Single-particle cryo-electron microscopy of macromolecular complexes

The graphene-based affinity cryo-EM grid for the endogenous protein structure determination

Following recent advancements in cryo-electron microscopy (cryo-EM) instrumentation and software algorithms, the next bottleneck in achieving high-resolution cryo-EM structures arises from sample preparation. To overcome this, we developed a graphene-based affinity cryo-EM grid, the Graffendor (GFD) grid, to target low-abundance endogenous protein complexes. To maintain grid quality and consistency within a single batch of 36 grids, we established a one-step crosslinking batch-production method using genetically modified ALFA nanobody as affinity probe (GFD-A grid). Using low concentrations of β-galactosidase-2xALFA, we demonstrated the GFD-A grid's efficiency in capturing tagged proteins and resolving its cryo-EM structure at 2.71 Å. To test its application for endogenous proteins, we engineered yeast cells with a C-terminal tandem affinity tag (3xALFA-Tev-3xFlag: ATF) at Pop6, a shared component of RNase MRP and RNase P. Cryo-EM structures of RNase MRP and RNase P were resolved at 3.3 Å and 3.0 Å from cell lysates, and 3.6 Å and 3.9 Å from anti-flag elution, respectively. Notably, additional densities were observed in the structures obtained from cell lysates, which were absent in those from the anti-FLAG eluate. These findings establish the GFD-A grid as a robust platform for investigating endogenous proteins, capable of capturing transient interactions and enhancing the resolution of challenging cryo-EM structures with greater efficiency.

Conventional Electron Microscopy, Cryogenic Electron Microscopy, and Cryogenic Electron Tomography of Viruses

Electron microscopy (EM) techniques have been crucial for understanding the structure of biological specimens such as cells, tissues and macromolecular assemblies. Viruses and related viral assemblies are ideal targets for structural studies that help to define essential biological functions. Whereas conventional EM methods use chemical fixation, dehydration, and staining of the specimens, cryogenic electron microscopy (cryo-EM) preserves the native hydrated state. Combined with image processing and three-dimensional reconstruction techniques, cryo-EM provides three-dimensional maps of these macromolecular complexes from projection images, at atomic or near-atomic resolutions. Cryo-EM is also a major technique in structural biology for dynamic studies of functional complexes, which are often unstable, flexible, scarce, or transient in their native environments. State-of-the-art techniques in structural virology now extend beyond purified symmetric capsids and focus on the asymmetric elements such as the packaged genome and minor structural proteins that were previously missed. As a tool, cryo-EM also complements high-resolution techniques such as X-ray diffraction and NMR spectroscopy; these synergistic hybrid approaches provide important new information. Three-dimensional cryogenic electron tomography (cryo-ET), a variation of cryo-EM, goes further, and allows the study of pleomorphic and complex viruses not only in their physiological state but also in their natural environment in the cell, thereby bridging structural studies at the molecular and cellular levels. Cryo-EM and cryo-ET have been applied successfully in basic research, shedding light on fundamental aspects of virus biology and providing insights into threatening viruses, including SARS-CoV-2, responsible for the COVID-19 pandemic.

Discerning conformational dynamics and binding kinetics of GPCRs by 19F NMR

19F NMR provides a way of monitoring conformational dynamics of G-protein coupled receptors (GPCRs) from the perspective of an ensemble. While X-ray crystallography provides exquisitely resolved high-resolution structures of specific states, it generally does not recapitulate the true ensemble of functional states. Fluorine (19F) NMR provides a highly sensitive spectroscopic window into the conformational ensemble, generally permitting the direct quantification of resolvable states. Moreover, straightforward T1- and T2-based relaxation experiments allow for the study of fluctuations within a given state and exchange between states, on timescales spanning nanoseconds to seconds. Conveniently, most biological systems are free of fluorine. Thus, via fluorinated amino acid analogues or thiol-reactive fluorinated tags, F or CF3 reporters can be site specifically incorporated into proteins of interest. In this review, fluorine labeling protocols and 19F NMR experiments will be presented, from the perspective of small molecule NMR (i.e. drug or small molecule interactions with receptors) or macromolecular NMR (i.e. conformational dynamics of receptors and receptor-G-protein complexes).

