In situ structural analysis of SARS-CoV-2 spike reveals flexibility mediated by three hinges

MiLoPYP: self-supervised molecular pattern mining and particle localization in situ

Cryo-electron tomography allows the routine visualization of cellular landscapes in three dimensions at nanometer-range resolutions. When combined with single-particle tomography, it is possible to obtain near-atomic resolution structures of frequently occurring macromolecules within their native environment. Two outstanding challenges associated with cryo-electron tomography/single-particle tomography are the automatic identification and localization of proteins, tasks that are hindered by the molecular crowding inside cells, imaging distortions characteristic of cryo-electron tomography tomograms and the sheer size of tomographic datasets. Current methods suffer from low accuracy, demand extensive and time-consuming manual labeling or are limited to the detection of specific types of proteins. Here, we present MiLoPYP, a two-step dataset-specific contrastive learning-based framework that enables fast molecular pattern mining followed by accurate protein localization. MiLoPYP's ability to effectively detect and localize a wide range of targets including globular and tubular complexes as well as large membrane proteins, will contribute to streamline and broaden the applicability of high-resolution workflows for in situ structure determination.

Markerauto2: A fast and robust fully automatic fiducial marker-based tilt series alignment software for electron tomography

Cryoelectron tomography (cryo-ET) has become an indispensable technology for visualizing in situ biological ultrastructures, where the tilt series alignment is the key step to obtain a high-resolution three-dimensional reconstruction. Specifically, with the advent of high-throughput cryo-ET data collection, there is an increasing demand for high-accuracy and fully automatic tilt series alignment, to enable efficient data processing. Here, we propose Markerauto2, a fast and robust fully automatic software that enables accurate fiducial marker-based tilt series alignment. Markerauto2 implements the following novel pipelines: (1) an accelerated high-precision fiducial marker detection with wavelet multiscale template, (2) an ultra-fast and robust fiducial marker tracking supported by hashed geometric features, (3) a high-angle fiducial marker supplementation strategy to produce more complete tracks, and (4) a precise and robust calibration of projection parameters with group-weighted parameter optimization. Comprehensive experiments conducted on both simulated and real-world datasets demonstrate the robustness, efficiency, and effectiveness of the proposed software.

Broad Adaptability of Coronavirus Adhesion Revealed from the Complementary Surface Affinity of Membrane and Spikes

Coronavirus stands for a large family of viruses characterized by protruding spikes surrounding a lipidic membrane adorned with proteins. The present study explores the adhesion of transmissible gastroenteritis coronavirus (TGEV) particles on a variety of reference solid surfaces that emulate typical virus-surface interactions. Atomic force microscopy informs about trapping effectivity and the shape of the virus envelope on each surface, revealing that the deformation of TGEV particles spans from 20% to 50% in diameter. Given this large deformation range, experimental Langmuir isotherms convey an unexpectedly moderate variation in the adsorption-free energy, indicating a viral adhesion adaptability which goes beyond the membrane. The combination of an extended Helfrich theory and coarse-grained simulations reveals that, in fact, the envelope and the spikes present complementary adsorption affinities. While strong membrane-surface interaction lead to highly deformed TGEV particles, surfaces with strong spike attraction yield smaller deformations with similar or even larger adsorption-free energies.

Structure and inhibition of SARS-CoV-2 spike refolding in membranes

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein binds the receptor angiotensin converting enzyme 2 (ACE2) and drives virus-host membrane fusion through refolding of its S2 domain. Whereas the S1 domain contains high sequence variability, the S2 domain is conserved and is a promising pan-betacoronavirus vaccine target. We applied cryo-electron tomography to capture intermediates of S2 refolding and understand inhibition by antibodies to the S2 stem-helix. Subtomogram averaging revealed ACE2 dimers cross-linking spikes before transitioning into S2 intermediates, which were captured at various stages of refolding. Pan-betacoronavirus neutralizing antibodies targeting the S2 stem-helix bound to and inhibited refolding of spike prehairpin intermediates. Combined with molecular dynamics simulations, these structures elucidate the process of SARS-CoV-2 entry and reveal how pan-betacoronavirus S2-targeting antibodies neutralize infectivity by arresting prehairpin intermediates.

