High-resolution cryo-EM: the nuts and bolts

Mapping protein conformational landscapes from crystallographic drug fragment screens

Proteins are dynamic macromolecules. Knowledge of a protein's thermally accessible conformations is critical to determining important transitions and designing therapeutics. Accessible conformations are highly constrained by a protein's structure such that concerted structural changes due to external perturbations likely track intrinsic conformational transitions. These transitions can be thought of as paths through a conformational landscape. Crystallographic drug fragment screens are high-throughput perturbation experiments, in which thousands of crystals of a drug target are soaked with small-molecule drug precursors (fragments) and examined for fragment binding, mapping potential drug binding sites on the target protein. Here, we describe an open-source Python package, COLAV (COnformational LAndscape Visualization), to infer conformational landscapes from such large-scale crystallographic perturbation studies. We apply COLAV to drug fragment screens of two medically important systems: protein tyrosine phosphatase 1B (PTP-1B), which regulates insulin signaling, and the SARS CoV-2 Main Protease (MPro). With enough fragment-bound structures, we find that such drug screens also enable detailed mapping of proteins' conformational landscapes.

Field-domain rapid-scan EPR at 240GHz for studies of protein functional dynamics at room temperature

We present field-domain rapid-scan (RS) electron paramagnetic resonance (EPR) at 8.6T and 240GHz. To enable this technique, we upgraded a home-built EPR spectrometer with an FPGA-enabled digitizer and real-time processing software. The software leverages the Hilbert transform to recover the in-phase (I) and quadrature (Q) channels, and therefore the raw absorptive and dispersive signals, χ' and χ'', from their combined magnitude (I2+Q2). Averaging a magnitude is simpler than real-time coherent averaging and has the added benefit of permitting long-timescale signal averaging (up to at least 2.5×106 scans) because it eliminates the effects of source-receiver phase drift. Our rapid-scan (RS) EPR provides a signal-to-noise ratio that is approximately twice that of continuous wave (CW) EPR under the same experimental conditions, after scaling by the square root of acquisition time. We apply our RS EPR as an extension of the recently reported time-resolved Gd-Gd EPR (TiGGER) [Maity et al., 2023], which is able to monitor inter-residue distance changes during the photocycle of a photoresponsive protein through changes in the Gd-Gd dipolar couplings. RS, opposed to CW, returns field-swept spectra as a function of time with 10ms time resolution, and thus, adds a second dimension to the static field transients recorded by TiGGER. We were able to use RS TiGGER to track time-dependent and temperature-dependent kinetics of AsLOV2, a light-activated phototropin domain found in oats. The results presented here combine the benefits of RS EPR with the improved spectral resolution and sensitivity of Gd chelates at high magnetic fields. In the future, field-domain RS EPR at high magnetic fields may enable studies of other real-time kinetic processes with time resolutions that are otherwise difficult to access in the solution state.

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

Graphene Oxide-Supported Microwell Grids for Preparing Cryo-EM Samples with Controlled Ice Thickness

Cryogenic-electron microscopy (cryo-EM) is the preferred method to determine 3D structures of proteins and to study diverse material systems that intrinsically have radiation or air sensitivity. Current cryo-EM sample preparation methods provide limited control over the sample quality, which limits the efficiency and high throughput of 3D structure analysis. This is partly because it is difficult to control the thickness of the vitreous ice that embeds specimens, in the range of nanoscale, depending on the size and type of materials of interest. Thus, there is a need for fine regulation of the thickness of vitreous ice to deliver consistent high signal-to-noise ratios for low-contrast biological specimens. Herein, an advanced silicon-chip-based device is developed which has a regular array of micropatterned holes with a graphene oxide (GO) window on freestanding silicon nitride (Six Ny ). Accurately regulated depths of micropatterned holes enable precise control of vitreous ice thickness. Furthermore, GO window with affinity for biomolecules can facilitate concentration of the sample molecules at a higher level. Incorporation of micropatterned chips with a GO window enhances cryo-EM imaging for various nanoscale biological samples including human immunodeficiency viral particles, groEL tetradecamers, apoferritin octahedral, aldolase homotetramer complexes, and tau filaments, as well as inorganic materials.

