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

Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies

Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe - Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms.

The application and development of electron microscopy for three-dimensional reconstruction in life science: a review

Imaging technologies have played a pivotal role in advancing biological research by enabling visualization of biological structures and processes. While traditional electron microscopy (EM) produces two-dimensional images, emerging techniques now allow high-resolution three-dimensional (3D) characterization of specimens in situ, meeting growing needs in molecular and cellular biology. Combining transmission electron microscopy (TEM) with serial sectioning inaugurated 3D imaging, attracting biologists seeking to explore cell ultrastructure and driving advancement of 3D EM reconstruction. By comprehensively and precisely rendering internal structure and distribution, 3D TEM reconstruction provides unparalleled ultrastructural insights into cells and molecules, holding tremendous value for elucidating structure-function relationships and broadly propelling structural biology. Here, we first introduce the principle of 3D reconstruction of cells and tissues by classical approaches in TEM and then discuss modern technologies utilizing TEM and on new SEM-based as well as cryo-electron microscope (cryo-EM) techniques. 3D reconstruction techniques from serial sections, electron tomography (ET), and the recent single-particle analysis (SPA) are examined; the focused ion beam scanning electron microscopy (FIB-SEM), the serial block-face scanning electron microscopy (SBF-SEM), and automatic tape-collecting lathe ultramicrotome (ATUM-SEM) for 3D reconstruction of large volumes are discussed. Finally, we review the challenges and development prospects of these technologies in life science. It aims to provide an informative reference for biological researchers.

Insights into protein structure using cryogenic light microscopy

Fluorescence microscopy has witnessed many clever innovations in the last two decades, leading to new methods such as structured illumination and super-resolution microscopies. The attainable resolution in biological samples is, however, ultimately limited by residual motion within the sample or in the microscope setup. Thus, such experiments are typically performed on chemically fixed samples. Cryogenic light microscopy (Cryo-LM) has been investigated as an alternative, drawing on various preservation techniques developed for cryogenic electron microscopy (Cryo-EM). Moreover, this approach offers a powerful platform for correlative microscopy. Another key advantage of Cryo-LM is the strong reduction in photobleaching at low temperatures, facilitating the collection of orders of magnitude more photons from a single fluorophore. This results in much higher localization precision, leading to Angstrom resolution. In this review, we discuss the general development and progress of Cryo-LM with an emphasis on its application in harnessing structural information on proteins and protein complexes.

Local Disordered Region Sampling (LDRS) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments

SUMMARY

The Local Disordered Region Sampling (LDRS, pronounced loaders) tool is a new module developed for IDPConformerGenerator, a previously validated approach to model intrinsically disordered proteins (IDPs). The IDPConformerGenerator LDRS module provides a method for generating all-atom conformations of intrinsically disordered protein regions at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB or mmCIF formatted structural template of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo-Side Chain Entropy, transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, the ability to be used as a library and via command-line, and the computational speed of the IDPConformerGenerator platform.

AVAILABILITY AND IMPLEMENTATION

The LDRS module is part of the IDPConformerGenerator modeling suite, which can be downloaded from GitHub at https://github.com/julie-forman-kay-lab/IDPConformerGenerator. IDPConformerGenerator is written in Python3 and works on Linux, Microsoft Windows, and Mac OS versions that support DSSP. Users can utilize LDRS's Python API for scripting the same way they can use any part of IDPConformerGenerator's API, by importing functions from the "idpconfgen.ldrs_helper" library. Otherwise, LDRS can be used as a command line interface application within IDPConformerGenerator. Full documentation is available within the command-line interface as well as on IDPConformerGenerator's official documentation pages (https://idpconformergenerator.readthedocs.io/en/latest/).

