Structural Analysis of Protein Complexes by Cryo Electron Microscopy

Comparative Analysis of Symmetry Parameters in the E2 Inner Core of the Pyruvate Dehydrogenase Complex

Recent advances in cryo-electron microscopy (cryo-EM) have facilitated the high-resolution structural determination of macromolecular complexes in their native states, providing valuable insights into their dynamic behaviors. However, insufficient understanding or experience with the cryo-EM image processing parameters can result in the loss of biological meaning. In this paper, we investigate the dihydrolipoyl acetyltransferase (E2) inner core complex of the pyruvate dehydrogenase complex (PDC) and reconstruct the 3D maps using five different symmetry parameters. The results demonstrate that the reconstructions yield structurally identical 3D models even at a near-atomic structure. This finding underscores a crucial message for researchers engaging in single-particle analysis (SPA) with relatively user-friendly and convenient image processing software. This approach helps reduce the risk of missing critical biological details, such as the dynamic properties of macromolecules.

Plastocyanin and Cytochrome f Complex Structures Obtained by NMR, Molecular Dynamics, and AlphaFold 3 Methods Compared to Cryo-EM Data

Plastocyanin is a small mobile protein that facilitates electron transfer through the formation of short-lived protein-protein complexes with cytochrome bf and photosystem 1. Due to the transient nature of plastocyanin-cytochrome f complex, the lack of a long-lived tight complex makes it impossible to determine its structure by X-ray diffraction analysis. Up to today, a number of slightly different structures of such complexes have been obtained by experimental and computer methods. Now, artificial intelligence gives us the possibility to predict the structures of intermolecular complexes. In this study, we compare encounter and final complexes obtained by Brownian and molecular dynamics methods, as well as the structures predicted by AlphaFold 3, with NMR and cryo-EM data. Surprisingly, the best match for the plastocyanin electron density obtained by cryo-EM was demonstrated by an AlphaFold 3 structure. The orientation of plastocyanin in this structure almost completely coincides with its orientation obtained by molecular dynamics calculation, and, at the same time, it is different from the orientation of plastocyanin predicted on the basis of NMR data. This is even more unexpected given that only NMR structures for the plastocyanin-cytochrome f complex are available in the PDB database, which was used to train AlphaFold 3.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

Ferrochelatase: Mapping the Intersection of Iron and Porphyrin Metabolism in the Mitochondria

Porphyrin and iron are ubiquitous and essential for sustaining life in virtually all living organisms. Unlike iron, which exists in many forms, porphyrin macrocycles are mostly functional as metal complexes. The iron-containing porphyrin, heme, serves as a prosthetic group in a wide array of metabolic pathways; including respiratory cytochromes, hemoglobin, cytochrome P450s, catalases, and other hemoproteins. Despite playing crucial roles in many biological processes, heme, iron, and porphyrin intermediates are potentially cytotoxic. Thus, the intersection of porphyrin and iron metabolism at heme synthesis, and intracellular trafficking of heme and its porphyrin precursors are tightly regulated processes. In this review, we discuss recent advances in understanding the physiological dynamics of eukaryotic ferrochelatase, a mitochondrially localized metalloenzyme. Ferrochelatase catalyzes the terminal step of heme biosynthesis, the insertion of ferrous iron into protoporphyrin IX to produce heme. In most eukaryotes, except plants, ferrochelatase is localized to the mitochondrial matrix, where substrates are delivered and heme is synthesized for trafficking to multiple cellular locales. Herein, we delve into the structural and functional features of ferrochelatase, as well as its metabolic regulation in the mitochondria. We discuss the regulation of ferrochelatase via post-translational modifications, transportation of substrates and product across the mitochondrial membrane, protein-protein interactions, inhibition by small-molecule inhibitors, and ferrochelatase in protozoal parasites. Overall, this review presents insight on mitochondrial heme homeostasis from the perspective of ferrochelatase.

Using cryo-EM to uncover mechanisms of bacterial transcriptional regulation

Transcription is the principal control point for bacterial gene expression, and it enables a global cellular response to an intracellular or environmental trigger. Transcriptional regulation is orchestrated by transcription factors, which activate or repress transcription of target genes by modulating the activity of RNA polymerase. Dissecting the nature and precise choreography of these interactions is essential for developing a molecular understanding of transcriptional regulation. While the contribution of X-ray crystallography has been invaluable, the 'resolution revolution' of cryo-electron microscopy has transformed our structural investigations, enabling large, dynamic and often transient transcription complexes to be resolved that in many cases had resisted crystallisation. In this review, we highlight the impact cryo-electron microscopy has had in gaining a deeper understanding of transcriptional regulation in bacteria. We also provide readers working within the field with an overview of the recent innovations available for cryo-electron microscopy sample preparation and image reconstruction of transcription complexes.

Conquer by cryo-EM without physically dividing

This mini-review provides an update regarding the substantial progress that has been made in using single-particle cryo-EM to obtain high-resolution structures for proteins and other macromolecules whose particle sizes are smaller than 100 kDa. We point out that establishing the limits of what can be accomplished, both in terms of particle size and attainable resolution, serves as a guide for what might be expected when attempting to improve the resolution of small flexible portions of a larger structure using focused refinement approaches. These approaches, which involve computationally ignoring all but a specific, targeted region of interest on the macromolecules, is known as 'masking and refining,' and it thus is the computational equivalent of the 'divide and conquer' approach that has been used so successfully in X-ray crystallography. The benefit of masked refinement, however, is that one is able to determine structures in their native architectural context, without physically separating them from the biological connections that they require for their function. This mini-review also compares where experimental achievements currently stand relative to various theoretical estimates for the smallest particle size that can be successfully reconstructed to high resolution. Since it is clear that a substantial gap still remains between the two, we briefly recap the areas in which further improvement seems possible, both in equipment and in methods.

