To this end, we develop an efficient algorithm for signal enhancement of cryo-EM images. The enhanced images can be used for a variety of downstream tasks, such as two-dimensional classification, removing uninformative images, constructing ab initio models, generating templates for particle picking, providing a quick assessment of the data set, dimensionality reduction, and symmetry detection. The algorithm includes built-in quality measures to assess its performance and alleviate the risk of model bias. We demonstrate the effectiveness of the proposed algorithm on several experimental data sets. In particular, we show that the quality of the resulting images is high enough to produce ab initio models of Å resolution. The algorithm is accompanied by a publicly available, documented, and easy-to-use code.

Cryo-EM image alignment: From pair-wise to joint with deep unsupervised difference learning

Cryo-electron microscopy (cryo-EM) single-particle analysis is a revolutionary imaging technique to resolve and visualize biomacromolecules. Image alignment in cryo-EM is an important and basic step to improve the precision of the image distance calculation. However, it is a very challenging task due to high noise and low signal-to-noise ratio. Therefore, we propose a new deep unsupervised difference learning (UDL) strategy with novel pseudo-label guided learning network architecture and apply it to pair-wise image alignment in cryo-EM. The training framework is fully unsupervised. Furthermore, a variant of UDL called joint UDL (JUDL), is also proposed, which is capable of utilizing the similarity information of the whole dataset and thus further increase the alignment precision. Assessments on both real-world and synthetic cryo-EM single-particle image datasets suggest the new unsupervised joint alignment method can achieve more accurate alignment results. Our method is highly efficient by taking advantages of GPU devices. The source code of our methods is publicly available at "http://www.csbio.sjtu.edu.cn/bioinf/JointUDL/" for academic use.

Developing novel antifungals: lessons from G protein-coupled receptors

Up to 1.5 million people die yearly from fungal disease, but the repertoire of antifungal drug classes is minimal and the incidence of drug resistance is rising rapidly. This dilemma was recently declared by the World Health Organization as a global health emergency, but the discovery of new antifungal drug classes remains excruciatingly slow. This process could be accelerated by focusing on novel targets, such as G protein-coupled receptor (GPCR)-like proteins, that have a high likelihood of being druggable and have well-defined biology and roles in disease. We discuss recent successes in understanding the biology of virulence and in structure determination of yeast GPCRs, and highlight new approaches that might pay significant dividends in the urgent search for novel antifungal drugs.

Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties

Determining the three-dimensional structure of proteins in their native functional states has been a longstanding challenge in structural biology. While integrative structural biology has been the most effective way to get a high-accuracy structure of different conformations and mechanistic insights for larger proteins, advances in deep machine-learning algorithms have paved the way to fully computational predictions. In this field, AlphaFold2 (AF2) pioneered ab initio high-accuracy single-chain modeling. Since then, different customizations have expanded the number of conformational states accessible through AF2. Here, we further expanded AF2 with the aim of enriching an ensemble of models with user-defined functional or structural features. We tackled two common protein families for drug discovery, G-protein-coupled receptors (GPCRs) and kinases. Our approach automatically identifies the best templates satisfying the specified features and combines those with genetic information. We also introduced the possibility of shuffling the selected templates to expand the space of solutions. In our benchmark, models showed the intended bias and great accuracy. Our protocol can thus be exploited for modeling user-defined conformational states in an automatic fashion.

Uncovering structural ensembles from single-particle cryo-EM data using cryoDRGN

Single-particle cryogenic electron microscopy (cryo-EM) has emerged as a powerful technique to visualize the structural landscape sampled by a protein complex. However, algorithmic and computational bottlenecks in analyzing heterogeneous cryo-EM datasets have prevented the full realization of this potential. CryoDRGN is a machine learning system for heterogeneous cryo-EM reconstruction of proteins and protein complexes from single-particle cryo-EM data. Central to this approach is a deep generative model for heterogeneous cryo-EM density maps, which we empirically find is effective in modeling both discrete and continuous forms of structural variability. Once trained, cryoDRGN is capable of generating an arbitrary number of 3D density maps, and thus interpreting the resulting ensemble is a challenge. Here, we showcase interactive and automated processing approaches for analyzing cryoDRGN results. Specifically, we detail a step-by-step protocol for the analysis of an existing assembling 50S ribosome dataset, including preparation of inputs, network training and visualization of the resulting ensemble of density maps. Additionally, we describe and implement methods to comprehensively analyze and interpret the distribution of volumes with the assistance of an associated atomic model. This protocol is appropriate for structural biologists familiar with processing single-particle cryo-EM datasets and with moderate experience navigating Python and Jupyter notebooks. It requires 3-4 days to complete. CryoDRGN is open source software that is freely available.