Unravelling the Mystery of COVID-19 Pathogenesis: Spike Protein and Cu Can Synergize to Trigger ROS Production

The COVID-19 pandemic has had a devastating impact on global health, highlighting the need to understand how the SARS-CoV-2 virus damages the lungs in order to develop effective treatments. Recent research has shown that patients with COVID-19 experience severe oxidative damage to various biomolecules. We propose that the overproduction of reactive oxygen species (ROS) in SARS-CoV-2 infection involves an interaction between copper ions and the virus's spike protein. We tested two peptide fragments, Ac-ELDKYFKNH-NH2 (L1) and Ac-WSHPQFEK-NH2 (L2), derived from the spike protein of the Wuhan strain and the β variant, respectively, and found that they bind Cu(II) ions and form a three-nitrogen complexes at lung pH. Our research demonstrates that these complexes trigger the overproduction of ROS, which can break both DNA strands and transform DNA into its linear form. Using A549 cells, we demonstrated that ROS overproduction occurs in the mitochondria, not in the cytoplasm. Our findings highlight the importance of the interaction between copper ions and the virus's spike protein in the development of lung damage and may aid in the development of therapeutic procedures.

Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments

The Local Disordered Region Sampling (LDRS, pronounced loaders) tool, developed for the IDPConformerGenerator platform (Teixeira et al. 2022), provides a method for generating all-atom conformations of intrinsically disordered regions (IDRs) at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB structure of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo Side Chain Entropy (MC-SCE) (Bhowmick and Head-Gordon 2015), transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, ability to be used as a library and via command-line, and computational speed of the IDPConformerGenerator platform.

Role of surfactants in electron cryo-microscopy film preparation

Single-particle electron cryo-microscopy (cryo-EM) has become an effective and straightforward approach to determine the structure of membrane proteins. However, obtaining cryo-EM grids of sufficient quality for high-resolution structural analysis remains a major bottleneck. One of the difficulties arises from the presence of detergents, which often leads to a lack of control of the ice thickness. Amphipathic polymers such as amphipols (APols) are detergent substitutes, which have proven to be valuable tools for cryo-EM studies. In this work, we investigate the physico-chemical behavior of APol- and detergent-containing solutions and show a correlation with the properties of vitreous thin films in cryo-EM grids. This study provides new insight on the potential of APols, allowing a better control of ice thickness while limiting protein adsorption at the air-water interface, as shown with the full-length mouse serotonin 5-HT3A receptor whose structure has been solved in APol. These findings may speed up the process of grid optimization to obtain high-resolution structures of membrane proteins.

Potassium Ion Channels in Glioma: From Basic Knowledge into Therapeutic Applications

Ion channels, specifically those controlling the flux of potassium across cell membranes, have recently been shown to exhibit an important role in the pathophysiology of glioma, the most common primary central nervous system tumor with a poor prognosis. Potassium channels are grouped into four subfamilies differing by their domain structure, gating mechanisms, and functions. Pertinent literature indicates the vital functions of potassium channels in many aspects of glioma carcinogenesis, including proliferation, migration, and apoptosis. The dysfunction of potassium channels can result in pro-proliferative signals that are highly related to calcium signaling as well. Moreover, this dysfunction can feed into migration and metastasis, most likely by increasing the osmotic pressure of cells allowing the cells to initiate the "escape" and "invasion" of capillaries. Reducing the expression or channel blockage has shown efficacy in reducing the proliferation and infiltration of glioma cells as well as inducing apoptosis, priming several approaches to target potassium channels in gliomas pharmacologically. This review summarizes the current knowledge on potassium channels, their contribution to oncogenic transformations in glioma, and the existing perspectives on utilizing them as potential targets for therapy.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology

Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.

Characterization of conformational heterogeneity via higher-dimensionality, proton-detected solid-state NMR

Site-specific heterogeneity of solid protein samples can be exploited as valuable information to answer biological questions ranging from thermodynamic properties determining fibril formation to protein folding and conformational stability upon stress. In particular, for proteins of increasing molecular weight, however, site-resolved assessment without residue-specific labeling is challenging using established methodology, which tends to rely on carbon-detected 2D correlations. Here we develop purely chemical-shift-based approaches for assessment of relative conformational heterogeneity that allows identification of each residue via four chemical-shift dimensions. High dimensionality diminishes the probability of peak overlap in the presence of multiple, heterogeneously broadened resonances. Utilizing backbone dihedral-angle reconstruction from individual contributions to the peak shape either via suitably adapted prediction routines or direct association with a relational database, the methods may in future studies afford assessment of site-specific heterogeneity of proteins without site-specific labeling.