Protein Structure Prediction with Mass Spectrometry Data

Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such methods are frequently limited by experimental challenges such as sample quantity, target size, and efficiency. Structural mass spectrometry (MS) is a technique in which structural features of proteins are elucidated quickly and relatively easily. Computational techniques that convert sparse MS data into protein models that demonstrate agreement with the data are needed. This review features cutting-edge computational methods that predict protein structure from MS data such as chemical cross-linking, hydrogen-deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation. Additionally, we address future directions for protein structure prediction with sparse MS data. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Identification of Mg2+ ions next to nucleotides in cryo-EM maps using electrostatic potential maps

Cryo electron microscopy (cryo-EM) can produce maps of macromolecules that have resolutions that are sufficiently high that structural details such as chemical modifications, water molecules and bound metal ions can be discerned. However, those accustomed to interpreting the electron-density maps of macromolecules produced by X-ray crystallography need to be careful when assigning features such as these in cryo-EM maps because cations, for example, interact far more strongly with electrons than they do with X-rays. Using simulated electrostatic potential (ESP) maps as a tool led us to re-examine a recent cryo-EM map of the human ribosome, and we realized that some of the ESP peaks originally identified as novel groups covalently bonded to the N7, O6 or O4 atoms of several guanines, adenines or uridines, respectively, in this structure are likely to instead represent Mg2+ ions coordinated to these atoms, which provide only partial charge compensation compared with Mg2+ ions located next to phosphate groups. In addition, direct evidence is provided for a variation in the level of 2'-O ribose methylation of nucleotides in the human ribosome. ESP maps can thus help in identifying ions next to nucleotide bases, i.e. at positions that can be difficult to address in cryo-EM maps due to charge effects, which are specifically encountered in cryo-EM. This work is particularly relevant to nucleoprotein complexes and shows that it is important to consider charge effects when interpreting cryo-EM maps, thus opening possibilities for localizing charges in structures that may be relevant for enzymatic mechanisms and drug interactions.

Native Mass Spectrometry-Based Screening for Optimal Sample Preparation in Single-Particle Cryo-EM

Recent advances in single-particle cryogenic electron microscopy (cryo-EM) have enabled the structural determination of numerous protein assemblies at high resolution, yielding unprecedented insights into their function. However, despite its extraordinary capabilities, cryo-EM remains time-consuming and resource-intensive. It is therefore beneficial to have a means for rapidly assessing and optimizing the quality of samples prior to lengthy cryo-EM analyses. To do this, we have developed a native mass spectrometry (nMS) platform that provides rapid feedback on sample quality and highly streamlined biochemical screening. Because nMS enables accurate mass analysis of protein complexes, it is well suited to routine evaluation of the composition, integrity, and homogeneity of samples prior to their plunge-freezing on EM grids. We demonstrate the utility of our nMS-based platform for facilitating cryo-EM studies using structural characterizations of exemplar bacterial transcription complexes as well as the replication-transcription assembly from the SARS-CoV-2 virus that is responsible for the COVID-19 pandemic.

How low can we go? Structure determination of small biological complexes using single-particle cryo-EM

For decades, high-resolution structural studies of biological macromolecules with masses of <200kDa by cryo-EM single-particle analysis were considered infeasible. It was not until several years after the advent of direct detectors that the overlooked potential of cryo-EM for studying small complexes was first realized. Subsequent advances in sample preparation, imaging, and data processing algorithms have improved our ability to visualize small biological targets. In the past two years alone, nearly two hundred high-resolution structures have been determined of small (<200kDa) macromolecules, the smallest being approximately 39kDa in molecular weight. Here we summarize some salient lessons and strategies for cryo-EM studies of small biological complexes, and also consider future prospects for routine structure determination.

Solution structure and oligomeric state of the E. coliglycerol facilitator

Protein dynamics at atomic resolution can provide deep insights into the biological activities of proteins and enzymes but they can also make structure and dynamics studies challenging. Despite their well-known biological and pharmaceutical importance, integral membrane protein structure and dynamics studies lag behind those of water-soluble proteins mainly owing to solubility problems that result upon their removal from the membrane. Escherichia coli glycerol facilitator (GF) is a member of the aquaglyceroporin family that allows for the highly selective passive diffusion of its substrate glycerol across the inner membrane of the bacterium. Previous molecular dynamics simulations and hydrogen-deuterium exchange studies suggested that protein dynamics play an important role in the passage of glycerol through the protein pore. With the aim of studying GF dynamics by solution and solid-state nuclear magnetic resonance (NMR) spectroscopy we optimized the expression of isotope-labelled GF and explored various solubilizing agents including detergents, osmolytes, amphipols, random heteropolymers, lipid nanodiscs, bicelles and other buffer additives to optimize the solubility and polydispersity of the protein. The GF protein is most stable and soluble in lauryl maltose neopentyl glycol (LMNG), where it exists in a tetramer-octamer equilibrium. The solution structures of the GF tetramer and octamer were determined by negative-stain transmission electron microscopy (TEM), size-exclusion chromatography small-angle X-ray scattering (SEC-SAXS) and solid-state magic-angle spinning NMR spectroscopy. Although NMR sample preparation still needs optimization for full structure and dynamics studies, negative stain TEM and SEC-SAXS revealed low-resolution structures of the detergent-solubilized tetramer and octamer particles. The non-native octamer appears to form from the association of the cytoplasmic faces of two tetramers, the interaction apparently mediated by their disordered N- and C-termini. This information may be useful in future studies directed at reducing the heterogeneity and self-association of the protein.