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, αVß8 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.

Improving Protein-Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge.

Elucidating protein-ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein-ligand interaction is traditionally tackled by molecular docking and simulation, which is based on physical forces and statistical potentials and cannot effectively leverage cryo-EM data and existing protein structural information in the protein-ligand modeling process. In this work, we developed a deep learning bioinformatics pipeline (DeepProLigand) to predict protein-ligand interactions from cryo-EM density maps of proteins and ligands. DeepProLigand first uses a deep learning method to predict the structure of proteins from cryo-EM maps, which is averaged with a reference (template) structure of the proteins to produce a combined structure to add ligands. The ligands are then identified and added into the structure to generate a protein-ligand complex structure, which is further refined. The method based on the deep learning prediction and template-based modeling was blindly tested in the 2021 EMDataResource Ligand Challenge and was ranked first in fitting ligands to cryo-EM density maps. These results demonstrate that the deep learning bioinformatics approach is a promising direction for modeling protein-ligand interactions on cryo-EM data using prior structural information.

Epoxidized graphene grid for highly efficient high-resolution cryoEM structural analysis.

Functionalization of graphene is one of the most important fundamental technologies in a wide variety of fields including industry and biochemistry. We have successfully achieved a novel oxidative modification of graphene using photoactivated ClO2· as a mild oxidant and confirmed the oxidized graphene grid is storable with its functionality for at least three months under N2 atmosphere. Subsequent chemical functionalization enabled us to develop an epoxidized graphene grid (EG-grid™), which effectively adsorbs protein particles for electron cryomicroscopy (cryoEM) image analysis. The EG-grid dramatically improved the particle density and orientation distribution. The density maps of GroEL and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were reconstructed at 1.99 and 2.16 Å resolution from only 504 and 241 micrographs, respectively. A sample solution of 0.1 mg ml-1 was sufficient to reconstruct a 3.10 Å resolution map of SARS-CoV-2 spike protein from 1163 micrographs. The map resolutions of ß-galactosidase and apoferritin easily reached 1.81 Å and 1.29 Å resolution, respectively, indicating its atomic-resolution imaging capability. Thus, the EG-grid will be an extremely powerful tool for highly efficient high-resolution cryoEM structural analysis of biological macromolecules.

Improved AlphaFold modeling with implicit experimental information.

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.

Electron cryotomography of SARS-CoV-2 virions reveals cylinder-shaped particles with a double layer RNP assembly.

SARS-CoV-2 is a lipid-enveloped Betacoronavirus and cause of the Covid-19 pandemic. To study the three-dimensional architecture of the virus, we perform electron cryotomography (cryo-ET) on SARS-Cov-2 virions and three variants revealing particles of regular cylindrical morphology. The ribonucleoprotein particles packaging the genome in the virion interior form a dense, double layer assembly with a cylindrical shape related to the overall particle morphology. This organisation suggests structural interactions important to virus assembly.

Cryo-electron tomography of enveloped viruses.

Viruses are macromolecular machineries that hijack cellular metabolism for replication. Enveloped viruses comprise a large variety of RNA and DNA viruses, many of which are notorious human or animal pathogens. Despite their importance, the presence of lipid bilayers in their assembly has made most enveloped viruses too pleomorphic to be reconstructed as a whole by traditional structural biology methods. Furthermore, structural biology of the viral lifecycle was hindered by the sample thickness. Here, I review the recent advances in the applications of cryo-electron tomography (cryo-ET) on enveloped viral structures and intracellular viral activities.

Advancing High-Resolution Imaging of Virus Assemblies in Liquid and Ice.

Interest in liquid-electron microscopy (liquid-EM) has skyrocketed in recent years as scientists can now observe real-time processes at the nanoscale. It is extremely desirable to pair high-resolution cryo-EM information with dynamic observations as many events occur at rapid timescales - in the millisecond range or faster. Improved knowledge of flexible structures can also assist in the design of novel reagents to combat emerging pathogens, such as SARS-CoV-2. More importantly, viewing biological materials in a fluid environment provides a unique glimpse of their performance in the human body. Presented here are newly developed methods to investigate the nanoscale properties of virus assemblies in liquid and vitreous ice. To accomplish this goal, well-defined samples were used as model systems. Side-by-side comparisons of sample preparation methods and representative structural information are presented. Sub-nanometer features are shown for structures resolved in the range of ~3.5-Å-10 Å. Other recent results that support this complementary framework include dynamic insights of vaccine candidates and antibody-based therapies imaged in liquid. Overall, these correlative applications advance our ability to visualize molecular dynamics, providing a unique context for their use in human health and disease.