NMR insights into dynamic, multivalent interactions of intrinsically disordered regions: from discrete complexes to condensates

The spatial and temporal organization of interactions between proteins underlie the regulation of most cellular processes. The requirement for such interactions to be specific predisposes a view that protein-protein interactions are relatively static and are formed through the stable complementarity of the interacting partners. A growing body of reports indicate, however, that many interactions lead to fuzzy complexes with an ensemble of conformations in dynamic exchange accounting for the observed binding. Here, we discuss how NMR has facilitated the characterization of these discrete, dynamic complexes and how such characterization has aided the understanding of dynamic, condensed phases of phase-separating proteins with exchanging multivalent interactions.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

Biophysical insights into glucose-dependent transcriptional regulation by PDX1

The pancreatic and duodenal homeobox 1 (PDX1) is a central regulator of glucose-dependent transcription of insulin in pancreatic β cells. PDX1 transcription factor activity is integral to the development and sustained health of the pancreas; accordingly, deciphering the complex network of cellular cues that lead to PDX1 activation or inactivation is an important step toward understanding the etiopathologies of pancreatic diseases and the development of novel therapeutics. Despite nearly 3 decades of research into PDX1 control of Insulin expression, the molecular mechanisms that dictate the function of PDX1 in response to glucose are still elusive. The transcriptional activation functions of PDX1 are regulated, in part, by its two intrinsically disordered regions, which pose a barrier to its structural and biophysical characterization. Indeed, many studies of PDX1 interactions, clinical mutations, and posttranslational modifications lack molecular level detail. Emerging methods for the quantitative study of intrinsically disordered regions and refined models for transactivation now enable us to validate and interrogate the biochemical and biophysical features of PDX1 that dictate its function. The goal of this review is to summarize existing PDX1 studies and, further, to generate a comprehensive resource for future studies of transcriptional control via PDX1.

SETH predicts nuances of residue disorder from protein embeddings

Predictions for millions of protein three-dimensional structures are only a few clicks away since the release of AlphaFold2 results for UniProt. However, many proteins have so-called intrinsically disordered regions (IDRs) that do not adopt unique structures in isolation. These IDRs are associated with several diseases, including Alzheimer’s Disease. We showed that three recent disorder measures of AlphaFold2 predictions (pLDDT, “experimentally resolved” prediction and “relative solvent accessibility”) correlated to some extent with IDRs. However, expert methods predict IDRs more reliably by combining complex machine learning models with expert-crafted input features and evolutionary information from multiple sequence alignments (MSAs). MSAs are not always available, especially for IDRs, and are computationally expensive to generate, limiting the scalability of the associated tools. Here, we present the novel method SETH that predicts residue disorder from embeddings generated by the protein Language Model ProtT5, which explicitly only uses single sequences as input. Thereby, our method, relying on a relatively shallow convolutional neural network, outperformed much more complex solutions while being much faster, allowing to create predictions for the human proteome in about 1 hour on a consumer-grade PC with one NVIDIA GeForce RTX 3060. Trained on a continuous disorder scale (CheZOD scores), our method captured subtle variations in disorder, thereby providing important information beyond the binary classification of most methods. High performance paired with speed revealed that SETH’s nuanced disorder predictions for entire proteomes capture aspects of the evolution of organisms. Additionally, SETH could also be used to filter out regions or proteins with probable low-quality AlphaFold2 3D structures to prioritize running the compute-intensive predictions for large data sets. SETH is freely publicly available at: https://github.com/Rostlab/SETH.

Linear discriminant analysis reveals hidden patterns in NMR chemical shifts of intrinsically disordered proteins

NMR spectroscopy is key in the study of intrinsically disordered proteins (IDPs). Yet, even the first step in such an analysis-the assignment of observed resonances to particular nuclei-is often problematic due to low peak dispersion in the spectra of IDPs. We show that the assignment process can be aided by finding "hidden" chemical shift patterns specific to the amino acid residue types. We find such patterns in the training data from the Biological Magnetic Resonance Bank using linear discriminant analysis, and then use them to classify spin systems in an α-synuclein sample prepared by us. We describe two situations in which the procedure can greatly facilitate the analysis of NMR spectra. The first involves the mapping of spin systems chains onto the protein sequence, which is part of the assignment procedure-a prerequisite for any NMR-based protein analysis. In the second, the method supports assignment transfer between similar samples. We conducted experiments to demonstrate these cases, and both times the majority of spin systems could be unambiguously assigned to the correct residue types.

