Likelihood-based classification of cryo-EM images using FREALIGN

Structural mechanism of angiogenin activation by the ribosome

Angiogenin, an RNase-A-family protein, promotes angiogenesis and has been implicated in cancer, neurodegenerative diseases and epigenetic inheritance1-10. After activation during cellular stress, angiogenin cleaves tRNAs at the anticodon loop, resulting in translation repression11-15. However, the catalytic activity of isolated angiogenin is very low, and the mechanisms of the enzyme activation and tRNA specificity have remained a puzzle3,16-23. Here we identify these mechanisms using biochemical assays and cryogenic electron microscopy (cryo-EM). Our study reveals that the cytosolic ribosome is the activator of angiogenin. A cryo-EM structure features angiogenin bound in the A site of the 80S ribosome. The C-terminal tail of angiogenin is rearranged by interactions with the ribosome to activate the RNase catalytic centre, making the enzyme several orders of magnitude more efficient in tRNA cleavage. Additional 80S-angiogenin structures capture how tRNA substrate is directed by the ribosome into angiogenin's active site, demonstrating that the ribosome acts as the specificity factor. Our findings therefore suggest that angiogenin is activated by ribosomes with a vacant A site, the abundance of which increases during cellular stress24-27. These results may facilitate the development of therapeutics to treat cancer and neurodegenerative diseases.

Endogenous trans-translation structure visualizes the decoding of the first tmRNA alanine codon

Ribosomes stall on truncated or otherwise damaged mRNAs. Bacteria rely on ribosome rescue mechanisms to replenish the pool of ribosomes available for translation. Trans-translation, the main ribosome-rescue pathway, uses a circular hybrid transfer-messenger RNA (tmRNA) to restart translation and label the resulting peptide for degradation. Previous studies have visualized how tmRNA and its helper protein SmpB interact with the stalled ribosome to establish a new open reading frame. As tmRNA presents the first alanine codon via a non-canonical mRNA path in the ribosome, the incoming alanyl-tRNA must rearrange the tmRNA molecule to read the codon. Here, we describe cryo-EM analyses of an endogenous Escherichia coli ribosome-tmRNA complex with tRNAAla accommodated in the A site. The flexible adenosine-rich tmRNA linker, which connects the mRNA-like domain with the codon, is stabilized by the minor groove of the canonically positioned anticodon stem of tRNAAla. This ribosome complex can also accommodate a tRNA near the E (exit) site, bringing insights into the translocation and dissociation of the tRNA that decoded the defective mRNA prior to tmRNA binding. Together, these structures uncover a key step of ribosome rescue, in which the ribosome starts translating the tmRNA reading frame.

Sample Preparation for Electron Cryo-Microscopy of Macromolecular Machines

High-resolution structure determination by electron cryo-microscopy underwent a step change in recent years. This now allows study of challenging samples which previously were inaccessible for structure determination, including membrane proteins. These developments shift the focus in the field to the next bottlenecks which are high-quality sample preparations. While the amounts of sample required for cryo-EM are relatively small, sample quality is the key challenge. Sample quality is influenced by the stability of complexes which depends on buffer composition, inherent flexibility of the sample, and the method of solubilization from the membrane for membrane proteins. It further depends on the choice of sample support, grid pre-treatment and cryo-grid freezing protocol. Here, we discuss various widely applicable approaches to improve sample quality for structural analysis by cryo-EM.

MDSPACE and MDTOMO Software for Extracting Continuous Conformational Landscapes from Datasets of Single Particle Images and Subtomograms Based on Molecular Dynamics Simulations: Latest Developments in ContinuousFlex Software Package

Cryo electron microscopy (cryo-EM) instrumentation allows obtaining 3D reconstruction of the structure of biomolecular complexes in vitro (purified complexes studied by single particle analysis) and in situ (complexes studied in cells by cryo electron tomography). Standard cryo-EM approaches allow high-resolution reconstruction of only a few conformational states of a molecular complex, as they rely on data classification into a given number of classes to increase the resolution of the reconstruction from the most populated classes while discarding all other classes. Such discrete classification approaches result in a partial picture of the full conformational variability of the complex, due to continuous conformational transitions with many, uncountable intermediate states. In this article, we present the software with a user-friendly graphical interface for running two recently introduced methods, namely, MDSPACE and MDTOMO, to obtain continuous conformational landscapes of biomolecules by analyzing in vitro and in situ cryo-EM data (single particle images and subtomograms) based on molecular dynamics simulations of an available atomic model of one of the conformations. The MDSPACE and MDTOMO software is part of the open-source ContinuousFlex software package (starting from version 3.4.2 of ContinuousFlex), which can be run as a plugin of the Scipion software package (version 3.1 and later), broadly used in the cryo-EM field.

Focused classifications and refinements in high-resolution single particle cryo-EM analysis

Recent advances in cryo electron microscopy (cryo-EM) and image processing provide new opportunities to analyse drug targets at high resolution. However, structural heterogeneity limits resolution in many practical cases, hence restricting the level at which structural details can be analysed and drug design be performed. As structural disorder is not spread throughout the entire structure of a given macromolecular complex but instead is found in certain regions that move with respect to others and covering molecular scales from domain conformational changes up to the level of side chain conformations in ligand binding pockets, it is possible to focus the attention on those regions and the associated relative movements. Here we show how the usage of focused classifications and refinements provide insights into global conformational arrangements, exemplified on the human ribosome and on the cannabinoid G protein coupled receptor (GPCR), and how they can improve the local map resolution from an essentially disordered region to the 3-4 Å and finally to the 2 Å resolution range. A systematic analysis with variable spherical masks during focused refinement is presented showing that the choice of an optimal mask size helps refining to high resolution. This study covers several practical approaches on 4 examples illustrating how important mask size & shape and including neighbouring structural elements are for a focused analysis of a macromolecular complex. Such methods will be crucial for cryo-EM structure-based drug design of various medical targets and are applicable to single particle cryo-EM and electron tomography data.