An automated iterative approach for protein structure refinement using pseudocontact shifts

NMR structure calculation using NOE-derived distance restraints requires a considerable number of assignments of both backbone and sidechains resonances, often difficult or impossible to get for large or complex proteins. Pseudocontact shifts (PCSs) also play a well-established role in NMR protein structure calculation, usually to augment existing structural, mostly NOE-derived, information. Existing refinement protocols using PCSs usually either require a sizeable number of sidechain assignments or are complemented by other experimental restraints. Here, we present an automated iterative procedure to perform backbone protein structure refinements requiring only a limited amount of backbone amide PCSs. Already known structural features from a starting homology model, in this case modules of repeat proteins, are framed into a scaffold that is subsequently refined by experimental PCSs. The method produces reliable indicators that can be monitored to judge about the performance. We applied it to a system in which sidechain assignments are hardly possible, designed Armadillo repeat proteins (dArmRPs), and we calculated the solution NMR structure of YM4A, a dArmRP containing four sequence-identical internal modules, obtaining high convergence to a single structure. We suggest that this approach is particularly useful when approximate folds are known from other techniques, such as X-ray crystallography, while avoiding inherent artefacts due to, for instance, crystal packing.

Highly accurate protein structure prediction for the human proteome

Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure1. Here we markedly expand the structural coverage of the proteome by applying the state-of-the-art machine learning method, AlphaFold2, at a scale that covers almost the entire human proteome (98.5% of human proteins). The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence. We introduce several metrics developed by building on the AlphaFold model and use them to interpret the dataset, identifying strong multi-domain predictions as well as regions that are likely to be disordered. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses. We are making our predictions freely available to the community and anticipate that routine large-scale and high-accuracy structure prediction will become an important tool that will allow new questions to be addressed from a structural perspective.

Toward the solution of the protein structure prediction problem

Since Anfinsen demonstrated that the information encoded in a protein's amino acid sequence determines its structure in 1973, solving the protein structure prediction problem has been the Holy Grail of structural biology. The goal of protein structure prediction approaches is to utilize computational modeling to determine the spatial location of every atom in a protein molecule starting from only its amino acid sequence. Depending on whether homologous structures can be found in the Protein Data Bank (PDB), structure prediction methods have been historically categorized as template-based modeling (TBM) or template-free modeling (FM) approaches. Until recently, TBM has been the most reliable approach to predicting protein structures, and in the absence of reliable templates, the modeling accuracy sharply declines. Nevertheless, the results of the most recent community-wide assessment of protein structure prediction experiment (CASP14) have demonstrated that the protein structure prediction problem can be largely solved through the use of end-to-end deep machine learning techniques, where correct folds could be built for nearly all single-domain proteins without using the PDB templates. Critically, the model quality exhibited little correlation with the quality of available template structures, as well as the number of sequence homologs detected for a given target protein. Thus, the implementation of deep-learning techniques has essentially broken through the 50-year-old modeling border between TBM and FM approaches and has made the success of high-resolution structure prediction significantly less dependent on template availability in the PDB library.

Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning

An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there are still substantial fractions of maps determined at intermediate or low resolutions, where extracting structure information is not trivial. Here, we report a new computational method, Emap2sec+, which identifies DNA or RNA as well as the secondary structures of proteins in cryo-EM maps of 5 to 10 Å resolution. Emap2sec+ employs the deep Residual convolutional neural network. Emap2sec+ assigns structural labels with associated probabilities at each voxel in a cryo-EM map, which will help structure modeling in an EM map. Emap2sec+ showed stable and high assignment accuracy for nucleotides in low resolution maps and improved performance for protein secondary structure assignments than its earlier version when tested on simulated and experimental maps.

John PC, Bomble YJ. Advances in integrative structural biology: Towards understanding protein complexes in their cellular context

Microorganisms rely on protein interactions to transmit signals, react to stimuli, and grow. One of the best ways to understand these protein interactions is through structural characterization. However, in the past, structural knowledge was limited to stable, high-affinity complexes that could be crystallized. Recent developments in structural biology have revolutionized how protein interactions are characterized. The combination of multiple techniques, known as integrative structural biology, has provided insight into how large protein complexes interact in their native environment. In this mini-review, we describe the past, present, and potential future of integrative structural biology as a tool for characterizing protein interactions in their cellular context.