Overview and applications of map and model validation tools in the CCP-EM software suite.

Cryogenic electron microscopy (cryo-EM) has recently been established as a powerful technique for solving macromolecular structures. Although the best resolutions achievable are improving, a significant majority of data are still resolved at resolutions worse than 3 Å, where it is non-trivial to build or fit atomic models. The map reconstructions and atomic models derived from the maps are also prone to errors accumulated through the different stages of data processing. Here, we highlight the need to evaluate both model geometry and fit to data at different resolutions. Assessment of cryo-EM structures from SARS-CoV-2 highlights a bias towards optimising the model geometry to agree with the most common conformations, compared to the agreement with data. We present the CoVal web service which provides multiple validation metrics to reflect the quality of atomic models derived from cryo-EM data of structures from SARS-CoV-2. We demonstrate that further refinement can lead to improvement of the agreement with data without the loss of geometric quality. We also discuss the recent CCP-EM developments aimed at addressing some of the current shortcomings.

Cryo-electron Tomography Remote Data Collection and Subtomogram Averaging.

Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved automated acquisition strategies, preparative techniques that expand the possibilities of what the electron microscope can image at high-resolution using cryo-ET and new subtomogram averaging software. Additionally, data acquisition has become increasingly streamlined, making it more accessible to many users. The SARS-CoV-2 pandemic has further accelerated remote cryo-electron microscopy (cryo-EM) data collection, especially for single-particle cryo-EM, in many facilities globally, providing uninterrupted user access to state-of-the-art instruments during the pandemic. With the recent advances in Tomo5 (software for 3D electron tomography), remote cryo-ET data collection has become robust and easy to handle from anywhere in the world. This article aims to provide a detailed walk-through, starting from the data collection setup in the tomography software for the process of a (remote) cryo-ET data collection session with detailed troubleshooting. The (remote) data collection protocol is further complemented with the workflow for structure determination at near-atomic resolution by subtomogram averaging with emClarity, using apoferritin as an example.

Sequence-assignment validation in cryo-EM models with checkMySequence.

The availability of new artificial intelligence-based protein-structure-prediction tools has radically changed the way that cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models will continue to be locally rebuilt and refined using interactive tools. This inevitably results in occasional errors, among which register shifts remain one of the most difficult to identify and correct. Here, checkMySequence, a fast, fully automated and parameter-free method for detecting register shifts in protein models built into cryo-EM maps, is introduced. It is shown that the method can assist model building in cases where poorer map resolution hinders visual interpretation. It is also shown that checkMySequence could have helped to avoid a widely discussed sequence-register error in a model of SARS-CoV-2 RNA-dependent RNA polymerase that was originally detected thanks to a visual residue-by-residue inspection by members of the structural biology community. The software is freely available at https://gitlab.com/gchojnowski/checkmysequence.

Refined Capsid Structure of Human Adenovirus D26 at 3.4 Å Resolution.

Various adenoviruses are being used as viral vectors for the generation of vaccines against chronic and emerging diseases (e.g., AIDS, COVID-19). Here, we report the improved capsid structure for one of these vectors, human adenovirus D26 (HAdV-D26), at 3.4 Å resolution, by reprocessing the previous cryo-electron microscopy dataset and obtaining a refined model. In addition to overall improvements in the model, the highlights of the structure include (1) locating a segment of the processed peptide of VIII that was previously believed to be released from the mature virions, (2) reorientation of the helical appendage domain (APD) of IIIa situated underneath the vertex region relative to its counterpart observed in the cleavage defective (ts1) mutant of HAdV-C5 that resulted in the loss of interactions between the APD and hexon bases, and (3) the revised conformation of the cleaved N-terminal segments of pre-protein VI (pVIn), located in the hexon cavities, is highly conserved, with notable stacking interactions between the conserved His13 and Phe18 residues. Taken together, the improved model of HAdV-D26 capsid provides a better understanding of protein-protein interactions in HAdV capsids and facilitates the efforts to modify and/or design adenoviral vectors with altered properties. Last but not least, we provide some insights into clotting factors (e.g., FX and PF4) binding to AdV vectors.

Better, Faster, Cheaper: Recent Advances in Cryo-Electron Microscopy.

Cryo-electron microscopy (cryo-EM) continues its remarkable growth as a method for visualizing biological objects, which has been driven by advances across the entire pipeline. Developments in both single-particle analysis and in situ tomography have enabled more structures to be imaged and determined to better resolutions, at faster speeds, and with more scientists having improved access. This review highlights recent advances at each stageof the cryo-EM pipeline and provides examples of how these techniques have been used to investigate real-world problems, including antibody development against the SARS-CoV-2 spike during the recent COVID-19 pandemic.