OPUS-DSD: deep structural disentanglement for cryo-EM single-particle analysis

Cryo-electron microscopy (cryo-EM) captures snapshots of dynamic macromolecules, collectively illustrating the involved structural landscapes. This provides an exciting opportunity to explore the structural variations of macromolecules under study. However, traditional cryo-EM single-particle analysis often yields static structures. Here we describe OPUS-DSD, an algorithm capable of efficiently reconstructing the structural landscape embedded in cryo-EM data. OPUS-DSD uses a three-dimensional convolutional encoder-decoder architecture trained with cryo-EM images, thereby encoding structural variations into a smooth and easily analyzable low-dimension space. This space can be traversed to reconstruct continuous dynamics or clustered to identify distinct conformations. OPUS-DSD can offer meaningful insights into the structural variations of macromolecules, filling in the gaps left by traditional cryo-EM structural determination, and potentially improves the reconstruction resolution by reliably clustering similar particles within the dataset. These functionalities are especially relevant to the study of highly dynamic biological systems. OPUS-DSD is available at https://github.com/alncat/opusDSD .

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.

Robust ab initio solution of the cryo-EM reconstruction problem at low resolution with small data sets

Single particle cryo-electron microscopy has become a critical tool in structural biology over the last decade, able to achieve atomic scale resolution in three dimensional models from hundreds of thousands of (noisy) two-dimensional projection views of particles frozen at unknown orientations. This is accomplished by using a suite of software tools to (i) identify particles in large micrographs, (ii) obtain low-resolution reconstructions, (iii) refine those low-resolution structures, and (iv) finally match the obtained electron scattering density to the constituent atoms that make up the macromolecule or macromolecular complex of interest. Here, we focus on the second stage of the reconstruction pipeline: obtaining a low resolution model from picked particle images. Our goal is to create an algorithm that is capable of ab initio reconstruction from small data sets (on the order of a few thousand selected particles). More precisely, we propose an algorithm that is robust, automatic, and fast enough that it can potentially be used to assist in the assessment of particle quality as the data is being generated during the microscopy experiment.

Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.

Methods for Cryo-EM Single Particle Reconstruction of Macromolecules Having Continuous Heterogeneity

Macromolecules change their shape (conformation) in the process of carrying out their functions. The imaging by cryo-electron microscopy of rapidly-frozen, individual copies of macromolecules (single particles) is a powerful and general approach to understanding the motions and energy landscapes of macromolecules. Widely-used computational methods already allow the recovery of a few distinct conformations from heterogeneous single-particle samples, but the treatment of complex forms of heterogeneity such as the continuum of possible transitory states and flexible regions remains largely an open problem. In recent years there has been a surge of new approaches for treating the more general problem of continuous heterogeneity. This paper surveys the current state of the art in this area.

MDSPACE: Extracting Continuous Conformational Landscapes from Cryo-EM Single Particle Datasets Using 3D-to-2D Flexible Fitting based on Molecular Dynamics Simulation

This article presents an original approach for extracting atomic-resolution landscapes of continuous conformational variability of biomolecular complexes from cryo electron microscopy (cryo-EM) single particle images. This approach is based on a new 3D-to-2D flexible fitting method, which uses molecular dynamics (MD) simulation and is embedded in an iterative conformational-landscape refinement scheme. This new approach is referred to as MDSPACE, which stands for Molecular Dynamics simulation for Single Particle Analysis of Continuous Conformational hEterogeneity. The article describes the MDSPACE approach and shows its performance using synthetic and experimental datasets.

Exploring the Structural Variability of Dynamic Biological Complexes by Single-Particle Cryo-Electron Microscopy

Biological macromolecules and assemblies precisely rearrange their atomic 3D structures to execute cellular functions. Understanding the mechanisms by which these molecular machines operate requires insight into the ensemble of structural states they occupy during the functional cycle. Single-particle cryo-electron microscopy (cryo-EM) has become the preferred method to provide near-atomic resolution, structural information about dynamic biological macromolecules elusive to other structure determination methods. Recent advances in cryo-EM methodology have allowed structural biologists not only to probe the structural intermediates of biochemical reactions, but also to resolve different compositional and conformational states present within the same dataset. This article reviews newly developed sample preparation and single-particle analysis (SPA) techniques for high-resolution structure determination of intrinsically dynamic and heterogeneous samples, shedding light upon the intricate mechanisms employed by molecular machines and helping to guide drug discovery efforts.

Cryo-EM for Small Molecules

In recent years, protein structure analysis using cryo-electron microscopy(cryo-EM) has expanded and improved. In this review, we discuss many recent improvements to the field, the problems those improvements hope to solve, and some of the still unanswered questions. Most notably, this review will discuss improvements in resolving small or fragmented protein structures, as well as methods to improve the signal-to-noise ratio of the data by increasing image contrast using carbon-based systems. We will also describe how, in the last 5 years, methodological improvements have allowed for better 3D image resolution by capturing a continuum of 3D images. We will provide examples of these methods in practice and discuss how these improved methods may be used in small-molecule drug discovery and development. © 2022 Wiley Periodicals LLC.

DeepHEMNMA: ResNet-based hybrid analysis of continuous conformational heterogeneity in cryo-EM single particle images

Single-particle cryo-electron microscopy (cryo-EM) is a technique for biomolecular structure reconstruction from vitrified samples containing many copies of a biomolecular complex (known as single particles) at random unknown 3D orientations and positions. Cryo-EM allows reconstructing multiple conformations of the complexes from images of the same sample, which usually requires many rounds of 2D and 3D classifications to disentangle and interpret the combined conformational, orientational, and translational heterogeneity. The elucidation of different conformations is the key to understand molecular mechanisms behind the biological functions of the complexes and the key to novel drug discovery. Continuous conformational heterogeneity, due to gradual conformational transitions giving raise to many intermediate conformational states of the complexes, is both an obstacle for high-resolution 3D reconstruction of the conformational states and an opportunity to obtain information about multiple coexisting conformational states at once. HEMNMA method, specifically developed for analyzing continuous conformational heterogeneity in cryo-EM, determines the conformation, orientation, and position of the complex in each single particle image by image analysis using normal modes (the motion directions simulated for a given atomic structure or EM map), which in turn allows determining the full conformational space of the complex but at the price of high computational cost. In this article, we present a new method, referred to as DeepHEMNMA, which speeds up HEMNMA by combining it with a residual neural network (ResNet) based deep learning approach. The performance of DeepHEMNMA is shown using synthetic and experimental single particle images.

