Bridging structural and cell biology with cryo-electron microscopy.

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

RNA: The Unsuspected Conductor in the Orchestra of Macromolecular Crowding.

This comprehensive Review delves into the chemical principles governing RNA-mediated crowding events, commonly referred to as granules or biological condensates. We explore the pivotal role played by RNA sequence, structure, and chemical modifications in these processes, uncovering their correlation with crowding phenomena under physiological conditions. Additionally, we investigate instances where crowding deviates from its intended function, leading to pathological consequences. By deepening our understanding of the delicate balance that governs molecular crowding driven by RNA and its implications for cellular homeostasis, we aim to shed light on this intriguing area of research. Our exploration extends to the methodologies employed to decipher the composition and structural intricacies of RNA granules, offering a comprehensive overview of the techniques used to characterize them, including relevant computational approaches. Through two detailed examples highlighting the significance of noncoding RNAs, NEAT1 and XIST, in the formation of phase-separated assemblies and their influence on the cellular landscape, we emphasize their crucial role in cellular organization and function. By elucidating the chemical underpinnings of RNA-mediated molecular crowding, investigating the role of modifications, structures, and composition of RNA granules, and exploring both physiological and aberrant phase separation phenomena, this Review provides a multifaceted understanding of the intriguing world of RNA-mediated biological condensates.

Determining Macromolecular Structures Using Cryo-Electron Microscopy.

Structural insights into macromolecular and protein complexes provide key clues about the molecular basis of the function. Cryogenic electron microscopy (cryo-EM) has emerged as a powerful structural biology method for studying protein and macromolecular structures at high resolution in both native and near-native states. Despite the ability to get detailed structural insights into the processes underlying protein function using cryo-EM, there has been hesitancy amongst plant biologists to apply the method for biomolecular interaction studies. This is largely evident from the relatively fewer structural depositions of proteins and protein complexes from plant origin in electron microscopy databank. Even though the progress has been slow, cryo-EM has significantly contributed to our understanding of the molecular biology processes underlying photosynthesis, energy transfer in plants, besides viruses infecting plants. This chapter introduces sample preparation for both negative-staining electron microscopy (NSEM) and cryo-EM for plant proteins and macromolecular complexes and data analysis using single particle analysis for beginners.

High-resolution cryo-EM of the human CDK-activating kinase for structure-based drug design.

Rational design of next-generation therapeutics can be facilitated by high-resolution structures of drug targets bound to small-molecule inhibitors. However, application of structure-based methods to macromolecules refractory to crystallization has been hampered by the often-limiting resolution and throughput of cryogenic electron microscopy (cryo-EM). Here, we use high-resolution cryo-EM to determine structures of the CDK-activating kinase, a master regulator of cell growth and division, in its free and nucleotide-bound states and in complex with 15 inhibitors at up to 1.8 Å resolution. Our structures provide detailed insight into inhibitor interactions and networks of water molecules in the active site of cyclin-dependent kinase 7 and provide insights into the mechanisms contributing to inhibitor selectivity, thereby providing the basis for rational design of next-generation therapeutics. These results establish a methodological framework for the use of high-resolution cryo-EM in structure-based drug design.

The Complementarity of Nuclear Magnetic Resonance and Native Mass Spectrometry in Probing Protein-Protein Interactions.

Nuclear magnetic resonance (NMR) and native mass spectrometry (MS) are mature physicochemical techniques with long histories and important applications. NMR spectroscopy provides detailed information about the structure, dynamics, interactions, and chemical environment of biomolecules. MS is an effective approach for determining the mass of biomolecules with high accuracy, sensitivity, and speed. The two techniques offer unique advantages and provide solid tools for structural biology. In the present review, we discuss their individual merits in the context of their applications to structural studies in biology with specific focus on protein interactions and evaluate their limitations. We provide specific examples in which these techniques can complement each other, providing new information on the same scientific case. We discuss how the field may develop and what challenges are expected in the future. Overall, the combination of NMR and MS plays an increasingly important role in integrative structural biology, assisting scientists in deciphering the three-dimensional structure of composite macromolecular assemblies.

X-Ray Crystallography for Macromolecular Complexes.