Evolving Experimental Techniques for Structure-Based Drug Design

Structure-based drug design (SBDD) is a prominent method in rational drug development and has traditionally benefitted from the atomic models of protein targets obtained using X-ray crystallography at cryogenic temperatures. In this perspective, we highlight recent advances in the development of structural techniques that are capable of probing dynamic information about protein targets. First, we discuss advances in the field of X-ray crystallography including serial room-temperature crystallography as a method for obtaining high-resolution conformational dynamics of protein-inhibitor complexes. Next, we look at cryogenic electron microscopy (cryoEM), another high-resolution technique that has recently been used to study proteins and protein complexes that are too difficult to crystallize. Finally, we present small-angle X-ray scattering (SAXS) as a potential high-throughput screening tool to identify inhibitors that target protein complexes and protein oligomerization.

Deciphering a hexameric protein complex with Angstrom optical resolution

Cryogenic optical localization in three dimensions (COLD) was recently shown to resolve up to four binding sites on a single protein. However, because COLD relies on intensity fluctuations that result from the blinking behavior of fluorophores, it is limited to cases where individual emitters show different brightness. This significantly lowers the measurement yield. To extend the number of resolved sites as well as the measurement yield, we employ partial labeling and combine it with polarization encoding in order to identify single fluorophores during their stochastic blinking. We then use a particle classification scheme to identify and resolve heterogenous subsets and combine them to reconstruct the three-dimensional arrangement of large molecular complexes. We showcase this method (polarCOLD) by resolving the trimer arrangement of proliferating cell nuclear antigen (PCNA) and six different sites of the hexamer protein Caseinolytic Peptidase B (ClpB) of Thermus thermophilus in its quaternary structure, both with Angstrom resolution. The combination of polarCOLD and single-particle cryogenic electron microscopy (cryoEM) promises to provide crucial insight into intrinsic heterogeneities of biomolecular structures. Furthermore, our approach is fully compatible with fluorescent protein labeling and can, thus, be used in a wide range of studies in cell and membrane biology.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Do molecular dynamics force fields accurately model Ramachandran distributions of amino acid residues in water?

Molecular dynamics (MD) is a powerful tool for studying intrinsically disordered proteins, however, its reliability depends on the accuracy of the force field. We assess Amber ff19SB, Amber ff14SB, OPLS-AA/M, and CHARMM36m with respect to their capacity to capture intrinsic conformational dynamics of 14 guest residues x (=G, A, L, V, I, F, Y, D^P, E^P, R, C, N, S, T) in GxG peptides in water. The MD-derived Ramachandran distribution of each guest residue is used to calculate 5 J-coupling constants and amide I' band profiles to facilitate a comparison to spectroscopic data through reduced χ² functions. We show that the Gaussian model, optimized to best fit the experimental data, outperforms all MD force fields by an order of magnitude. The weaknesses of the MD force fields are: (i) insufficient variability of the polyproline II (pPII) population among the guest residues; (ii) oversampling of antiparallel at the expense of transitional β-strand region; (iii) inadequate sampling of turn-forming conformations for ionizable and polar residues; and (iv) insufficient guest residue-specificity of the Ramachandran distributions. Whereas Amber ff19SB performs worse than the other three force fields with respect to χ² values, it accounts for residue-specific pPII content better than the other three force fields. Additional testing of residue-specific RSFF1 and Amber ff14SB combined with TIP4P/2005 on six guest residues x (=A, I, F, D^P, R, S) reveals that residue specificity derived from protein coil libraries or an improved water model alone do not result in significantly lower χ² values.