Visualizing Conformational Space of Functional Biomolecular Complexes by Deep Manifold Learning

The cellular functions are executed by biological macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving the conformational continuum of important biomolecular complexes at the atomic level is essential to understanding their functional mechanisms and guiding structure-based drug discovery. Here, we introduce a deep manifold learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy (cryo-EM) reconstructions that approximately visualize the conformational space of biomolecular complexes of interest. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of pseudo-energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. In blind assessments using simulated heterogeneous datasets, AlphaCryo4D achieved 3D classification accuracy three times those of alternative methods and reconstructed continuous conformational changes of a 130-kDa protein at sub-3 Å resolution. By applying this approach to analyze several experimental datasets of the proteasome, ribosome and spliceosome, we demonstrate its potential generality in exploring hidden conformational space or transient states of macromolecular complexes that remain hitherto invisible. Integration of this approach with time-resolved cryo-EM further allows visualization of conformational continuum in a nonequilibrium regime at the atomic level, thus potentially enabling therapeutic discovery against highly dynamic biomolecular targets.

Emerging Themes in CryoEM─Single Particle Analysis Image Processing

Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.

Ribosome inhibition by C9ORF72-ALS/FTD-associated poly-PR and poly-GR proteins revealed by cryo-EM

Toxic dipeptide-repeat (DPR) proteins are produced from expanded G4C2 repeats in the C9ORF72 gene, the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Two DPR proteins, poly-PR and poly-GR, repress cellular translation but the molecular mechanism remains unknown. Here we show that poly-PR and poly-GR of ≥20 repeats inhibit the ribosome's peptidyl-transferase activity at nanomolar concentrations, comparable to specific translation inhibitors. High-resolution cryogenic electron microscopy (cryo-EM) reveals that poly-PR and poly-GR block the polypeptide tunnel of the ribosome, extending into the peptidyl-transferase center (PTC). Consistent with these findings, the macrolide erythromycin, which binds in the tunnel, competes with poly-PR and restores peptidyl-transferase activity. Our results demonstrate that strong and specific binding of poly-PR and poly-GR in the ribosomal tunnel blocks translation, revealing the structural basis of their toxicity in C9ORF72-ALS/FTD.

Quantitative mining of compositional heterogeneity in cryo-EM datasets of ribosome assembly intermediates

Single-particle cryoelectron microscopy (cryo-EM) offers a unique opportunity to characterize macromolecular structural heterogeneity by virtue of its ability to place distinct particle populations into different groups through computational classification. However, there is a dearth of tools for surveying the heterogeneity landscape, quantitatively analyzing heterogeneous particle populations after classification, deciding how many unique classes are represented by the data, and accurately cross-comparing reconstructions. Here, we develop a workflow that contains discovery and analysis modules to quantitatively mine cryo-EM data for sets of structures with maximal diversity. This workflow was applied to a dataset of E. coli 50S ribosome assembly intermediates, which are characterized by significant structural heterogeneity. We identified more detailed branchpoints in the assembly process and characterized the interactions of an assembly factor with immature intermediates. While the tools described here were developed for ribosome assembly, they should be broadly applicable to the analysis of other heterogeneous cryo-EM datasets.

Hierarchical autoclassification of cryo-EM samples and macromolecular energy landscape determination

BACKGROUND AND OBJECTIVE

Cryo-electron microscopy using single particle analysis is a powerful technique for obtaining 3D reconstructions of macromolecules in near native conditions. One of its major advances is its capacity to reveal conformations of dynamic molecular complexes. Most popular and successful current approaches to analyzing heterogeneous complexes are founded on Bayesian inference. However, these 3D classification methods require the tuning of specific parameters by the user and the use of complicated 3D re-classification procedures for samples affected by extensive heterogeneity. Thus, the success of these approaches highly depends on the user experience. We introduce a robust approach to identify many different conformations presented in a cryo-EM dataset based on Bayesian inference through Relion classification methods that does not require tuning of parameters and reclassification strategies.

METHODS

The algorithm allows both 2D and 3D classification and is based on a hierarchical clustering approach that runs automatically without requiring typical inputs, such as the number of conformations present in the dataset or the required classification iterations. This approach is applied to robustly determine the energy landscapes of macromolecules.

RESULTS

We tested the performance of the methods proposed here using four different datasets, comprising structurally homogeneous and highly heterogeneous cases. In all cases, the approach provided excellent results. The routines are publicly available as part of the CryoMethods plugin included in the Scipion package.

CONCLUSIONS

Our results show that the proposed method can be used to align and classify homogeneous and heterogeneous datasets without requiring previous alignment information or any prior knowledge about the number of co-existing conformations. The approach can be used for both 2D and 3D autoclassification and only requires an initial volume. In addition, the approach is robust to the "attractor" problem providing many different conformations/views for samples affected by extensive heterogeneity. The obtained 3D classes can render high resolution 3D structures, while the obtained energy landscapes can be used to determine structural trajectories.

On bias, variance, overfitting, gold standard and consensus in single-particle analysis by cryo-electron microscopy

Single-particle analysis (SPA) by cryo-electron microscopy comprises the estimation of many parameters along its image-processing pipeline. Overfitting observed in SPA is normally due to misestimated parameters, and the only way to identify these is by comparing the estimates of multiple algorithms or, at least, multiple executions of the same algorithm.