Adsorption-Driven Deformation and Footprints of the RBD Proteins in SARS-CoV-2 Variants on Biological and Inanimate Surfaces

Respiratory viruses, carried through airborne microdroplets, frequently adhere to surfaces, including plastics and metals. However, our understanding of the interactions between viruses and materials remains limited, particularly in scenarios involving polarizable surfaces. Here, we investigate the role of the receptor-binding domain (RBD) of the spike protein mutations on the adsorption of SARS-CoV-2 to hydrophobic and hydrophilic surfaces employing molecular simulations. To contextualize our findings, we contrast the interactions on inanimate surfaces with those on native biological interfaces, specifically the angiotensin-converting enzyme 2. Notably, we identify a 2-fold increase in structural deformations for the protein's receptor binding motif (RBM) onto inanimate surfaces, indicative of enhanced shock-absorbing mechanisms. Furthermore, the distribution of adsorbed amino acids (landing footprints) on the inanimate surface reveals a distinct regional asymmetry relative to the biological interface, with roughly half of the adsorbed amino acids arranged in opposite sites. In spite of the H-bonds formed at the hydrophilic substrate, the simulations consistently show a higher number of contacts and interfacial area with the hydrophobic surface, where the wild-type RBD adsorbs more strongly than the Delta or Omicron RBDs. In contrast, the adsorption of Delta and Omicron to hydrophilic surfaces was characterized by a distinctive hopping-pattern. The novel shock-absorbing mechanisms identified in the virus adsorption on inanimate surfaces show the embedded high-deformation capacity of the RBD without losing its secondary structure, which could lead to current experimental strategies in the design of virucidal surfaces.

Integrated cryoEM structure of a spumaretrovirus reveals cross-kingdom evolutionary relationships and the molecular basis for assembly and virus entry

Foamy viruses (FVs) are an ancient lineage of retroviruses, with an evolutionary history spanning over 450 million years. Vector systems based on Prototype Foamy Virus (PFV) are promising candidates for gene and oncolytic therapies. Structural studies of PFV contribute to the understanding of the mechanisms of FV replication, cell entry and infection, and retroviral evolution. Here we combine cryoEM and cryoET to determine high-resolution in situ structures of the PFV icosahedral capsid (CA) and envelope glycoprotein (Env), including its type III transmembrane anchor and membrane-proximal external region (MPER), and show how they are organized in an integrated structure of assembled PFV particles. The atomic models reveal an ancient retroviral capsid architecture and an unexpected relationship between Env and other class 1 fusion proteins of the Mononegavirales. Our results represent the de novo structure determination of an assembled retrovirus particle.

Mechanistic Insights into How the Single Point Mutation Change the Autoantibody Repertoire

A recent study showed that just one point mutation F33 to Y in the complementarity-determining region 1 of heavy chain (H-CDR1) could lead to the auto-antibody losing its DNA binding ability. However, the potential molecular mechanisms have not been well elucidated. In this study, we investigated how the antibody lost the DNA binding ability caused by mutation F33 to Y in the H-CDR1. We found that the electrostatic force was not the primary driving force for the interaction between anti-DNA antibodies and the antigen single strand DNA (ssDNA), and that the H-CDR2 largely contributed to the binding of antigen ssDNA, even larger than H-CDR1. The H-F33Y mutation could increase the hydrogen-bond interaction but impair the pi-pi stacking interaction between the antibody and ssDNA. We further found that F33H, W98H and Y95L in the wiletype antibody could form the stable pi-pi stacking interaction with the nucleotide bases of ssDNA. However, the Y33 in mutant could not form the parallel sandwich pi-pi stacking interaction with the ssDNA. To further confirm the importance of pi-pi stacking, the wildtype antibody and the mutants (F33YH, F33AH, W98AH and Y95AL) were experimentally expressed in CHO cells and purified, and the results from ELISA clearly showed that all the mutants lost the ssDNA binding ability. Taken together, our findings may not only deepen the understanding of the underlying interaction mechanism between autoantibody and antigen, but also broad implications in the field of antibody engineer.