X-ray crystallography has for most of the last century been the standard technique to determine the high-resolution structure of biological macromolecules, including multi-subunit protein-protein and protein-nucleic acids as large as the ribosome and viruses. As such, the successful application of X-ray crystallography to many biological problems revolutionized biology and biomedicine by solving the structures of small molecules and vitamins, peptides and proteins, DNA and RNA molecules, and many complexes-affording a detailed knowledge of the structures that clarified biological and chemical mechanisms, conformational changes, interactions, catalysis and the biological processes underlying DNA replication, translation, and protein synthesis. Now reaching well into the first quarter of the twenty-first century, X-ray crystallography shares the structural biology stage with cryo-electron microscopy and other innovative structure determination methods, as relevant and central to our understanding of biological function and structure as ever. In this chapter, we provide an overview of modern X-ray crystallography and how it interfaces with other mainstream structural biology techniques, with an emphasis on macromolecular complexes.

Small-Angle X-Ray Scattering for Macromolecular Complexes.

Small angle X-ray scattering (SAXS) is a versatile technique that can provide unique insights in the solution structure of macromolecules and their complexes, covering the size range from small peptides to complete viral assemblies. Technological and conceptual advances in the last two decades have tremendously improved the accessibility of the technique and transformed it into an indispensable tool for structural biology. In this chapter we introduce and discuss several approaches to collecting SAXS data on macromolecular complexes, including several approaches to online chromatography. We include practical advice on experimental design and point out common pitfalls of the technique.

Characterization of Complexes and Supramolecular Structures by Electron Microscopy.

Recent advancements in cryo-electron microscopy (cryo-TEM) have enabled the determination of structures of macromolecular complexes at near-atomic resolution, establishing it as a pivotal tool in Structural Biology. This high resolution allows for the detection of ligands and substrates under physiological conditions. Enhancements in detectors and imaging devices, like phase plates, improve signal quality, facilitating the reconstruction of even smaller macromolecular complexes. The 100-kDa barrier has been surpassed, presenting new opportunities for pharmacological research and expanding the scope of crystallographic analyses in the pharmaceutical industry. Cryo-TEM produces vast data sets from minimal samples, and refined classification methods can identify different conformational states of macromolecular complexes, offering deeper insights into the functional characteristics of macromolecular systems. Additionally, cryo-TEM is paving the way for time-resolved microscopy, with rapid freezing techniques capturing snapshots of vital structural changes in biological complexes. Finally, in Structural Cell Biology, advanced cryo-TEM, through tomographic procedures, is revealing conformational changes related to the specific subcellular localization of macromolecular systems and their interactions within cells.

Accounting for nonuniformity of bulk-solvent: A mosaic model.

A flat mask-based model is almost universally used in macromolecular crystallography to account for disordered (bulk) solvent. This model assumes any voxel of the crystal unit cell that is not occupied by the atomic model is occupied by the solvent. The properties of this solvent are assumed to be exactly the same across the whole volume of the unit cell. While this is a reasonable approximation in practice, there are a number of scenarios where this model becomes suboptimal. In this work, we enumerate several of these scenarios and describe a new generalized approach to modeling the bulk-solvent which we refer to as mosaic bulk-solvent model. The mosaic bulk-solvent model allows nonuniform features of the solvent in the crystal to be accounted for in a computationally efficient way. It is implemented in the computational crystallography toolbox and the Phenix software.

Exploring advances in single particle CryoEM with apoferritin: From blobs to true atomic resolution.

Deciphering the three-dimensional structures of macromolecules is of paramount importance for gaining insights into their functions and roles in human health and disease. Single particle cryoEM has emerged as a powerful technique that enables direct visualization of macromolecules and their complexes, and through subsequent averaging, achieve near atomic-level resolution. A major breakthrough was recently achieved with the determination of the apoferritin structure at true atomic resolution. In this review, we discuss the latest technological innovations across the entire single-particle workflow, which have been instrumental in driving the resolution revolution and in transforming cryoEM as a mainstream technique in structural biology. We illustrate these advancements using apoferritin as an example that has served as an excellent benchmark sample for assessing emerging technologies. We further explore whether the existing technology can routinely generate atomic structures of dynamic macromolecules that more accurately represent real-world samples, the limitations in the workflow, and the current approaches employed to overcome them.