Synthetic virions reveal fatty acid-coupled adaptive immunogenicity of SARS-CoV-2 spike glycoprotein.

SARS-CoV-2 infection is a major global public health concern with incompletely understood pathogenesis. The SARS-CoV-2 spike (S) glycoprotein comprises a highly conserved free fatty acid binding pocket (FABP) with unknown function and evolutionary selection advantage1,2. Deciphering FABP impact on COVID-19 progression is challenged by the heterogenous nature and large molecular variability of live virus. Here we create synthetic minimal virions (MiniVs) of wild-type and mutant SARS-CoV-2 with precise molecular composition and programmable complexity by bottom-up assembly. MiniV-based systematic assessment of S free fatty acid (FFA) binding reveals that FABP functions as an allosteric regulatory site enabling adaptation of SARS-CoV-2 immunogenicity to inflammation states via binding of pro-inflammatory FFAs. This is achieved by regulation of the S open-to-close equilibrium and the exposure of both, the receptor binding domain (RBD) and the SARS-CoV-2 RGD motif that is responsible for integrin co-receptor engagement. We find that the FDA-approved drugs vitamin K and dexamethasone modulate S-based cell binding in an FABP-like manner. In inflammatory FFA environments, neutralizing immunoglobulins from human convalescent COVID-19 donors lose neutralization activity. Empowered by our MiniV technology, we suggest a conserved mechanism by which SARS-CoV-2 dynamically couples its immunogenicity to the host immune response.

High Molecular Weight Kininogen: A Review of the Structural Literature.

Kininogens are multidomain glycoproteins found in the blood of most vertebrates. High molecular weight kininogen demonstrate both carrier and co-factor activity as part of the intrinsic pathway of coagulation, leading to thrombin generation. Kininogens are the source of the vasoactive nonapeptide bradykinin. To date, attempts to crystallize kininogen have failed, and very little is known about the shape of kininogen at an atomic level. New advancements in the field of cryo-electron microscopy (cryoEM) have enabled researchers to crack the structure of proteins that has been refractory to traditional crystallography techniques. High molecular weight kininogen is a good candidate for structural investigation by cryoEM. The goal of this review is to summarize the findings of kininogen structural studies.

Cryo-EM structure determination of small proteins by nanobody-binding scaffolds (Legobodies).

We describe a general method that allows structure determination of small proteins by single-particle cryo-electron microscopy (cryo-EM). The method is based on the availability of a target-binding nanobody, which is then rigidly attached to two scaffolds: 1) a Fab fragment of an antibody directed against the nanobody and 2) a nanobody-binding protein A fragment fused to maltose binding protein and Fab-binding domains. The overall ensemble of ∼120 kDa, called Legobody, does not perturb the nanobody-target interaction, is easily recognizable in EM images due to its unique shape, and facilitates particle alignment in cryo-EM image processing. The utility of the method is demonstrated for the KDEL receptor, a 23-kDa membrane protein, resulting in a map at 3.2-Šoverall resolution with density sufficient for de novo model building, and for the 22-kDa receptor-binding domain (RBD) of SARS-CoV-2 spike protein, resulting in a map at 3.6-Šresolution that allows analysis of the binding interface to the nanobody. The Legobody approach thus overcomes the current size limitations of cryo-EM analysis.

From cells to atoms: Cryo-EM as an essential tool to investigate pathogen biology, host-pathogen interaction, and drug discovery.

Electron cryo-microscopy (cryo-EM) has lately emerged as a powerful method in structural biology and cell biology. While cryo-EM single-particle analysis (SPA) is now routinely delivering structures of purified proteins and protein complexes at near-atomic resolution, the use of electron cryo-tomography (cryo-ET), together with subtomogram averaging, is allowing visualization of macromolecular complexes in their native cellular environment, at unprecedented resolution. The unique ability of cryo-EM to provide information at many spatial resolution scales from ångströms to microns makes it an invaluable tool that bridges the classic "resolution-gap" between structural biology and cell biology domains. Like in many other fields of biology, in recent years, cryo-EM has revolutionized our understanding of pathogen biology, host-pathogen interaction and has made significant strides toward structure-based drug discovery. In a very recent example, during the ongoing coronavirus disease (COVID-19) pandemic, the structure of the stabilized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein was deciphered by SPA. This led to the development of multiple vaccines. Alongside, cryo-ET provided key insights into the structure of the native virion, mechanism of its entry, replication, and budding; demonstrating the unrivaled power of cryo-EM in investigating pathogen biology, host-pathogen interaction, and drug discovery. In this review, we showcase a few examples of how different imaging modalities within cryo-EM have enabled the study of microbiology and host-pathogen interaction.