Strategic outline of interventions targeting extracellular matrix for promoting healthy longevity

The extracellular matrix (ECM), composed of interlinked proteins outside of cells, is an important component of the human body that helps maintain tissue architecture and cellular homeostasis. As people age, the ECM undergoes changes that can lead to age-related morbidity and mortality. Despite its importance, ECM aging remains understudied in the field of geroscience. In this review, we discuss the core concepts of ECM integrity, outline the age-related challenges and subsequent pathologies and diseases, summarize diagnostic methods detecting a faulty ECM, and provide strategies targeting ECM homeostasis. To conceptualize this, we built a technology research tree to hierarchically visualize possible research sequences for studying ECM aging. This strategic framework will hopefully facilitate the development of future research on interventions to restore ECM integrity, which could potentially lead to the development of new drugs or therapeutic interventions promoting health during aging.

Unsupervised Cryo-EM Images Denoising and Clustering Based on Deep Convolutional Autoencoder and K-Means+

Cryo-electron microscopy (cryo-EM) is a widely used structural determination technique. Because of the extremely low signal-to-noise ratio (SNR) of images captured by cryo-EM, clustering single-particle cryo-EM images with high accuracy is challenging. To address this, we proposed an iterative denoising and clustering method based on a deep convolutional variational autoencoder and K-means++. The proposed method contains two modules: a denoising ResNet variational autoencoder (DRVAE), and Balance size K-means++ (BSK-means++). First, the DRVAE is trained in a fully unsupervised manner to initialize the neural network and obtain preliminary denoised images. Second, BSK-means++ is built for clustering denoised images, and images closer to class centers are divided into reliable samples. Third, the training of DRVAE is continued, while the class-average images are used as pseudo supervision of reliable samples to reserve more detailed information of denoised images. Finally, the second and third steps mentioned above can be performed jointly and iteratively until convergence occurs. The experimental results showed that the proposed method can generate reliable class average images and achieve better clustering accuracy and normalized mutual information than current methods. This study confirmed that DRVAE with BSK-means++ could achieve a good denoise performance on single-particle cryo-EM images, which can help researchers obtain information such as symmetry and heterogeneity of the target particles. In addition, the proposed method avoids the extreme imbalance of class size, which improves the reliability of the clustering result.

DNA Origami Curvature Sensors for Nanoparticle and Vesicle Size Determination with Single-Molecule FRET Readout

Particle size is an important characteristic of materials with a direct effect on their physicochemical features. Besides nanoparticles, particle size and surface curvature are particularly important in the world of lipids and cellular membranes as the cell membrane undergoes conformational changes in many biological processes which leads to diverging local curvature values. On account of that, it is important to develop cost-effective, rapid and sufficiently precise systems that can measure the surface curvature on the nanoscale that can be translated to size for spherical particles. As an alternative approach for particle characterization, we present flexible DNA nanodevices that can adapt to the curvature of the structure they are bound to. The curvature sensors use Fluorescence Resonance Energy Transfer (FRET) as the transduction mechanism on the single-molecule level. The curvature sensors consist of segmented DNA origami structures connected via flexible DNA linkers incorporating a FRET pair. The activity of the sensors was first demonstrated with defined binding to different DNA origami geometries used as templates. Then the DNA origami curvature sensors were applied to measure spherical silica beads having different size, and subsequently on lipid vesicles. With the designed sensors, we could reliably distinguish different sized nanoparticles within a size range of 50-300 nm as well as the bending angle range of 50-180°. This study helps with the development of more advanced modular-curvature sensing devices that are capable of determining the sizes of nanoparticles and biological complexes.