Mitigating local over-fitting during single particle reconstruction with SIDESPLITTER

Single particle analysis has become a key structural biology technique. Experimental images are extremely noisy, and during iterative refinement it is possible to stably incorporate noise into the reconstruction. Such "over-fitting" can lead to misinterpretation of the structure and flawed biological results. Several strategies are routinely used to prevent over-fitting, the most common being independent refinement of two sides of a split dataset. In this study, we show that over-fitting remains an issue within regions of low local signal-to-noise, despite independent refinement of half datasets. We propose a modification of the refinement process through the application of a local signal-to-noise filter: SIDESPLITTER. We show that our approach can reduce over-fitting for both idealised and experimental data while maintaining independence between the two sides of a split refinement. SIDESPLITTER refinement leads to improved density, and can also lead to improvement of the final resolution in extreme cases where datasets are prone to severe over-fitting, such as small membrane proteins.

WITHDRAWN: Structural studies of vitrified biological proteins and macromolecules - A review on the microimaging aspects of cryo-electron microscopy

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Structural Insights into RNA Dimerization: Motifs, Interfaces and Functions

In comparison with the pervasive use of protein dimers and multimers in all domains of life, functional RNA oligomers have so far rarely been observed in nature. Their diminished occurrence contrasts starkly with the robust intrinsic potential of RNA to multimerize through long-range base-pairing ("kissing") interactions, self-annealing of palindromic or complementary sequences, and stable tertiary contact motifs, such as the GNRA tetraloop-receptors. To explore the general mechanics of RNA dimerization, we performed a meta-analysis of a collection of exemplary RNA homodimer structures consisting of viral genomic elements, ribozymes, riboswitches, etc., encompassing both functional and fortuitous dimers. Globally, we found that domain-swapped dimers and antiparallel, head-to-tail arrangements are predominant architectural themes. Locally, we observed that the same structural motifs, interfaces and forces that enable tertiary RNA folding also drive their higher-order assemblies. These feature prominently long-range kissing loops, pseudoknots, reciprocal base intercalations and A-minor interactions. We postulate that the scarcity of functional RNA multimers and limited diversity in multimerization motifs may reflect evolutionary constraints imposed by host antiviral immune surveillance and stress sensing. A deepening mechanistic understanding of RNA multimerization is expected to facilitate investigations into RNA and RNP assemblies, condensates, and granules and enable their potential therapeutical targeting.

Parvovirus Capsid-Antibody Complex Structures Reveal Conservation of Antigenic Epitopes Across the Family

The parvoviruses are small nonenveloped single stranded DNA viruses that constitute members that range from apathogenic to pathogenic in humans and animals. The infection with a parvovirus results in the generation of antibodies against the viral capsid by the host immune system to eliminate the virus and to prevent re-infection. For members currently either being developed as delivery vectors for gene therapy applications or as oncolytic biologics for tumor therapy, efforts are aimed at combating the detrimental effects of pre-existing or post-treatment antibodies that can eliminate therapeutic benefits. Therefore, understanding antigenic epitopes of parvoviruses can provide crucial information for the development of vaccination applications and engineering novel capsids able to escape antibody recognition. This review aims to capture the information for the binding regions of ∼30 capsid-antibody complex structures of different parvovirus capsids determined to date by cryo-electron microscopy and three-dimensional image reconstruction. The comparison of all complex structures revealed the conservation of antigenic regions among parvoviruses from different genera despite low sequence identity and indicates that the available data can be used across the family for vaccine development and capsid engineering.