Advanced exploitation of unmerged reflection data during processing and refinement with autoPROC and BUSTER.

The validation of structural models obtained by macromolecular X-ray crystallography against experimental diffraction data, whether before deposition into the PDB or after, is typically carried out exclusively against the merged data that are eventually archived along with the atomic coordinates. It is shown here that the availability of unmerged reflection data enables valuable additional analyses to be performed that yield improvements in the final models, and tools are presented to implement them, together with examples of the results to which they give access. The first example is the automatic identification and removal of image ranges affected by loss of crystal centering or by excessive decay of the diffraction pattern as a result of radiation damage. The second example is the `reflection-auditing' process, whereby individual merged data items showing especially poor agreement with model predictions during refinement are investigated thanks to the specific metadata (such as image number and detector position) that are available for the corresponding unmerged data, potentially revealing previously undiagnosed instrumental, experimental or processing problems. The third example is the calculation of so-called F(early) - F(late) maps from carefully selected subsets of unmerged amplitude data, which can not only highlight the location and extent of radiation damage but can also provide guidance towards suitable fine-grained parametrizations to model the localized effects of such damage.

The effects of biological crowders on fibrillization, structure, diffusion, and conformational dynamics of α-synuclein.

α-synuclein is an intrinsically disordered protein (IDP) whose aggregation in presynaptic neuronal cells is a pathological hallmark of Lewy body formation and Parkinson's disease. This aggregation process is likely affected by the crowded macromolecular cellular environment. In this study, α-synuclein was studied in the presence of both a synthetic crowder, Ficoll70, and a biological crowder composed of lysed cells that better mimics the biocomplexity of the cellular environment. 15 N-1 H HSQC NMR results show similar α-synuclein chemical shifts in non-crowded and all crowded conditions implying that it remains similarly unstructured in all conditions. Nevertheless, both HSQC NMR and fluorescence measurements indicate that, only in the cell lysate, α-synuclein forms aggregates over a timescale of 48 h. 15 N-edited diffusion measurements indicate that all crowders slow down the α-synuclein's diffusivity. Interestingly, at high concentrations, α-synuclein diffuses faster in cell lysate than in Ficoll70, possibly due to additional soft (e.g., electrostatic or hydrophobic) interactions. 15 N-edited relaxation measurements show that some residues are more mobile in cell lysate than in Ficoll70; the rates that are most different are predominantly in hydrophobic residues. We thus examined cell lysates with reduced hydrophobicity and found slower dynamics (higher relaxation rates) in several α-synuclein residues. Taken together, these experiments suggest that while cell lysate does not substantially affect α-synuclein structure (HSQC spectra), it does affect chain dynamics and translational diffusion, and strongly affects aggregation over a timescale of days, in a manner that is different from either no crowder or an artificial crowder: soft hydrophobic interactions are implicated.

Optimizing representations for integrative structural modeling using Bayesian model selection.

MOTIVATION: Integrative structural modeling combines data from experiments, physical principles, statistics of previous structures, and prior models to obtain structures of macromolecular assemblies that are challenging to characterize experimentally. The choice of model representation is a key decision in integrative modeling, as it dictates the accuracy of scoring, efficiency of sampling, and resolution of analysis. But currently, the choice is usually made ad hoc, manually. RESULTS: Here, we report NestOR (Nested Sampling for Optimizing Representation), a fully automated, statistically rigorous method based on Bayesian model selection to identify the optimal coarse-grained representation for a given integrative modeling setup. Given an integrative modeling setup, it determines the optimal representations from given candidate representations based on their model evidence and sampling efficiency. The performance of NestOR was evaluated on a benchmark of four macromolecular assemblies. AVAILABILITY AND IMPLEMENTATION: NestOR is implemented in the Integrative Modeling Platform (https://integrativemodeling.org) and is available at https://github.com/isblab/nestor. Data for the benchmark is at https://www.doi.org/10.5281/zenodo.10360718.

Understanding the cell: Future views of structural biology.

Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.

Structural highlights of macromolecular complexes and assemblies.