Allosteric binding on nuclear receptors: Insights on screening of non-competitive endocrine-disrupting chemicals

Endocrine-disrupting chemicals (EDCs) can compete with endogenous hormones and bind to the orthosteric site of nuclear receptors (NRs), affecting normal endocrine system function and causing severe symptoms. Recently, a series of pharmaceuticals and personal care products (PPCPs) have been discovered to bind to the allosteric sites of NRs and induce similar effects. However, it remains unclear how diverse EDCs work in this new way. Therefore, we have systematically summarized the allosteric sites and underlying mechanisms based on existing studies, mainly regarding drugs belonging to the PPCP class. Advanced methods, classified as structural biology, biochemistry and computational simulation, together with their advantages and hurdles for allosteric site recognition and mechanism insight have also been described. Furthermore, we have highlighted two available strategies for virtual screening of numerous EDCs, relying on the structural features of allosteric sites and lead compounds, respectively. We aim to provide reliable theoretical and technical support for a broader view of various allosteric interactions between EDCs and NRs, and to drive high-throughput and accurate screening of potential EDCs with non-competitive effects.

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.

Cosolvent and Dynamic Effects in Binding Pocket Search by Docking Simulations

The lack of conformational sampling in virtual screening projects can lead to inefficient results because many of the potential drugs may not be able to bind to the target protein during the static docking simulations. Here, we performed ensemble docking for around 2000 United States Food and Drug Administration (FDA)-approved drugs with the RNA-dependent RNA polymerase (RdRp) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a target. The representative protein structures were generated by clustering classical molecular dynamics trajectories, which were evolved using three solvent scenarios, namely, pure water, benzene/water and phenol/water mixtures. The introduction of dynamic effects in the theoretical model showed improvement in docking results in terms of the number of strong binders and binding sites in the protein. Some of the discovered pockets were found only for the cosolvent simulations, where the nonpolar probes induced local conformational changes in the protein that lead to the opening of transient pockets. In addition, the selection of the ligands based on a combination of the binding free energy and binding free energy gap between the best two poses for each ligand provided more suitable binders than the selection of ligands based solely on one of the criteria. The application of cosolvent molecular dynamics to enhance the sampling of the configurational space is expected to improve the efficacy of virtual screening campaigns of future drug discovery projects.

Advances in Hydrogen/Deuterium Exchange Mass Spectrometry and the Pursuit of Challenging Biological Systems

Solution-phase hydrogen/deuterium exchange (HDX) coupled to mass spectrometry (MS) is a widespread tool for structural analysis across academia and the biopharmaceutical industry. By monitoring the exchangeability of backbone amide protons, HDX-MS can reveal information about higher-order structure and dynamics throughout a protein, can track protein folding pathways, map interaction sites, and assess conformational states of protein samples. The combination of the versatility of the hydrogen/deuterium exchange reaction with the sensitivity of mass spectrometry has enabled the study of extremely challenging protein systems, some of which cannot be suitably studied using other techniques. Improvements over the past three decades have continually increased throughput, robustness, and expanded the limits of what is feasible for HDX-MS investigations. To provide an overview for researchers seeking to utilize and derive the most from HDX-MS for protein structural analysis, we summarize the fundamental principles, basic methodology, strengths and weaknesses, and the established applications of HDX-MS while highlighting new developments and applications.

Intrinsically disordered protein regions at membrane contact sites

Membrane contact sites (MCS) are regions of close apposition between membrane-bound organelles. Proteins that occupy MCS display various domain organisation. Among them, lipid transfer proteins (LTPs) frequently contain both structured domains as well as regions of intrinsic disorder. In this review, we discuss the various roles of intrinsically disordered protein regions (IDPRs) in LTPs as well as in other proteins that are associated with organelle contact sites. We distinguish the following functions: (i) to act as flexible tethers between two membranes; (ii) to act as entropic barriers to prevent protein crowding and regulate membrane tethering geometry; (iii) to define the action range of catalytic domains. These functions are added to other functions of IDPRs in membrane environments, such as mediating protein-protein and protein-membrane interactions. We suggest that the overall efficiency and fidelity of contact sites might require fine coordination between all these IDPR activities.

Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses

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Potential coronavirus spike protein mimicry revealed by structural comparison.