Evolving SAXS versatility: solution X-ray scattering for macromolecular architecture, functional landscapes, and integrative structural biology

Small-angle X-ray scattering (SAXS) has emerged as an enabling integrative technique for comprehensive analyses of macromolecular structures and interactions in solution. Over the past two decades, SAXS has become a mainstay of the structural biologist's toolbox, supplying multiplexed measurements of molecular shape and dynamics that unveil biological function. Here, we discuss evolving SAXS theory, methods, and applications that extend the field of small-angle scattering beyond simple shape characterization. SAXS, coupled with size-exclusion chromatography (SEC-SAXS) and time-resolved (TR-SAXS) methods, is now providing high-resolution insight into macromolecular flexibility and ensembles, delineating biophysical landscapes, and facilitating high-throughput library screening to assess macromolecular properties and to create opportunities for drug discovery. Looking forward, we consider SAXS in the integrative era of hybrid structural biology methods, its potential for illuminating cellular supramolecular and mesoscale structures, and its capacity to complement high-throughput bioinformatics sequencing data. As advances in the field continue, we look forward to proliferating uses of SAXS based upon its abilities to robustly produce mechanistic insights for biology and medicine.

Cryo-EM structure of Neurospora crassa respiratory complex IV

In fungi, the mitochondrial respiratory chain complexes (complexes I-IV) are responsible for oxidative phosphorylation, as in higher eukaryotes. Cryo-EM was used to identify a 200 kDa membrane protein from Neurospora crassa in lipid nanodiscs as cytochrome c oxidase (complex IV) and its structure was determined at 5.5 Å resolution. The map closely resembles the cryo-EM structure of complex IV from Saccharomyces cerevisiae. Its ten subunits are conserved in S. cerevisiae and Bos taurus, but other transmembrane subunits are missing. The different structure of the Cox5a subunit is typical for fungal complex IV and may affect the interaction with complex III in a respiratory supercomplex. Additional density was found between the matrix domains of the Cox4 and Cox5a subunits that appears to be specific to N. crassa.

ETDB-Caltech: A blockchain-based distributed public database for electron tomography

Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets.

Frontiers in Cryo Electron Microscopy of Complex Macromolecular Assemblies

In recent years, cryo electron microscopy (cryo-EM) technology has been transformed with the development of better instrumentation, direct electron detectors, improved methods for specimen preparation, and improved software for data analysis. Analyses using single-particle cryo-EM methods have enabled determination of structures of proteins with sizes smaller than 100 kDa and resolutions of ∼2 Å in some cases. The use of electron tomography combined with subvolume averaging is beginning to allow the visualization of macromolecular complexes in their native environment in unprecedented detail. As a result of these advances, solutions to many intractable challenges in structural and cell biology, such as analysis of highly dynamic soluble and membrane-embedded protein complexes or partially ordered protein aggregates, are now within reach. Recent reports of structural studies of G protein-coupled receptors, spliceosomes, and fibrillar specimens illustrate the progress that has been made using cryo-EM methods, and are the main focus of this review.

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.

Recent innovations in membrane-protein structural biology

Innovations are expanding the capabilities of experimental investigations of the structural properties of membrane proteins. Traditionally, three-dimensional structures have been determined by measuring x-ray diffraction using protein crystals with a size of least 100 μm. For membrane proteins, achieving crystals suitable for these measurements has been a significant challenge. The availabilities of micro-focus x-ray beams and the new instrumentation of x-ray free-electron lasers have opened up the possibility of using submicrometer-sized crystals. In addition, advances in cryo-electron microscopy have expanded the use of this technique for studies of protein crystals as well as studies of individual proteins as single particles. Together, these approaches provide unprecedented opportunities for the exploration of structural properties of membrane proteins, including dynamical changes during protein function.

Single-Particle cryo-EM as a Pipeline for Obtaining Atomic Resolution Structures of Druggable Targets in Preclinical Structure-Based Drug Design

Single-particle cryo-electron microscopy (cryo-EM) and three-dimensional (3D) image processing have gained importance in the last few years to obtain atomic structures of drug targets. Obtaining atomic-resolution 3D structure better than ~2.5 Å is a standard approach in pharma companies to design and optimize therapeutic compounds against drug targets like proteins. Protein crystallography is the main technique in solving the structures of drug targets at atomic resolution. However, this technique requires protein crystals which in turn is a major bottleneck. It was not possible to obtain the structure of proteins better than 2.5 Å resolution by any other methods apart from protein crystallography until 2015. Recent advances in single-particle cryo-EM and 3D image processing have led to a resolution revolution in the field of structural biology that has led to high-resolution protein structures, thus breaking the cryo-EM resolution barriers to facilitate drug discovery. There are 24 structures solved by single-particle cryo-EM with resolution 2.5 Å or better in the EMDataBank (EMDB) till date. Among these, five cryo-EM 3D reconstructions of proteins in the EMDB have their associated coordinates deposited in Protein Data Bank (PDB), with bound inhibitor/ ligand. Thus, for the first time, single-particle cryo-EM was included in the structure-based drug design (SBDD) pipeline for solving protein structures independently or where crystallography has failed to crystallize the protein. Further, this technique can be complementary and supplementary to protein crystallography field in solving 3D structures. Thus, single-particle cryo-EM can become a standard approach in pharmaceutical industry in the design, validation, and optimization of therapeutic compounds targeting therapeutically important protein molecules during preclinical drug discovery research. The present chapter will describe briefly the history and the principles of single-particle cryo-EM and 3D image processing to obtain atomic-resolution structure of proteins and their complex with their drug targets/ligands.

Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

Sub-2 Å Ewald curvature corrected structure of an AAV2 capsid variant

Single-particle cryogenic electron microscopy (cryo-EM) provides a powerful methodology for structural biologists, but the resolutions typically attained with experimentally determined structures have lagged behind microscope capabilities. Here, we exploit several technical advances to improve resolution, including per-particle contrast transfer function (CTF) refinement and correction for Ewald sphere curvature. The latter is demonstrated with several experimental samples and should become more standard as resolutions increase or at lower microscope accelerating voltages. The combined application of the described methods to micrographs recorded on a Titan Krios enables structure determination at ~1.86-Å resolution of an adeno-associated virus serotype 2 variant (AAV2), an important gene-delivery vehicle. The resulting structural details provide an improved model for understanding the biology of AAV that will guide future vector development for gene therapy.

Single-particle cryo-EM is a powerful method for macromolecular structure determination. Here the authors demonstrate that Ewald sphere curvature correction, sub-Angstrom pixilation and per-particle CTF refinement can improve map quality and resolution and present the 1.86 Å cryo-EM structure of an adeno-associated virus serotype 2 variant.

Characterization of Glycoproteins with the Immunoglobulin Fold by X-Ray Crystallography and Biophysical Techniques

Glycoproteins on the surface of cells play critical roles in cellular function, including signalling, adhesion and transport. On leukocytes, several of these glycoproteins possess immunoglobulin (Ig) folds and are central to immune recognition and regulation. Here, we present a platform for the design, expression and biophysical characterization of the extracellular domain of human B cell receptor CD22. We propose that these approaches are broadly applicable to the characterization of mammalian glycoprotein ectodomains containing Ig domains. Two suspension human embryonic kidney (HEK) cell lines, HEK293F and HEK293S, are used to express glycoproteins harbouring complex and high-mannose glycans, respectively. These recombinant glycoproteins with different glycoforms allow investigating the effect of glycan size and composition on ligand binding. We discuss protocols for studying the kinetics and thermodynamics of glycoprotein binding to biologically relevant ligands and therapeutic antibody candidates. Recombinant glycoproteins produced in HEK293S cells are amenable to crystallization due to glycan homogeneity, reduced flexibility and susceptibility to endoglycosidase H treatment. We present methods for soaking glycoprotein crystals with heavy atoms and small molecules for phase determination and analysis of ligand binding, respectively. The experimental protocols discussed here hold promise for the characterization of mammalian glycoproteins to give insight into their function and investigate the mechanism of action of therapeutics.

Monomeric Intermediates Formed by Vesiculovirus Glycoprotein during Its Low-pH-induced Structural Transition

•Vesiculovirus G is the prototype of class III viral fusion glycoproteins. •The structures of both G pre- and post-fusion conformation have been determined. •The structure of monomeric intermediates reveals the pathway of the transition. •A fusion-loop-exposing antiparallel dimer may initiate the fusion process. •Those data challenge the current model proposed for viral membrane fusion.

CryoEM-based hybrid modeling approaches for structure determination

Recent advances in cryo-electron microscopy (cryoEM) have dramatically improved the resolutions at which vitrified biological specimens can be studied, revealing new structural and mechanistic insights over a broad range of spatial scales. Bolstered by these advances, much effort has been directed toward the development of hybrid modeling methodologies for the construction and refinement of high-fidelity atomistic models from cryoEM data. In this brief review, we will survey the key elements of cryoEM-based hybrid modeling, providing an overview of available computational tools and strategies as well as several recent applications.