The structures of macromolecular assemblies have given us deep insights into cellular processes and have profoundly impacted biological research and drug discovery. We highlight the structures of macromolecular assemblies that have been modeled using integrative and computational methods and describe how open access to these structures from structural archives has empowered the research community. The arsenal of experimental and computational methods for structure determination ensures a future where whole organelles and cells can be modeled.

MaDDOSY (Mass Determination Diffusion Ordered Spectroscopy) using an 80 MHz Bench Top NMR for the Rapid Determination of Polymer and Macromolecular Molecular Weight.

Measurement of molecular weight is an integral part of macromolecular and polymer characterization which usually has limitations. Herein, this article presents the use of a bench-top 80 MHz Nuclear Magnetic Resonance (NMR) spectrometer for diffusion-ordered spectroscopy as a practical and rapid approach for the determination of molecular weight/size using a novel solvent and polymer-independent universal calibration.

Predictive modeling and cryo-EM: A synergistic approach to modeling macromolecular structure.

Over the last 15 years, structural biology has seen unprecedented development and improvement in two areas: electron cryo-microscopy (cryo-EM) and predictive modeling. Once relegated to low resolutions, single-particle cryo-EM is now capable of achieving near-atomic resolutions of a wide variety of macromolecular complexes. Ushered in by AlphaFold, machine learning has powered the current generation of predictive modeling tools, which can accurately and reliably predict models for proteins and some complexes directly from the sequence alone. Although they offer new opportunities individually, there is an inherent synergy between these techniques, allowing for the construction of large, complex macromolecular models. Here, we give a brief overview of these approaches in addition to illustrating works that combine these techniques for model building. These examples provide insight into model building, assessment, and limitations when integrating predictive modeling with cryo-EM density maps. Together, these approaches offer the potential to greatly accelerate the generation of macromolecular structural insights, particularly when coupled with experimental data.

Assembly Requirements for the Construction of Large-Scale Binary Protein Structures.

The precise assembly of multiple biomacromolecules into well-defined structures and materials is of great importance for various biomedical and nanobiotechnological applications. In this study, we investigate the assembly requirements for two-component materials using charged protein nanocages as building blocks. To achieve this, we designed several variants of ferritin nanocages to determine the surface characteristics necessary for the formation of large-scale binary three-dimensional (3D) assemblies. These nanocage variants were employed in protein crystallization experiments and macromolecular crystallography analyses, complemented by computational methods. Through the screening of nanocage variant combinations at various ionic strengths, we identified three essential features for successful assembly: (1) the presence of a favored crystal contact region, (2) the presence of a charged patch not involved in crystal contacts, and (3) sufficient distinctiveness between the nanocages. Surprisingly, the absence of noncrystal contact mediating patches had a detrimental effect on the assemblies, highlighting their unexpected importance. Intriguingly, we observed the formation of not only binary structures but also both negatively and positively charged unitary structures under previously exclusively binary conditions. Overall, our findings will inform future design strategies by providing some design rules, showcasing the utility of supercharging symmetric building blocks in facilitating the assembly of biomacromolecules into large-scale binary 3D assemblies.

Effects of Ionic Strength on the Morphology, Scattering, and Mechanical Response of Neurofilament-Derived Protein Brushes.

Protein brushes not only play a key role in the functionality of neurofilaments but also have wide applications in biomedical materials. Here, we investigate the effect of ionic strength on the morphology of protein brushes using continuous-space self-consistent field theory. A coarse-grained multiblock charged macromolecular model is developed to capture the chemical identity of amino acid sequences. For neurofilament heavy (NFH) brushes at pH 2.4, we predict three morphological regimes: swollen brushes, condensed brushes, and coexisting brushes, which consist of both a dense inner layer and a diffuse outer layer. The brush height predicted by our theory is in good agreement with the experimental data for a wide range of ionic strengths. The dramatic height decrease is a result of the electrostatic screening-induced transition from the overlapping state to the isolated state of the coexisting brushes. We also studied the evolution of the scattering and mechanical responses accompanying the morphological change. The oscillation in the reflectivity spectra characterizes the existence and microstructure of the inner condensed layer, whereas the shoulder in the force spectra signifies a swollen morphology.