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Human and non-human protein potential interactions with virus identified.

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Predicted structural mimicry corroborated by protein–protein docking.

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Epitope-based alignments may help guide vaccine efforts.

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism and druggability of the virus. Peptide and epitope motifs have been detected on coronavirus spike proteins using sequence homology approaches; however, comparing the three-dimensional shape of the protein has been shown as more informative in predicting mimicry than sequence-based comparisons. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known protein models with the receptor-binding motifs and verify potential mimicked interactions with protein docking simulations. Both human and non-human proteins were returned for all three receptor-binding motifs. For example, all three were similar to several proteins containing EGF-like domains: some of which are endogenous to humans, such as thrombomodulin, and others exogenous, such as Plasmodium falciparum MSP-1. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins.

Scrutinizing Coronaviruses Using Publicly Available Bioinformatic Tools: The Viral Structural Proteins as a Case Study

Since early 2020, the world suffers from a new beta-coronavirus, called SARS-CoV-2, that has devastating effects globally due to its associated disease, Covid-19. Until today, Covid-19, which not only causes life-threatening lung infections but also impairs various other organs and tissues, has killed hundreds of thousands of people and caused irreparable damage to many others. Since the very onset of the pandemic, huge efforts were made worldwide to fully understand this virus and numerous studies were, and still are, published. Many of these deal with structural analyses of the viral spike glycoprotein and with vaccine development, antibodies and antiviral molecules or immunomodulators that are assumed to become essential tools in the struggle against the virus. This paper summarizes knowledge on the properties of the four structural proteins (spike protein S, membrane protein M, envelope protein E and nucleocapsid protein N) of the SARS-CoV-2 virus and its relatives, SARS-CoV and MERS-CoV, that emerged few years earlier. Moreover, attention is paid to ways to analyze such proteins using freely available bioinformatic tools and, more importantly, to bring these proteins alive by looking at them on a computer/laptop screen with the easy-to-use but highly performant and interactive molecular graphics program DeepView. It is hoped that this paper will stimulate non-bioinformaticians and non-specialists in structural biology to scrutinize these and other macromolecules and as such will contribute to establishing procedures to fight these and maybe other forthcoming viruses.

Amphipathic environments for determining the structure of membrane proteins by single-particle electron cryo-microscopy

Over the past decade, the structural biology of membrane proteins (MPs) has taken a new turn thanks to epoch-making technical progress in single-particle electron cryo-microscopy (cryo-EM) as well as to improvements in sample preparation. The present analysis provides an overview of the extent and modes of usage of the various types of surfactants for cryo-EM studies. Digitonin, dodecylmaltoside, protein-based nanodiscs, lauryl maltoside-neopentyl glycol, glyco-diosgenin, and amphipols (APols) are the most popular surfactants at the vitrification step. Surfactant exchange is frequently used between MP purification and grid preparation, requiring extensive optimization each time the study of a new MP is undertaken. The variety of both the surfactants and experimental approaches used over the past few years bears witness to the need to continue developing innovative surfactants and optimizing conditions for sample preparation. The possibilities offered by novel APols for EM applications are discussed.

Hybrid methods for combined experimental and computational determination of protein structure

Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.

Structural Dynamics of Glutamate Signaling Systems by smFRET

Single-molecule Förster resonance energy transfer (smFRET) is a powerful technique for investigating the structural dynamics of biological macromolecules. smFRET reveals the conformational landscape and dynamic changes of proteins by building on the static structures found using cryo-electron microscopy, x-ray crystallography, and other methods. Combining smFRET with static structures allows for a direct correlation between dynamic conformation and function. Here, we discuss the different experimental setups, fluorescence detection schemes, and data analysis strategies that enable the study of structural dynamics of glutamate signaling across various timescales. We illustrate the versatility of smFRET by highlighting studies of a wide range of questions, including the mechanism of activation and transport, the role of intrinsically disordered segments, and allostery and cooperativity between subunits in biological systems responsible for glutamate signaling.