Microbial expression systems for membrane proteins

Despite many high-profile successes, recombinant membrane protein production remains a technical challenge; it is still the case that many fewer membrane protein structures have been published than those of soluble proteins. However, progress is being made because empirical methods have been developed to produce the required quantity and quality of these challenging targets. This review focuses on the microbial expression systems that are a key source of recombinant prokaryotic and eukaryotic membrane proteins for structural studies. We provide an overview of the host strains, tags and promoters that, in our experience, are most likely to yield protein suitable for structural and functional characterization. We also catalogue the detergents used for solubilization and crystallization studies of these proteins. Here, we emphasize a combination of practical methods, not necessarily high-throughput, which can be implemented in any laboratory equipped for recombinant DNA technology and microbial cell culture.

Affinity maturation of a portable Fab-RNA module for chaperone-assisted RNA crystallography

Antibody fragments such as Fabs possess properties that can enhance protein and RNA crystallization and therefore can facilitate macromolecular structure determination. In particular, Fab BL3-6 binds to an AAACA RNA pentaloop closed by a GC pair with ∼100 nM affinity. The Fab and hairpin have served as a portable module for RNA crystallization. The potential for general application make it desirable to adjust the properties of this crystallization module in a manner that facilitates its use for RNA structure determination, such as ease of purification, surface entropy or binding affinity. In this work, we used both in vitro RNA selection and phage display selection to alter the epitope and paratope sides of the binding interface, respectively, for improved binding affinity. We identified a 5'-GNGACCC-3' consensus motif in the RNA and S97N mutation in complimentarity determining region L3 of the Fab that independently impart about an order of magnitude improvement in affinity, resulting from new hydrogen bonding interactions. Using a model RNA, these modifications facilitated crystallization under a wider range of conditions and improved diffraction. The improved features of the Fab-RNA module may facilitate its use as an affinity tag for RNA purification and imaging and as a chaperone for RNA crystallography.

Dawning of a new era in TRP channel structural biology by cryo-electron microscopy

Cryo-electron microscopy (cryo-EM) permits the determination of atomic protein structures by averaging large numbers of individual projection images recorded at cryogenic temperatures-a method termed single-particle analysis. The cryo-preservation traps proteins within a thin glass-like ice layer, making literally a freeze image of proteins in solution. Projections of randomly adopted orientations are merged to reconstruct a 3D density map. While atomic resolution for highly symmetric viruses was achieved already in 2009, the development of new sensitive and fast electron detectors has enabled cryo-EM for smaller and asymmetrical proteins including fragile membrane proteins. As one of the most important structural biology methods at present, cryo-EM was awarded in October 2017 with the Nobel Prize in Chemistry. The molecular understanding of Transient-Receptor-Potential (TRP) channels has been boosted tremendously by cryo-EM single-particle analysis. Several near-atomic and atomic structures gave important mechanistic insights, e.g., into ion permeation and selectivity, gating, as well as into the activation of this enigmatic and medically important membrane protein family by various chemical and physical stimuli. Lastly, these structures have set the starting point for the rational design of TRP channel-targeted therapeutics to counteract life-threatening channelopathies. Here, we attempt a brief introduction to the method, review the latest advances in cryo-EM structure determination of TRP channels, and discuss molecular insights into the channel function based on the wealth of TRP channel cryo-EM structures.

Modeling the assembly order of multimeric heteroprotein complexes

Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes.

AIPL1: A specialized chaperone for the phototransduction effector

Molecular chaperones play pivotal roles in protein folding, quality control, assembly of multimeric protein complexes, protein trafficking, stress responses, and other essential cellular processes. Retinal photoreceptor rod and cone cells have an unusually high demand for production, quality control, and trafficking of key phototransduction components, and thus, require a robust and specialized chaperone machinery to ensure the fidelity of sensing and transmission of visual signals. Misfolding and/or mistrafficking of photoreceptor proteins are known causes for debilitating blinding diseases. Phosphodiesterase 6, the effector enzyme of the phototransduction cascade, relies on a unique chaperone aryl hydrocarbon receptor (AhR)-interacting protein-like 1 (AIPL1) for its stability and function. The structure of AIPL1 and its relationship with the client remained obscure until recently. This review summarizes important recent advances in understanding the mechanisms underlying normal function of AIPL1 and the protein perturbations caused by pathogenic mutations.