Exact gram filtering and efficient back projection for iterative CT reconstruction

PURPOSE

Forward and back-projections are the basis of all model-based iterative reconstruction (MBIR) methods. However, computing these accurately is time consuming. In this paper, we present a method for model-based iterative reconstruction in parallel X-ray beam geometry that utilizes a Gram filter to efficiently implement forward and back projection.

METHODS

We propose using voxel-basis and modeling its footprint in a box spline framework to calculate the Gram filter exactly and improve the performance of back-projection. In the special case of parallel X-ray beam geometry, the forward and back-projection can be implemented by an estimated Gram filter efficiently if the sinogram signal is bandlimited. In this paper, a specialized sinogram interpolation method is proposed to eliminate the bandlimited prerequisite and thus improve the reconstruction accuracy. We build on this idea by utilizing the continuity of the voxel-basis' footprint, which provides a more accurate sinogram interpolation and further improves the efficiency and quality of back-projection. In addition, the detector blur effect can be efficiently accounted for in our method to better handle realistic scenarios.

RESULTS

The proposed method is tested on both phantom and real CT images under different resolutions, sinogram sampling steps, and noise levels. The proposed method consistently outperforms other state-of-the-art projection models in terms of speed and accuracy for both back-projection and reconstruction.

CONCLUSIONS

We proposed a iterative reconstruction methodology for 3D parallel-beam X-ray CT reconstruction. Our experimental results demonstrate that the proposed methodology is accurate, fast, and reproducible, and outperforms alternative state-of-the-art projection models on both back-projection and reconstruction results significantly. This article is protected by copyright. All rights reserved.

Sequence Divergence and Functional Specializations of the Ancient Spliceosomal SF3b: Implications in Flexibility and Adaptations of the Multi-Protein Complex

Multi-protein assemblies are complex molecular systems that perform highly sophisticated biochemical functions in an orchestrated manner. They are subject to changes that are governed by the evolution of individual components. We performed a comparative analysis of the ancient and functionally conserved spliceosomal SF3b complex, to recognize molecular signatures that contribute to sequence divergence and functional specializations. For this, we recognized homologous sequences of individual SF3b proteins distributed across 10 supergroups of eukaryotes and identified all seven protein components of the complex in 578 eukaryotic species. Using sequence and structural analysis, we establish that proteins occurring on the surface of the SF3b complex harbor more sequence variation than the proteins that lie in the core. Further, we show through protein interface conservation patterns that the extent of conservation varies considerably between interacting partners. When we analyze phylogenetic distributions of individual components of the complex, we find that protein partners that are known to form independent subcomplexes are observed to share similar profiles, reaffirming the link between differential conservation of interface regions and their inter-dependence. When we extend our analysis to individual protein components of the complex, we find taxa-specific variability in molecular signatures of the proteins. These trends are discussed in the context of proline-rich motifs of SF3b4, functional and drug binding sites of SF3b1. Further, we report key protein-protein interactions between SF3b1 and SF3b6 whose presence is observed to be lineage-specific across eukaryotes. Together, our studies show the association of protein location within the complex and subcomplex formation patterns with the sequence conservation of SF3b proteins. In addition, our study underscores evolutionarily flexible elements that appear to confer adaptive features in individual components of the multi-protein SF3b complexes and may contribute to its functional adaptability.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.

Protein scaffolds: A tool for multi-enzyme assembly

The synthesis of complex molecules using multiple enzymes simultaneously in one reaction vessel has rapidly emerged as a new frontier in the field of bioprocess technology. However, operating different enzymes together in a single vessel limits their operational performance which needs to be addressed. With this respect, scaffolding proteins play an immense role in bringing different enzymes together in a specific manner. The scaffolding improves the catalytic performance, enzyme stability and provides an optimal micro-environment for biochemical reactions. This review describes the components of protein scaffolds, different ways of constructing a protein scaffold-based multi-enzyme complex, and their effects on enzyme kinetics. Moreover, different conjugation strategies viz; dockerin-cohesin interaction, SpyTag-SpyCatcher system, peptide linker-based ligation, affibody, and sortase-mediated ligation are discussed in detail. Various analytical and characterization tools that have enabled the development of these scaffolding strategies are also reviewed. Such mega-enzyme complexes promise wider applications in the field of biotechnology and bioengineering.