Landscape of human antibody recognition of the SARS-CoV-2 receptor binding domain.

Potent neutralizing monoclonal antibodies are one of the few agents currently available to treat COVID-19. SARS-CoV-2 variants of concern (VOCs) that carry multiple mutations in the viral spike protein can exhibit neutralization resistance, potentially affecting the effectiveness of some antibody-based therapeutics. Here, the generation of a diverse panel of 91 human, neutralizing monoclonal antibodies provides an in-depth structural and phenotypic definition of receptor binding domain (RBD) antigenic sites on the viral spike. These RBD antibodies ameliorate SARS-CoV-2 infection in mice and hamster models in a dose-dependent manner and in proportion to in vitro, neutralizing potency. Assessing the effect of mutations in the spike protein on antibody recognition and neutralization highlights both potent single antibodies and stereotypic classes of antibodies that are unaffected by currently circulating VOCs, such as B.1.351 and P.1. These neutralizing monoclonal antibodies and others that bind analogous epitopes represent potentially useful future anti-SARS-CoV-2 therapeutics.

An overview of human proteins and genes involved in SARS-CoV-2 infection.

As of July 2021, the outbreak of coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has led to more than 200 million infections and more than 4.2 million deaths globally. Complications of severe COVID-19 include acute kidney injury, liver dysfunction, cardiomyopathy, and coagulation dysfunction. Thus, there is an urgent need to identify proteins and genetic factors associated with COVID-19 susceptibility and outcome. We comprehensively reviewed recent findings of host-SARS-CoV-2 interactome analyses. To identify genetic variants associated with COVID-19, we focused on the findings from genome and transcriptome wide association studies (GWAS and TWAS) and bioinformatics analysis. We described established human proteins including ACE2, TMPRSS2, 40S ribosomal subunit, ApoA1, TOM70, HLA-A, and PALS1 interacting with SARS-CoV-2 based on cryo-electron microscopy results. Furthermore, we described approximately 1000 human proteins showing evidence of interaction with SARS-CoV-2 and highlighted host cellular processes such as innate immune pathways affected by infection. We summarized the evidence on more than 20 identified candidate genes in COVID-19 severity. Predicted deleterious and disruptive genetic variants with possible effects on COVID-19 infectivity have been also summarized. These findings provide novel insights into SARS-CoV-2 biology and infection as well as potential strategies for development of novel COVID therapeutic targets and drug repurposing.

Cryo-EM and antisense targeting of the 28-kDa frameshift stimulation element from the SARS-CoV-2 RNA genome.

Drug discovery campaigns against COVID-19 are beginning to target the SARS-CoV-2 RNA genome. The highly conserved frameshift stimulation element (FSE), required for balanced expression of viral proteins, is a particularly attractive SARS-CoV-2 RNA target. Here we present a 6.9 Å resolution cryo-EM structure of the FSE (88 nucleotides, ~28 kDa), validated through an RNA nanostructure tagging method. The tertiary structure presents a topologically complex fold in which the 5' end is threaded through a ring formed inside a three-stem pseudoknot. Guided by this structure, we develop antisense oligonucleotides that impair FSE function in frameshifting assays and knock down SARS-CoV-2 virus replication in A549-ACE2 cells at 100 nM concentration.

User-friendly, High-throughput, and Fully Automated Data Acquisition Software for Single-particle Cryo-electron Microscopy.

In the past several years, technological and methodological advancements in single-particle cryo-electron microscopy (cryo-EM) have paved a new avenue for the high-resolution structure determination of biological macromolecules. Despite the remarkable advances in cryo-EM, there is still scope for improvement in various aspects of the single-particle analysis workflow. Single-particle analysis demands a suitable software package for high-throughput automatic data acquisition. Several automatic data acquisition software packages were developed for automatic imaging for single-particle cryo-EM in the last eight years. This paper presents an application of a fully automated image acquisition pipeline for vitrified biomolecules under low-dose conditions. It demonstrates a software package, which can collect cryo-EM data fully, automatically, and precisely. Additionally, various microscopic parameters are easily controlled by this software package. This protocol demonstrates the potential of this software package in automated imaging of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) spike protein with a 200 keV cryo-electron microscope equipped with a direct electron detector (DED). Around 3,000 cryo-EM movie images were acquired in a single session (48 h) of data collection, yielding an atomic-resolution structure of the spike protein of SARS-CoV-2. Furthermore, this structural study indicates that the spike protein adopts two major conformations, 1-RBD (receptor-binding domain) up open and all RBD down closed conformations.