Novel mechanisms and functions of complement

Progress at the beginning of the 21st century transformed the perception of complement from that of a blood-based antimicrobial system to that of a global regulator of immunity and tissue homeostasis. More recent years have witnessed remarkable advances in structure-function insights and understanding of the mechanisms and locations of complement activation, which have added new layers of complexity to the biology of complement. This complexity is readily reflected by the multifaceted and contextual involvement of complement-driven networks in a wide range of inflammatory and neurodegenerative disorders and cancer. This Review provides an updated view of new and previously unanticipated functions of complement and how these affect immunity and disease pathogenesis.

How Ribosomes Translate Cancer

A wealth of novel findings, including congenital ribosomal mutations in ribosomopathies and somatic ribosomal mutations in various cancers, have significantly increased our understanding of the relevance of ribosomes in oncogenesis. Here, we explore the growing list of mechanisms by which the ribosome is involved in carcinogenesis-from the hijacking of ribosomes by oncogenic factors and dysregulated translational control, to the effects of mutations in ribosomal components on cellular metabolism. Of clinical importance, the recent success of RNA polymerase inhibitors highlights the dependence on "onco-ribosomes" as an Achilles' heel of cancer cells and a promising target for further therapeutic intervention.Significance: The recent discovery of somatic mutations in ribosomal proteins in several cancers has strengthened the link between ribosome defects and cancer progression, while also raising the question of which cellular mechanisms such defects exploit. Here, we discuss the emerging molecular mechanisms by which ribosomes support oncogenesis, and how this understanding is driving the design of novel therapeutic strategies. Cancer Discov; 7(10); 1069-87. ©2017 AACR.

Nuclear Lamins: Thin Filaments with Major Functions

The nuclear lamina is a nuclear peripheral meshwork that is mainly composed of nuclear lamins, although a small fraction of lamins also localizes throughout the nucleoplasm. Lamins are classified as type V intermediate filament (IF) proteins. Mutations in lamin genes cause at least 15 distinct human diseases, collectively termed laminopathies, including muscle, metabolic, and neuronal diseases, and can cause accelerated aging. Most of these mutations are in the LMNA gene encoding A-type lamins. A growing number of nuclear proteins are known to bind lamins and are implicated in both nuclear and cytoskeletal organization, mechanical stability, chromatin organization, signaling, gene regulation, genome stability, and cell differentiation. Recent studies reveal the organization of the lamin filament meshwork in somatic cells where they assemble as tetramers in cross-section of the filaments.

Single-particle cryo-EM-Improved ab initio 3D reconstruction with SIMPLE/PRIME

Cryogenic electron microscopy (cryo-EM) and single-particle analysis now enables the determination of high-resolution structures of macromolecular assemblies that have resisted X-ray crystallography and other approaches. We developed the SIMPLE open-source image-processing suite for analysing cryo-EM images of single-particles. A core component of SIMPLE is the probabilistic PRIME algorithm for identifying clusters of images in 2D and determine relative orientations of single-particle projections in 3D. Here, we extend our previous work on PRIME and introduce new stochastic optimization algorithms that improve the robustness of the approach. Our refined method for identification of homogeneous subsets of images in accurate register substantially improves the resolution of the cluster centers and of the ab initio 3D reconstructions derived from them. We now obtain maps with a resolution better than 10 Å by exclusively processing cluster centers. Excellent parallel code performance on over-the-counter laptops and CPU workstations is demonstrated.

Best practices for managing large CryoEM facilities

This paper provides an overview of the discussion and presentations from the Workshop on the Management of Large CryoEM Facilities held at the New York Structural Biology Center, New York, NY on February 6-7, 2017. A major objective of the workshop was to discuss best practices for managing cryoEM facilities. The discussions were largely focused on supporting single-particle methods for cryoEM and topics included: user access, assessing projects, workflow, sample handling, microscopy, data management and processing, and user training.