N-terminal Transmembrane-Helix Epitope Tag for X-ray Crystallography and Electron Microscopy of Small Membrane Proteins

Structural studies of membrane proteins, especially small membrane proteins, are associated with well-known experimental challenges. Complexation with monoclonal antibody fragments is a common strategy to augment such proteins; however, generating antibody fragments that specifically bind a target protein is not trivial. Here we identify a helical epitope, from the membrane-proximal external region (MPER) of the gp41-transmembrane subunit of the HIV envelope protein, that is recognized by several well-characterized antibodies and that can be fused as a contiguous extension of the N-terminal transmembrane helix of a broad range of membrane proteins. To analyze whether this MPER-epitope tag might aid structural studies of small membrane proteins, we determined an X-ray crystal structure of a membrane protein target that does not crystallize without the aid of crystallization chaperones, the Fluc fluoride channel, fused to the MPER epitope and in complex with antibody. We also demonstrate the utility of this approach for single particle electron microscopy with Fluc and two additional small membrane proteins that represent different membrane protein folds, AdiC and GlpF. These studies show that the MPER epitope provides a structurally defined, rigid docking site for antibody fragments that is transferable among diverse membrane proteins and can be engineered without prior structural information. Antibodies that bind to the MPER epitope serve as effective crystallization chaperones and electron microscopy fiducial markers, enabling structural studies of challenging small membrane proteins.

A basic introduction to single particles cryo-electron microscopy

<abstract> <p>In the last years, cryogenic-electron microscopy (cryo-EM) underwent the most impressive improvement compared to other techniques used in structural biology, such as X-ray crystallography and NMR. Electron microscopy was invented nearly one century ago but, up to the beginning of the last decades, the 3D maps produced through this technique were poorly detailed, justifying the term “blobbology” to appeal to cryo-EM. Recently, thanks to a new generation of microscopes and detectors, more efficient algorithms, and easier access to computational power, single particles cryo-EM can routinely produce 3D structures at resolutions comparable to those obtained with X-ray crystallography. However, unlike X-ray crystallography, which needs crystallized proteins, cryo-EM exploits purified samples in solution, allowing the study of proteins and protein complexes that are hard or even impossible to crystallize. For these reasons, single-particle cryo-EM is often the first choice of structural biologists today. Nevertheless, before starting a cryo-EM experiment, many drawbacks and limitations must be considered. Moreover, in practice, the process between the purified sample and the final structure could be trickier than initially expected. Based on these observations, this review aims to offer an overview of the principal technical aspects and setups to be considered while planning and performing a cryo-EM experiment.</p> </abstract>

Deep-learning with synthetic data enables automated picking of cryo-EM particle images of biological macromolecules

MOTIVATION

Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique for determining 3D structures of biological macromolecules at near-atomic resolution. However, this approach requires picking huge numbers of macromolecular particle images from thousands of low-contrast, high-noisy electron micrographs. Although machine-learning methods were developed to get rid of this bottleneck, it still lacks universal methods that could automatically picking the noisy cryo-EM particles of various macromolecules.

RESULTS

Here, we present a deep-learning segmentation model that employs fully convolutional networks trained with synthetic data of known 3D structures, called PARSED (PARticle SEgmentation Detector). Without using any experimental information, PARSED could automatically segment the cryo-EM particles in a whole micrograph at a time, enabling faster particle picking than previous template/feature-matching and particle-classification methods. Applications to six large public cryo-EM datasets clearly validated its universal ability to pick macromolecular particles of various sizes. Thus, our deep-learning method could break the particle-picking bottleneck in the single-particle analysis, and thereby accelerates the high-resolution structure determination by cryo-EM.