Atomistic fibrillar architectures of polar prion-inspired heptapeptides

This article provides the computational prediction of the atomistic architectures resulting from self-assembly of the polar heptapeptide sequences NYNYNYN, SYSYSYS and GYGYGYG. Using a combination of molecular dynamics and a newly developed tool for non-covalent interaction analysis, we uncover the properties of a new class of bionanomaterials, including hydrogen-bonded polar zippers, and the relationship between peptide composition, fibril geometry and weak interaction networks. Our results, corroborated by experimental observations, provide the basis for the rational design of prion-inspired nanomaterials.

Experimentally Determined Long Intrinsically Disordered Protein Regions Are Now Abundant in the Protein Data Bank

Intrinsically disordered protein regions are commonly defined from missing electron density in X-ray structures. Experimental evidence for long disorder regions (LDRs) of at least 30 residues was so far limited to manually curated proteins. Here, we describe a comprehensive and large-scale analysis of experimental LDRs for 3133 unique proteins, demonstrating an increasing coverage of intrinsic disorder in the Protein Data Bank (PDB) in the last decade. The results suggest that long missing residue regions are a good quality source to annotate intrinsically disordered regions and perform functional analysis in large data sets. The consensus approach used to define LDRs allows to evaluate context dependent disorder and provide a common definition at the protein level.

The C-terminal domains of the NMDA receptor: How intrinsically disordered tails affect signalling, plasticity and disease

NMDA receptors are part of the ionotropic glutamate receptor family, and are crucial for neurotransmission and memory. At the cellular level, the effects of activating these receptors include long-term potentiation (LTP) or depression (LTD). The NMDA receptor is a stringently gated cation channel permeable to Ca²⁺ , and it shares the molecular architecture of a tetrameric ligand-gated ion channel with the other family members. Its subunits, however, have uniquely long cytoplasmic C-terminal domains (CTDs). While the molecular gymnastics of the extracellular domains have been described in exquisite detail, much less is known about the structure and function of these CTDs. The CTDs vary dramatically in length and sequence between receptor subunits, but they all have a composition characteristic of intrinsically disordered proteins. The CTDs affect channel properties, trafficking and downstream signalling output from the receptor, and these functions are regulated by alternative splicing, protein-protein interactions, and post-translational modifications such as phosphorylation and palmitoylation. Here, we review the roles of the CTDs in synaptic plasticity with a focus on biochemical mechanisms. In total, the CTDs play a multifaceted role as a modifier of channel function, a regulator of cellular location and abundance, and signalling scaffold control the downstream signalling output.

Understanding the Binding Induced Folding of Intrinsically Disordered Proteins by Protein Engineering: Caveats and Pitfalls

Many proteins lack a well-defined three-dimensional structure in isolation. These proteins, typically denoted as intrinsically disordered proteins (IDPs), may display a characteristic disorder-to-order transition when binding their physiological partner(s). From an experimental perspective, it is of great importance to establish the general grounds to understand how such folding processes may be explored. Here we discuss the caveats and the pitfalls arising when applying to IDPs one of the key techniques to characterize the folding of globular proteins, the Φ value analysis. This method is based on measurements of the free energy changes of transition and native states upon conservative, non-disrupting, mutations. On the basis of available data, we reinforce the validity of Φ value analysis in the study of IDPs and suggest future experiments to further validate this powerful experimental method.

Live Analysis and Reconstruction of Single-Particle Cryo-Electron Microscopy Data with CryoFLARE