Cryo-electron microscopy (cryoEM) has become a well established technique to elucidate the 3D structures of biological macromolecules. Projection images from thousands of macromolecules that are assumed to be structurally identical are combined into a single 3D map representing the Coulomb potential of the macromolecule under study. This article discusses possible caveats along the image-processing path and how to avoid them to obtain a reliable 3D structure. Some of these problems are very well known in the community. These may be referred to as sample-related (such as specimen denaturation at interfaces or non-uniform projection geometry leading to underrepresented projection directions). The rest are related to the algorithms used. While some have been discussed in depth in the literature, such as the use of an incorrect initial volume, others have received much less attention. However, they are fundamental in any data-analysis approach. Chiefly among them, instabilities in estimating many of the key parameters that are required for a correct 3D reconstruction that occur all along the processing workflow are referred to, which may significantly affect the reliability of the whole process. In the field, the term overfitting has been coined to refer to some particular kinds of artifacts. It is argued that overfitting is a statistical bias in key parameter-estimation steps in the 3D reconstruction process, including intrinsic algorithmic bias. It is also shown that common tools (Fourier shell correlation) and strategies (gold standard) that are normally used to detect or prevent overfitting do not fully protect against it. Alternatively, it is proposed that detecting the bias that leads to overfitting is much easier when addressed at the level of parameter estimation, rather than detecting it once the particle images have been combined into a 3D map. Comparing the results from multiple algorithms (or at least, independent executions of the same algorithm) can detect parameter bias. These multiple executions could then be averaged to give a lower variance estimate of the underlying parameters.

Seipin forms a flexible cage at lipid droplet formation sites

Lipid droplets (LDs) form in the endoplasmic reticulum by phase separation of neutral lipids. This process is facilitated by the seipin protein complex, which consists of a ring of seipin monomers, with a yet unclear function. Here, we report a structure of S. cerevisiae seipin based on cryogenic-electron microscopy and structural modeling data. Seipin forms a decameric, cage-like structure with the lumenal domains forming a stable ring at the cage floor and transmembrane segments forming the cage sides and top. The transmembrane segments interact with adjacent monomers in two distinct, alternating conformations. These conformations result from changes in switch regions, located between the lumenal domains and the transmembrane segments, that are required for seipin function. Our data indicate a model for LD formation in which a closed seipin cage enables triacylglycerol phase separation and subsequently switches to an open conformation to allow LD growth and budding.

Cryogenic electron microscopy approaches that combine images and tilt series

Cryogenic electron microscopy can be widely applied to biological specimens from the molecular to the cellular scale. In single-particle analysis, 3D structures may be obtained in high resolution by averaging 2D images of single particles in random orientations. For pleomorphic specimens, structures may be obtained by recording the tilt series of a single example of the specimen and calculating tomograms. Where many copies of a single structure such as a protein or nucleic acid assembly are present within the tomogram, averaging of the sub-volumes (subtomogram averaging) has been successfully applied. The choice of data collection method for any given specimen may depend on the structural question of interest and is determined by the radiation sensitivity of the specimen. Here, we survey some recent developments on the use of hybrid methods for recording and analysing data from radiation-sensitive biological specimens. These include single-particle reconstruction from 2D images where additional views are recorded at a single tilt angle of the specimen and methods where image tilt series, initially used for tomogram reconstruction, are processed as individual single-particle images. There is a continuum of approaches now available to maximize structural information obtained from the specimen.

Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review

Recently, single-particle cryo-electron microscopy (cryo-EM) has become an indispensable method for determining macromolecular structures at high resolution to deeply explore the relevant molecular mechanism. Its recent breakthrough is mainly because of the rapid advances in hardware and image processing algorithms, especially machine learning. As an essential support of single-particle cryo-EM, machine learning has powered many aspects of structure determination and greatly promoted its development. In this article, we provide a systematic review of the applications of machine learning in this field. Our review begins with a brief introduction of single-particle cryo-EM, followed by the specific tasks and challenges of its image processing. Then, focusing on the workflow of structure determination, we describe relevant machine learning algorithms and applications at different steps, including particle picking, 2-D clustering, 3-D reconstruction, and other steps. As different tasks exhibit distinct characteristics, we introduce the evaluation metrics for each task and summarize their dynamics of technology development. Finally, we discuss the open issues and potential trends in this promising field.

Retroviral integrase: Structure, mechanism, and inhibition

The retroviral protein Integrase (IN) catalyzes concerted integration of viral DNA into host chromatin to establish a permanent infection in the target cell. We learned a great deal about the mechanism of catalytic integration through structure/function studies over the previous four decades of IN research. As one of three essential retroviral enzymes, IN has also been targeted by antiretroviral drugs to treat HIV-infected individuals. Inhibitors blocking the catalytic integration reaction are now state-of-the-art drugs within the antiretroviral therapy toolkit. HIV-1 IN also performs intriguing non-catalytic functions that are relevant to the late stages of the viral replication cycle, yet this aspect remains poorly understood. There are also novel allosteric inhibitors targeting non-enzymatic functions of IN that induce a block in the late stages of the viral replication cycle. In this chapter, we will discuss the function, structure, and inhibition of retroviral IN proteins, highlighting remaining challenges and outstanding questions.

Inhibiting parasite proliferation using a rationally designed anti-tubulin agent

Infectious diseases caused by apicomplexan parasites remain a global public health threat. The presence of multiple ligand-binding sites in tubulin makes this protein an attractive target for anti-parasite drug discovery. However, despite remarkable successes as anti-cancer agents, the rational development of protozoan parasite-specific tubulin drugs has been hindered by a lack of structural and biochemical information on protozoan tubulins. Here, we present atomic structures for a protozoan tubulin and microtubule and delineate the architectures of apicomplexan tubulin drug-binding sites. Based on this information, we rationally designed the parasite-specific tubulin inhibitor parabulin and show that it inhibits growth of parasites while displaying no effects on human cells. Our work presents for the first time the rational design of a species-specific tubulin drug providing a framework to exploit structural differences between human and protozoa tubulin variants enabling the development of much-needed, novel parasite inhibitors.