AVAILABILITY AND IMPLEMENTATION

The PARSED package and user manual for noncommercial use are available as Supplementary Material (in the compressed file: parsed_v1.zip).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Antigen-Antibody Complexes

In vertebrates, immunoglobulins (Igs), commonly known as antibodies, play an integral role in the armamentarium of immune defense against various pathogens. After an antigenic challenge, antibodies are secreted by differentiated B cells called plasma cells. Antibodies have two predominant roles that involve specific binding to antigens to launch an immune response, along with activation of other components of the immune system to fight pathogens. The ability of immunoglobulins to fight against innumerable and diverse pathogens lies in their intrinsic ability to discriminate between different antigens. Due to this specificity and high affinity for their antigens, antibodies have been a valuable and indispensable tool in research, diagnostics and therapy. Although seemingly a simple maneuver, the association between an antibody and its antigen, to make an antigen-antibody complex, is comprised of myriads of non-covalent interactions. Amino acid residues on the antigen binding site, the epitope, and on the antibody binding site, the paratope, intimately contribute to the energetics needed for the antigen-antibody complex stability. Structural biology methods to study antigen-antibody complexes are extremely valuable tools to visualize antigen-antibody interactions in detail; this helps to elucidate the basis of molecular recognition between an antibody and its specific antigen. The main scope of this chapter is to discuss the structure and function of different classes of antibodies and the various aspects of antigen-antibody interactions including antigen-antibody interfaces-with a special focus on paratopes, complementarity determining regions (CDRs) and other non-CDR residues important for antigen binding and recognition. Herein, we also discuss methods used to study antigen-antibody complexes, antigen recognition by antibodies, types of antigens in complexes, and how antigen-antibody complexes play a role in modern day medicine and human health. Understanding the molecular basis of antigen binding and recognition by antibodies helps to facilitate the production of better and more potent antibodies for immunotherapy, vaccines and various other applications.

Structure Determination by Single-Particle Cryo-Electron Microscopy: Only the Sky (and Intrinsic Disorder) is the Limit

Traditionally, X-ray crystallography and NMR spectroscopy represent major workhorses of structural biologists, with the lion share of protein structures reported in protein data bank (PDB) being generated by these powerful techniques. Despite their wide utilization in protein structure determination, these two techniques have logical limitations, with X-ray crystallography being unsuitable for the analysis of highly dynamic structures and with NMR spectroscopy being restricted to the analysis of relatively small proteins. In recent years, we have witnessed an explosive development of the techniques based on Cryo-electron microscopy (Cryo-EM) for structural characterization of biological molecules. In fact, single-particle Cryo-EM is a special niche as it is a technique of choice for the structural analysis of large, structurally heterogeneous, and dynamic complexes. Here, sub-nanometer atomic resolution can be achieved (i.e., resolution below 10 Å) via single-particle imaging of non-crystalline specimens, with accurate 3D reconstruction being generated based on the computational averaging of multiple 2D projection images of the same particle that was frozen rapidly in solution. We provide here a brief overview of single-particle Cryo-EM and show how Cryo-EM has revolutionized structural investigations of membrane proteins. We also show that the presence of intrinsically disordered or flexible regions in a target protein represents one of the major limitations of this promising technique.