Efficient, reproducible and accountable single-particle cryo-electron microscopy structure determination is tedious and often impeded by the lack of a standardized procedure for data analysis and processing. To address this issue, we have developed the FMI Live Analysis and Reconstruction Engine (CryoFLARE). CryoFLARE is a modular open-source platform offering easy integration of new processing algorithms developed by the cryo-EM community. It provides a user-friendly interface that allows fast setup of standardized workflows, serving the need of pharmaceutical industry and academia alike who need to optimize throughput of their microscope. To consistently document how data is processed, CryoFLARE contains an integrated reporting facility to create reports. Live analysis and processing parallel to data acquisition are used to monitor and optimize data quality. Problems at the level of the sample preparation (heterogeneity, ice thickness, sparse particles, areas selected for acquisition, etc.) or misalignments of the microscope optics can quickly be detected and rectified before data collection is continued. Interfacing with automated data collection software for retrieval of acquisition metadata reduces user input needed for analysis, and with it minimizes potential sources of errors and workflow inconsistencies. Local and remote export support in Relion-compatible job and data format allows seamless integration into the refinement process. The support for nonlinear workflows and fine-grained scheduling for mixed workflows with separate CPU and GPU based calculation steps ensures optimal use of processing hardware. CryoFLARE's flexibility allows it to be used for all types of image acquisitions, ranging from sample screening to high-resolution data collection, and it offers a new alternative for setting up image processing workflows. It can be used without modifications of the hardware/software delivered by the microscope supplier. As it runs on a server in parallel to the hardware used for acquisition, it can easily be set up for remote display connections and fast control of the acquisition status.

Neuropathy target esterase (NTE/PNPLA6) and organophosphorus compound-induced delayed neurotoxicity (OPIDN)

Systemic inhibition of neuropathy target esterase (NTE) with certain organophosphorus (OP) compounds produces OP compound-induced delayed neurotoxicity (OPIDN), a distal degeneration of axons in the central nervous system (CNS) and peripheral nervous system (PNS), thereby providing a powerful model for studying a spectrum of neurodegenerative diseases. Axonopathies are important medical entities in their own right, but in addition, illnesses once considered primary neuronopathies are now thought to begin with axonal degeneration. These disorders include Alzheimer's disease, Parkinson's disease, and motor neuron diseases such as amyotrophic lateral sclerosis (ALS). Moreover, conditional knockout of NTE in the mouse CNS produces vacuolation and other degenerative changes in large neurons in the hippocampus, thalamus, and cerebellum, along with degeneration and swelling of axons in ascending and descending spinal cord tracts. In humans, NTE mutations cause a variety of neurodegenerative conditions resulting in a range of deficits including spastic paraplegia and blindness. Mutations in the Drosophila NTE orthologue SwissCheese (SWS) produce neurodegeneration characterized by vacuolization that can be partially rescued by expression of wild-type human NTE, suggesting a potential therapeutic approach for certain human neurological disorders. This chapter defines NTE and OPIDN, presents an overview of OP compounds, provides a rationale for NTE research, and traces the history of discovery of NTE and its relationship to OPIDN. It then briefly describes subsequent studies of NTE, including practical applications of the assay; aspects of its domain structure, subcellular localization, and tissue expression; abnormalities associated with NTE mutations, knockdown, and conventional or conditional knockout; and hypothetical models to help guide future research on elucidating the role of NTE in OPIDN.

Special Issue: The Actin-Myosin Interaction in Muscle: Background and Overview

Muscular contraction is a fundamental phenomenon in all animals; without it life as we know it would be impossible. The basic mechanism in muscle, including heart muscle, involves the interaction of the protein filaments myosin and actin. Motility in all cells is also partly based on similar interactions of actin filaments with non-muscle myosins. Early studies of muscle contraction have informed later studies of these cellular actin-myosin systems. In muscles, projections on the myosin filaments, the so-called myosin heads or cross-bridges, interact with the nearby actin filaments and, in a mechanism powered by ATP-hydrolysis, they move the actin filaments past them in a kind of cyclic rowing action to produce the macroscopic muscular movements of which we are all aware. In this special issue the papers and reviews address different aspects of the actin-myosin interaction in muscle as studied by a plethora of complementary techniques. The present overview provides a brief and elementary introduction to muscle structure and function and the techniques used to study it. It goes on to give more detailed descriptions of what is known about muscle components and the cross-bridge cycle using structural biology techniques, particularly protein crystallography, electron microscopy and X-ray diffraction. It then has a quick look at muscle mechanics and it summarises what can be learnt about how muscle works based on the other studies covered in the different papers in the special issue. A picture emerges of the main molecular steps involved in the force-producing process; steps that are also likely to be seen in non-muscle myosin interactions with cellular actin filaments. Finally, the remarkable advances made in studying the effects of mutations in the contractile assembly in causing specific muscle diseases, particularly those in heart muscle, are outlined and discussed.