Structural features of nucleosomes in interphase and metaphase chromosomes

Structural heterogeneity of nucleosomes in functional chromosomes is unknown. Here, we devise the template-, reference- and selection-free (TRSF) cryo-EM pipeline to simultaneously reconstruct cryo-EM structures of protein complexes from interphase or metaphase chromosomes. The reconstructed interphase and metaphase nucleosome structures are on average indistinguishable from canonical nucleosome structures, despite DNA sequence heterogeneity, cell-cycle-specific posttranslational modifications, and interacting proteins. Nucleosome structures determined by a decoy-classifying method and structure variability analyses reveal the nucleosome structural variations in linker DNA, histone tails, and nucleosome core particle configurations, suggesting that the opening of linker DNA, which is correlated with H2A C-terminal tail positioning, is suppressed in chromosomes. High-resolution (3.4-3.5 Å) nucleosome structures indicate DNA-sequence-independent stabilization of superhelical locations ±0-1 and ±3.5-4.5. The linker histone H1.8 preferentially binds to metaphase chromatin, from which chromatosome cryo-EM structures with H1.8 at the on-dyad position are reconstituted. This study presents the structural characteristics of nucleosomes in chromosomes.

Redeployment of automated MrBUMP search-model identification for map fitting in cryo-EM

In crystallography, the phase problem can often be addressed by the careful preparation of molecular-replacement search models. This has led to the development of pipelines such as MrBUMP that can automatically identify homologous proteins from an input sequence and edit them to focus on the areas that are most conserved. Many of these approaches can be applied directly to cryo-EM to help discover, prepare and correctly place models (here called cryo-EM search models) into electrostatic potential maps. This can significantly reduce the amount of manual model building that is required for structure determination. Here, MrBUMP is repurposed to fit automatically obtained PDB-derived chains and domains into cryo-EM maps. MrBUMP was successfully able to identify and place cryo-EM search models across a range of resolutions. Methods such as map segmentation are also explored as potential routes to improved performance. Map segmentation was also found to improve the effectiveness of the pipeline for higher resolution (<8 Å) data sets.

HEMNMA-3D: Cryo Electron Tomography Method Based on Normal Mode Analysis to Study Continuous Conformational Variability of Macromolecular Complexes

Cryogenic electron tomography (cryo-ET) allows structural determination of biomolecules in their native environment (in situ). Its potential of providing information on the dynamics of macromolecular complexes in cells is still largely unexploited, due to the challenges of the data analysis. The crowded cell environment and continuous conformational changes of complexes make difficult disentangling the data heterogeneity. We present HEMNMA-3D, which is, to the best of our knowledge, the first method for analyzing cryo electron subtomograms in terms of continuous conformational changes of complexes. HEMNMA-3D uses a combination of elastic and rigid-body 3D-to-3D iterative alignments of a flexible 3D reference (atomic structure or electron microscopy density map) to match the conformation, orientation, and position of the complex in each subtomogram. The elastic matching combines molecular mechanics simulation (Normal Mode Analysis of the 3D reference) and experimental, subtomogram data analysis. The rigid-body alignment includes compensation for the missing wedge, due to the limited tilt angle of cryo-ET. The conformational parameters (amplitudes of normal modes) of the complexes in subtomograms obtained through the alignment are processed to visualize the distribution of conformations in a space of lower dimension (typically, 2D or 3D) referred to as space of conformations. This allows a visually interpretable insight into the dynamics of the complexes, by calculating 3D averages of subtomograms with similar conformations from selected (densest) regions and by recording movies of the 3D reference's displacement along selected trajectories through the densest regions. We describe HEMNMA-3D and show its validation using synthetic datasets. We apply HEMNMA-3D to an experimental dataset describing in situ nucleosome conformational variability. HEMNMA-3D software is available freely (open-source) as part of ContinuousFlex plugin of Scipion V3.0 (http://scipion.i2pc.es).

Fusion peptide priming reduces immune responses to HIV-1 envelope trimer base

Soluble "SOSIP"-stabilized envelope (Env) trimers are promising HIV-vaccine immunogens. However, they induce high-titer responses against the glycan-free trimer base, which is occluded on native virions. To delineate the effect on base responses of priming with immunogens targeting the fusion peptide (FP) site of vulnerability, here, we quantify the prevalence of trimer-base antibody responses in 49 non-human primates immunized with various SOSIP-stabilized Env trimers and FP-carrier conjugates. Trimer-base responses account for ∼90% of the overall trimer response in animals immunized with trimer only, ∼70% in animals immunized with a cocktail of SOSIP trimer and FP conjugate, and ∼30% in animals primed with FP conjugates before trimer immunization. Notably, neutralization breadth in FP-conjugate-primed animals correlates inversely with trimer-base responses. Our data provide methods to quantify the prevalence of trimer-base responses and reveal that FP-conjugate priming, either alone or as part of a cocktail, can reduce the trimer-base response and improve the neutralization outcome.

Tools for visualizing and analyzing Fourier space sampling in Cryo-EM

A complete understanding of how an orientation distribution contributes to a cryo-EM reconstruction remains lacking. It is necessary to begin critically assessing the set of views to gain an understanding of its effect on experimental reconstructions. Toward that end, we recently suggested that the type of orientation distribution may alter resolution measures in a systematic manner. We introduced the sampling compensation factor (SCF), which incorporates how the collection geometry might change the spectral signal-to-noise ratio (SSNR), irrespective of the other experimental aspects. We show here that knowledge of the sampling restricted to spherical surfaces of sufficiently large radii in Fourier space is equivalent to knowledge of the set of projection views. Moreover, the SCF geometrical factor may be calculated from one such surface. To aid cryo-EM practitioners, we developed a graphical user interface (GUI) tool that evaluates experimental orientation distributions. The GUI returns plots of projection directions, sampling constrained to the surface of a sphere, the SCF value, the fraction of the empty region of Fourier space, and a histogram of the sampling values over the points on a sphere. Finally, a fixed tilt angle may be incorporated to determine how tilting the grid during collection may improve the distribution of views and Fourier space sampling. We advocate this simple conception of sampling and the use of such tools as a complement to the distribution of views to capture the different aspects of the effect of projection directions on cryo-EM reconstructions.

CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks

Cryo-electron microscopy (cryo-EM) single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many imaged protein complexes exhibit conformational and compositional heterogeneity that poses a major challenge to existing three-dimensional reconstruction methods. Here, we present cryoDRGN, an algorithm that leverages the representation power of deep neural networks to directly reconstruct continuous distributions of 3D density maps and map per-particle heterogeneity of single-particle cryo-EM datasets. Using cryoDRGN, we uncovered residual heterogeneity in high-resolution datasets of the 80S ribosome and the RAG complex, revealed a new structural state of the assembling 50S ribosome, and visualized large-scale continuous motions of a spliceosome complex. CryoDRGN contains interactive tools to visualize a dataset's distribution of per-particle variability, generate density maps for exploratory analysis, extract particle subsets for use with other tools and generate trajectories to visualize molecular motions. CryoDRGN is open-source software freely available at http://cryodrgn.csail.mit.edu .

ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions

Cryo-electron microscopy using single particle analysis requires the computational averaging of thousands of projection images captured from identical macromolecules. However, macromolecules usually present some degree of flexibility showing different conformations. Computational approaches are then required to classify heterogeneous single particle images into homogeneous sets corresponding to different structural states. Nonetheless, sometimes the attainable resolution of reconstructions obtained from these smaller homogeneous sets is compromised because of reduced number of particles or lack of images at certain macromolecular orientations. In these situations, the current solution to improve map resolution is returning to the electron microscope and collect more data. In this work, we present a fast approach to partially overcome this limitation for heterogeneous data sets. Our method is based on deforming and then moving particles between different conformations using an optical flow approach. Particles are then merged into a unique conformation obtaining reconstructions with improved resolution, contrast and signal-to-noise ratio. We present experimental results that show clear improvements in the quality of obtained 3D maps, however, there are also limits to this approach, i.e., the method is restricted to small deformations and cannot determine local patterns of flexibility of small elements, such as secondary structures, which we discuss in the manuscript.

Single Particle Analysis for High-Resolution 2D Electron Crystallography

Electron crystallography has been used for decades to determine three-dimensional structures of membrane proteins embedded in a lipid bilayer. However, high-resolution information could only be retrieved from samples where the 2D crystals were well ordered and perfectly flat. This is rarely the case in practice. We implemented in the FOCUS package a module to export transmission electron microscopy images of 2D crystals for 3D reconstruction by single particle algorithms. This approach allows for correcting local distortions of the 2D crystals, yielding much higher resolution reconstructions than otherwise expected from the observable diffraction spots. In addition, the single particle framework enables classification of heterogeneous structures coexisting within the 2D crystals. We provide here a detailed guide on single particle analysis of 2D crystal data based on the FOCUS and FREALIGN packages.

ArfB can displace mRNA to rescue stalled ribosomes

Ribosomes stalled during translation must be rescued to replenish the pool of translation-competent ribosomal subunits. Bacterial alternative rescue factor B (ArfB) releases nascent peptides from ribosomes stalled on mRNAs truncated at the A site, allowing ribosome recycling. Prior structural work revealed that ArfB recognizes such ribosomes by inserting its C-terminal α-helix into the vacant mRNA tunnel. In this work, we report that ArfB can efficiently recognize a wider range of mRNA substrates, including longer mRNAs that extend beyond the A-site codon. Single-particle cryo-EM unveils that ArfB employs two modes of function depending on the mRNA length. ArfB acts as a monomer to accommodate a shorter mRNA in the ribosomal A site. By contrast, longer mRNAs are displaced from the mRNA tunnel by more than 20 Å and are stabilized in the intersubunit space by dimeric ArfB. Uncovering distinct modes of ArfB function resolves conflicting biochemical and structural studies, and may lead to re-examination of other ribosome rescue pathways, whose functions depend on mRNA lengths.

Structural Heterogeneities of the Ribosome: New Frontiers and Opportunities for Cryo-EM

The extent of ribosomal heterogeneity has caught increasing interest over the past few years, as recent studies have highlighted the presence of structural variations of the ribosome. More precisely, the heterogeneity of the ribosome covers multiple scales, including the dynamical aspects of ribosomal motion at the single particle level, specialization at the cellular and subcellular scale, or evolutionary differences across species. Upon solving the ribosome atomic structure at medium to high resolution, cryogenic electron microscopy (cryo-EM) has enabled investigating all these forms of heterogeneity. In this review, we present some recent advances in quantifying ribosome heterogeneity, with a focus on the conformational and evolutionary variations of the ribosome and their functional implications. These efforts highlight the need for new computational methods and comparative tools, to comprehensively model the continuous conformational transition pathways of the ribosome, as well as its evolution. While developing these methods presents some important challenges, it also provides an opportunity to extend our interpretation and usage of cryo-EM data, which would more generally benefit the study of molecular dynamics and evolution of proteins and other complexes.

Structural mechanism of phospholipids translocation by MlaFEDB complex

In Gram-negative bacteria, phospholipids are major components of the inner membrane and the inner leaflet of the outer membrane, playing an essential role in forming the unique dual-membrane barrier to exclude the entry of most antibiotics. Understanding the mechanisms of phospholipid translocation between the inner and outer membrane represents one of the major challenges surrounding bacterial phospholipid homeostasis. The conserved MlaFEDB complex in the inner membrane functions as an ABC transporter to drive the translocation of phospholipids between the inner membrane and the periplasmic protein MlaC. However, the mechanism of phospholipid translocation remains elusive. Here we determined three cryo-EM structures of MlaFEDB from Escherichia coli in its nucleotide-free and ATP-bound conformations, and performed extensive functional studies to verify and extend our findings from structural analyses. Our work reveals unique structural features of the entire MlaFEDB complex, six well-resolved phospholipids in three distinct cavities, and large-scale conformational changes upon ATP binding. Together, these findings define the cycle of structural rearrangement of MlaFEDB in action, and suggest that MlaFEDB uses an extrusion mechanism to extract and release phospholipids through the central translocation cavity.