Spiraling in Control: Structures and Mechanisms of the Hsp104 Disaggregase

Hsp104 is a hexameric AAA⁺ ATPase and protein disaggregase found in yeast, which couples ATP hydrolysis to the dissolution of diverse polypeptides trapped in toxic preamyloid oligomers, phase-transitioned gels, disordered aggregates, amyloids, and prions. Hsp104 shows plasticity in disaggregating diverse substrates, but how its hexameric architecture operates as a molecular machine has remained unclear. Here, we highlight structural advances made via cryoelectron microscopy (cryo-EM) that enhance our mechanistic understanding of Hsp104 and other related AAA⁺ translocases. Hsp104 hexamers are dynamic and adopt open "lock-washer" spiral states and closed ring structures that envelope polypeptide substrate inside the axial channel. ATP hydrolysis-driven conformational changes at the spiral seam ratchet substrate deeper into the channel. Remarkably, this mode of polypeptide translocation is reminiscent of models for how hexameric helicases unwind DNA and RNA duplexes. Thus, Hsp104 likely adapts elements of a deeply rooted, ring-translocase mechanism to the specialized task of protein disaggregation.

Structural nanotechnology: three-dimensional cryo-EM and its use in the development of nanoplatforms for in vitro catalysis

The organization of enzymes into different subcellular compartments is essential for correct cell function. Protein-based cages are a relatively recently discovered subclass of structurally dynamic cellular compartments that can be mimicked in the laboratory to encapsulate enzymes. These synthetic structures can then be used to improve our understanding of natural protein-based cages, or as nanoreactors in industrial catalysis, metabolic engineering, and medicine. Since the function of natural protein-based cages is related to their three-dimensional structure, it is important to determine this at the highest possible resolution if viable nanoreactors are to be engineered. Cryo-electron microscopy (cryo-EM) is ideal for undertaking such analyses within a feasible time frame and at near-native conditions. This review describes how three-dimensional cryo-EM is used in this field and discusses its advantages. An overview is also given of the nanoreactors produced so far, their structure, function, and applications.

Dynamics of IRES-mediated translation

Viral internal ribosome entry sites (IRESs) are unique RNA elements, which use stable and dynamic RNA structures to recruit ribosomes and drive protein synthesis. IRESs overcome the high complexity of the canonical eukaryotic translation initiation pathway, often functioning with a limited set of eukaryotic initiation factors. The simplest types of IRESs are typified by the cricket paralysis virus intergenic region (CrPV IGR) and hepatitis C virus (HCV) IRESs, both of which independently form high-affinity complexes with the small (40S) ribosomal subunit and bypass the molecular processes of cap-binding and scanning. Owing to their simplicity and ribosomal affinity, the CrPV and HCV IRES have been important models for structural and functional studies of the eukaryotic ribosome during initiation, serving as excellent targets for recent technological breakthroughs in cryogenic electron microscopy (cryo-EM) and single-molecule analysis. High-resolution structural models of ribosome : IRES complexes, coupled with dynamics studies, have clarified decades of biochemical research and provided an outline of the conformational and compositional trajectory of the ribosome during initiation. Here we review recent progress in the study of HCV- and CrPV-type IRESs, highlighting important structural and dynamics insights and the synergy between cryo-EM and single-molecule studies.This article is part of the themed issue 'Perspectives on the ribosome'.

High-Quality Parallel-Ray X-Ray CT Back Projection Using Optimized Interpolation

We propose a new, cost-efficient method for computing back projections in parallel-ray X-ray CT. Forward and back projections are the basis of almost all X-ray CT reconstruction methods, but computing these accurately is costly. In the special case of parallel-ray geometry, it turns out that reconstruction requires back projection only. One approach to accelerate the back projection is through interpolation: fit a continuous representation to samples of the desired signal, then sample it at the required locations. Instead, we propose applying a prefilter that has the effect of orthogonally projecting the underlying signal onto the space spanned by the interpolator, which can significantly improve the quality of the interpolation. We then build on this idea by using oblique projection, which simplifies the computation while giving effectively the same improvement in quality. Our experiments on analytical phantoms show that this refinement can improve the reconstruction quality for both filtered back projection and iterative reconstruction in the high-quality regime, i.e., with low noise and many measurements.