Current limits of structural biology: The transient interaction between cytochrome c 6 and photosystem I

Trimeric photosystem I from the cyanobacterium Thermosynechococcus elongatus (TePSI) is an intrinsic membrane protein, which converts solar energy into electrical energy by oxidizing the soluble redox mediator cytochrome c 6 (Cyt c 6 ) and reducing ferredoxin. Here, we use cryo-electron microscopy and small angle neutron scattering (SANS) to characterize the transient binding of Cyt c 6 to TePSI. The structure of TePSI cross-linked to Cyt c 6 was solved at a resolution of 2.9 Å and shows additional cofactors as well as side chain density for 84% of the peptide chain of subunit PsaK, revealing a hydrophobic, membrane intrinsic loop that enables binding of associated proteins. Due to the poor binding specificity, Cyt c 6 could not be localized with certainty in our cryo-EM analysis. SANS measurements confirm that Cyt c 6 does not bind to TePSI at protein concentrations comparable to those for cross-linking. However, SANS data indicate a complex formation between TePSI and the non-native mitochondrial cytochrome from horse heart (Cyt c HH ). Our study pinpoints the difficulty of identifying very small binding partners (less than 5% of the overall size) in EM structures when binding affinities are poor. We relate our results to well resolved co-structures with known binding affinities and recommend confirmatory methods for complexes with K M values higher than 20 μM.

Structural mechanism of two gain-of-function cardiac and skeletal RyR mutations at an equivalent site by cryo-EM

Mutations in ryanodine receptors (RyRs), intracellular Ca2+ channels, are associated with deadly disorders. Despite abundant functional studies, the molecular mechanism of RyR malfunction remains elusive. We studied two single-point mutations at an equivalent site in the skeletal (RyR1 R164C) and cardiac (RyR2 R176Q) isoforms using ryanodine binding, Ca2+ imaging, and cryo-electron microscopy (cryo-EM) of the full-length protein. Loss of the positive charge had greater effect on the skeletal isoform, mediated via distortion of a salt bridge network, a molecular latch inducing rotation of a cytoplasmic domain, and partial progression to open-state traits of the large cytoplasmic assembly accompanied by alteration of the Ca2+ binding site, which concur with the major "hyperactive" feature of the mutated channel. Our cryo-EM studies demonstrated the allosteric effect of a mutation situated ~85 Å away from the pore and identified an isoform-specific structural effect.

Computational Methods for Single-Particle Electron Cryomicroscopy

Single-particle electron cryomicroscopy (cryo-EM) is an increasingly popular technique for elucidating the three-dimensional structure of proteins and other biologically significant complexes at near-atomic resolution. It is an imaging method that does not require crystallization and can capture molecules in their native states. In single-particle cryo-EM, the three-dimensional molecular structure needs to be determined from many noisy two-dimensional tomographic projections of individual molecules, whose orientations and positions are unknown. The high level of noise and the unknown pose parameters are two key elements that make reconstruction a challenging computational problem. Even more challenging is the inference of structural variability and flexible motions when the individual molecules being imaged are in different conformational states. This review discusses computational methods for structure determination by single-particle cryo-EM and their guiding principles from statistical inference, machine learning, and signal processing that also play a significant role in many other data science applications.

Cryo-EM of elongating ribosome with EF-Tu•GTP elucidates tRNA proofreading

Ribosomes accurately decode mRNA by proofreading each aminoacyl-tRNA delivered by elongation factor EF-Tu¹. Understanding the molecular mechanism of proofreading requires visualizing GTP-catalyzed elongation, which has remained a challenge^2–4. Here, time-resolved cryo-EM revealed 33 states following aminoacyl-tRNA delivery by EF-Tu•GTP. Instead of locking cognate tRNA upon initial recognition, the ribosomal decoding center (DC) dynamically monitors codon-anticodon interactions before and after GTP hydrolysis. GTP hydrolysis allows EF-Tu’s GTPase domain to extend away, releasing EF-Tu from tRNA. Then, the 30S subunit locks cognate tRNA in the DC, and rotates, enabling the tRNA to bypass 50S protrusions during accommodation into the peptidyl transferase center. By contrast, the DC fails to lock near-cognate tRNA, allowing dissociation of near-cognate tRNA during both initial selection (before GTP hydrolysis) and proofreading (after GTP hydrolysis). These findings reveal structural similarity between initial selection^5,6 and the previously unseen proofreading, which together govern efficient rejection of incorrect tRNA.

Ribosome engineering reveals the importance of 5S rRNA autonomy for ribosome assembly

5S rRNA is an indispensable component of cytoplasmic ribosomes in all species. The functions of 5S rRNA and the reasons for its evolutionary preservation as an independent molecule remain unclear. Here we used ribosome engineering to investigate whether 5S rRNA autonomy is critical for ribosome function and cell survival. By linking circularly permutated 5S rRNA with 23S rRNA we generated a bacterial strain devoid of free 5S rRNA. Viability of the engineered cells demonstrates that autonomous 5S rRNA is dispensable for cell growth under standard conditions and is unlikely to have essential functions outside the ribosome. The fully assembled ribosomes carrying 23S-5S rRNA are highly active in translation. However, the engineered cells accumulate aberrant 50S subunits unable to form stable 70S ribosomes. Cryo-EM analysis revealed a malformed peptidyl transferase center in the misassembled 50S subunits. Our results argue that the autonomy of 5S rRNA is preserved due to its role in ribosome biogenesis.

Negative-Stain Transmission Electron Microscopy of Molecular Complexes for Image Analysis by 2D Class Averaging

Negative-stain transmission electron microscopy (EM) is a technique that has provided nanometer resolution images of macromolecules for about 60 years. Developments in cryo-EM image processing have maximized the information gained from averaging large numbers of particles. These developments can now be applied back to negative-stain image analysis to ascertain domain level molecular structure (10 to 20 Å) more quickly and efficiently than possible by atomic resolution cryo-EM. Using uranyl acetate stained molecular complexes of influenza hemagglutinin bound to Fab 441D6, we describe a simple and efficient means to collect several hundred micrographs with SerialEM. Using RELION, we illustrate how tens of thousands of complexes can be auto-picked and classified to accurately describe the domain level topology of this unconventional hemagglutinin head-domain epitope. By comparing to the cryo-EM density map of the same complex, we show that questions about epitope mapping and conformational heterogeneity can readily be answered by this negative-stain method. © 2019 The Authors.