Coming to Grips with Ambiguity: Ion Mobility-Mass Spectrometry for Protein Quaternary Structure Assignment

Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein complexes are too often refractory to analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged as a promising approach for characterizing the structures of challenging assemblies due in large part to the ability of these methods to characterize the composition, connectivity, and topology of large, labile complexes. In this Critical Insight, we present a series of bioinformatics studies aimed at assessing the information content of IM-MS datasets for building models of multiprotein structure. Our computational data highlights the limits of current coarse-graining approaches, and compelled us to develop an improved workflow for multiprotein topology modeling, which we benchmark against a subset of the multiprotein complexes within the PDB. This improved workflow has allowed us to ascertain both the minimal experimental restraint sets required for generation of high-confidence multiprotein topologies, and quantify the ambiguity in models where insufficient IM-MS information is available. We conclude by projecting the future of IM-MS in the context of protein quaternary structure assignment, where we predict that a more complete knowledge of the ultimate information content and ambiguity within such models will undoubtedly lead to applications for a broader array of challenging biomolecular assemblies. Graphical Abstract ᅟ.

Flexible fitting to cryo-EM density map using ensemble molecular dynamics simulations

Flexible fitting is a computational algorithm to derive a new conformational model that conforms to low-resolution experimental data by transforming a known structure. A common application is against data from cryo-electron microscopy to obtain conformational models in new functional states. The conventional flexible fitting algorithms cannot derive correct structures in some cases due to the complexity of conformational transitions. In this study, we show the importance of conformational ensemble in the refinement process by performing multiple fittings trials using a variety of different force constants. Application to simulated maps of Ca²⁺ ATPase and diphtheria toxin as well as experimental data of release factor 2 revealed that for these systems, multiple conformations with similar agreement with the density map exist and a large number of fitting trials are necessary to generate good models. Clustering analysis can be an effective approach to avoid over-fitting models. In addition, we show that an automatic adjustment of the biasing force constants during the fitting process, implemented as replica-exchange scheme, can improve the success rate. © 2017 Wiley Periodicals, Inc.

A guide to the 3D structure of the ryanodine receptor type 1 by cryoEM

Signal transduction by the ryanodine receptor (RyR) is essential in many excitable cells including all striated contractile cells and some types of neurons. While its transmembrane domain is a classic tetrameric, six-transmembrane cation channel, the cytoplasmic domain is uniquely large and complex, hosting a multiplicity of specialized domains. The overall outline and substructure readily recognizable by electron microscopy make RyR a geometrically well-behaved specimen. Hence, for the last two decades, the 3D structural study of the RyR has tracked closely the technological advances in electron microscopy, cryo-electron microscopy (cryoEM), and computerized 3D reconstruction. This review summarizes the progress in the structural determination of RyR by cryoEM and, bearing in mind the leap in resolution provided by the recent implementation of direct electron detection, analyzes the first near-atomic structures of RyR. These reveal a complex orchestration of domains controlling the channel's function, and help to understand how this could break down as a consequence of disease-causing mutations.

Breaking Cryo-EM Resolution Barriers to Facilitate Drug Discovery

Recent advances in single-particle cryoelecton microscopy (cryo-EM) are enabling generation of numerous near-atomic resolution structures for well-ordered protein complexes with sizes ≥ ∼200 kDa. Whether cryo-EM methods are equally useful for high-resolution structural analysis of smaller, dynamic protein complexes such as those involved in cellular metabolism remains an important question. Here, we present 3.8 Å resolution cryo-EM structures of the cancer target isocitrate dehydrogenase (93 kDa) and identify the nature of conformational changes induced by binding of the allosteric small-molecule inhibitor ML309. We also report 2.8-Å- and 1.8-Å-resolution structures of lactate dehydrogenase (145 kDa) and glutamate dehydrogenase (334 kDa), respectively. With these results, two perceived barriers in single-particle cryo-EM are overcome: (1) crossing 2 Å resolution and (2) obtaining structures of proteins with sizes < 100 kDa, demonstrating that cryo-EM can be used to investigate a broad spectrum of drug-target interactions and dynamic conformational states.