ABCG2 transports anticancer drugs via a closed-to-open switch

ABCG2 is an ABC transporter that extrudes a variety of compounds from cells, and presents an obstacle in treating chemotherapy-resistant cancers. Despite recent structural insights, no anticancer drug bound to ABCG2 has been resolved, and the mechanisms of multidrug transport remain obscure. Such a gap of knowledge limits the development of novel compounds that block or evade this critical molecular pump. Here we present single-particle cryo-EM studies of ABCG2 in the apo state, and bound to the three structurally distinct chemotherapeutics. Without the binding of conformation-selective antibody fragments or inhibitors, the resting ABCG2 adopts a closed conformation. Our cryo-EM, biochemical, and functional analyses reveal the binding mode of three chemotherapeutic compounds, demonstrate how these molecules open the closed conformation of the transporter, and establish that imatinib is particularly effective in stabilizing the inward facing conformation of ABCG2. Together these studies reveal the previously unrecognized conformational cycle of ABCG2.

ABCG2 is a human ABC transporter that actively extrudes a wide variety of compounds from cells but the mechanisms of multidrug transport remain obscure. Here authors present cryo-EM structures of ABCG2 in the apo state, and bound to the three structurally distinct chemotherapeutics and demonstrate how these molecules open the closed conformation of the transporter.

Need for Cross-Validation of Single Particle Cryo-EM

Cross-validation is used to determine the validity of a model on unseen data by assessing if the model is overfitted to noise. It is widely used in many fields, from artificial intelligence to structural biology in X-ray crystallography and nuclear magnetic resonance. Although there are concerns of map overfitting in cryo-electron microscopy (cryo-EM), cross-validation is rarely used. The problem is that establishing a performance metric of the maps over unseen data (given by 2D-projection images) is difficult due to the low signal-to-noise ratios in the individual particles. Here, I present recent advances for cryo-EM map reconstruction. I highlight that the gold-standard procedure can fail to detect map overfitting in certain cases, showing the necessity of assessing the map quality on unbiased data. Finally, I describe the challenges and advantages of developing a robust cross-validation methodology for cryo-EM.

Cryo-EM reconstruction of continuous heterogeneity by Laplacian spectral volumes

Single-particle electron cryomicroscopy is an essential tool for high-resolution 3D reconstruction of proteins and other biological macromolecules. An important challenge in cryo-EM is the reconstruction of non-rigid molecules with parts that move and deform. Traditional reconstruction methods fail in these cases, resulting in smeared reconstructions of the moving parts. This poses a major obstacle for structural biologists, who need high-resolution reconstructions of entire macromolecules, moving parts included. To address this challenge, we present a new method for the reconstruction of macromolecules exhibiting continuous heterogeneity. The proposed method uses projection images from multiple viewing directions to construct a graph Laplacian through which the manifold of three-dimensional conformations is analyzed. The 3D molecular structures are then expanded in a basis of Laplacian eigenvectors, using a novel generalized tomographic reconstruction algorithm to compute the expansion coefficients. These coefficients, which we name spectral volumes, provide a high-resolution visualization of the molecular dynamics. We provide a theoretical analysis and evaluate the method empirically on several simulated data sets.

Molecular structures of the human Slo1 K+ channel in complex with β4

Slo1 is a Ca²⁺- and voltage-activated K⁺ channel that underlies skeletal and smooth muscle contraction, audition, hormone secretion and neurotransmitter release. In mammals, Slo1 is regulated by auxiliary proteins that confer tissue-specific gating and pharmacological properties. This study presents cryo-EM structures of Slo1 in complex with the auxiliary protein, β4. Four β4, each containing two transmembrane helices, encircle Slo1, contacting it through helical interactions inside the membrane. On the extracellular side, β4 forms a tetrameric crown over the pore. Structures with high and low Ca²⁺ concentrations show that identical gating conformations occur in the absence and presence of β4, implying that β4 serves to modulate the relative stabilities of 'pre-existing' conformations rather than creating new ones. The effects of β4 on scorpion toxin inhibition kinetics are explained by the crown, which constrains access but does not prevent binding.

Cryo-EM structure of the KvAP channel reveals a non-domain-swapped voltage sensor topology

Conductance in voltage-gated ion channels is regulated by membrane voltage through structural domains known as voltage sensors. A single structural class of voltage sensor domain exists, but two different modes of voltage sensor attachment to the pore occur in nature: domain-swapped and non-domain-swapped. Since the more thoroughly studied Kv1-7, Nav and Cav channels have domain-swapped voltage sensors, much less is known about non-domain-swapped voltage-gated ion channels. In this paper, using cryo-EM, we show that KvAP from Aeropyrum pernix has non-domain-swapped voltage sensors as well as other unusual features. The new structure, together with previous functional data, suggests that KvAP and the Shaker channel, to which KvAP is most often compared, probably undergo rather different voltage-dependent conformational changes when they open.

Hybrid Electron Microscopy Normal Mode Analysis with Scipion

Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) method was introduced in 2014. HEMNMA computes normal modes of a reference model (an atomic structure or an electron microscopy map) of a molecular complex and uses this model and its normal modes to analyze single-particle images of the complex to obtain information on its continuous conformational changes, by determining the full distribution of conformational variability from the images. An advantage of HEMNMA is a simultaneous determination of all parameters of each image (particle conformation, orientation, and shift) through their iterative optimization, which allows applications of HEMNMA even when the effects of conformational changes dominate those of orientational changes. HEMNMA was first implemented in Xmipp and was using MATLAB for statistical analysis of obtained conformational distributions and for fitting of underlying trajectories of conformational changes. A HEMNMA implementation independent of MATLAB is now available as part of a plugin of Scipion V2.0 (http://scipion.i2pc.es). This plugin, named ContinuousFlex, can be installed by following the instructions at https://pypi.org/project/scipion-em-continuousflex. In this article, we present this new HEMNMA software, which is user-friendly, totally free, and open-source. STATEMENT FOR A BROADER AUDIENCE: This article presents Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) software that allows analyzing single-particle images of a complex to obtain information on continuous conformational changes of the complex, by determining the full distribution of conformational variability from the images. The HEMNMA software is user-friendly, totally free, open-source, and available as part of ContinuousFlex plugin (https://pypi.org/project/scipion-em-continuousflex) of Scipion V2.0 (http://scipion.i2pc.es).