SARS-CoV-2 Omicron XBB lineage spike structures, conformations, antigenicity, and receptor recognition

A recombinant lineage of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryoelectron microscopy (cryo-EM) structures of XBB.1.5, XBB.1.16, EG.5, and EG.5.1 spike (S) ectodomains to reveal reinforced 3-receptor binding domain (RBD)-down receptor-inaccessible closed states mediated by interprotomer RBD interactions previously observed in BA.1 and BA.2. Improved XBB.1.5 and XBB.1.16 RBD stability compensated for stability loss caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. S1 subunit mutations had long-range impacts on conformation and epitope presentation in the S2 subunit. Our results reveal continued S protein evolution via simultaneous optimization of multiple parameters, including stability, receptor binding, and immune evasion, and the dramatic effects of relatively few residue substitutions in altering the S protein conformational landscape.

Cryo-electron microscopy in the study of virus entry and infection

Viruses have been responsible for many epidemics and pandemics that have impacted human life globally. The COVID-19 pandemic highlighted both our vulnerability to viral outbreaks, as well as the mobilization of the scientific community to come together to combat the unprecedented threat to humanity. Cryo-electron microscopy (cryo-EM) played a central role in our understanding of SARS-CoV-2 during the pandemic and continues to inform about this evolving pathogen. Cryo-EM with its two popular imaging modalities, single particle analysis (SPA) and cryo-electron tomography (cryo-ET), has contributed immensely to understanding the structure of viruses and interactions that define their life cycles and pathogenicity. Here, we review how cryo-EM has informed our understanding of three distinct viruses, of which two - HIV-1 and SARS-CoV-2 infect humans, and the third, bacteriophages, infect bacteria. For HIV-1 and SARS-CoV-2 our focus is on the surface glycoproteins that are responsible for mediating host receptor binding, and host and cell membrane fusion, while for bacteriophages, we review their structure, capsid maturation, attachment to the bacterial cell surface and infection initiation mechanism.

Deposition of Human-Serum-Albumin-Functionalized Spheroidal Particles on Abiotic Surfaces: Reference Kinetic Results for Bioparticles

Human serum albumin (HSA) corona formation on polymer microparticles of a spheroidal shape was studied using dynamic light scattering and Laser Doppler Velocimetry (LDV). Physicochemical characteristics of the albumin comprising the zeta potential and the isoelectric point were determined as a function of pH for various ionic strengths. Analogous characteristics of the polymer particles were analyzed. The adsorption of albumin on the particles was in situ monitored by LDV. The stability of the HSA-functionalized particle suspensions under various pHs and their electrokinetic properties were also determined. The deposition kinetics of the particles on mica, silica and gold sensors were investigated by optical microscopy, AFM and quartz microbalance (QCM) under diffusion and flow conditions. The obtained results were interpreted in terms of the random sequential adsorption model that allowed to estimate the range of applicability of QCM for determining the deposition kinetics of viruses and bacteria at abiotic surfaces.

Light-Induced Transformation of Virus-Like Particles on TiO2

Titanium dioxide (TiO2) shows significant potential as a self-cleaning material to inactivate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and prevent virus transmission. This study provides insights into the impact of UV-A light on the photocatalytic inactivation of adsorbed SARS-CoV-2 virus-like particles (VLPs) on a TiO2 surface at the molecular and atomic levels. X-ray photoelectron spectroscopy, combined with density functional theory calculations, reveals that spike proteins can adsorb on TiO2 predominantly via their amine and amide functional groups in their amino acids blocks. We employ atomic force microscopy and grazing-incidence small-angle X-ray scattering (GISAXS) to investigate the molecular-scale morphological changes during the inactivation of VLPs on TiO2 under light irradiation. Notably, in situ measurements reveal photoinduced morphological changes of VLPs, resulting in increased particle diameters. These results suggest that the denaturation of structural proteins induced by UV irradiation and oxidation of the virus structure through photocatalytic reactions can take place on the TiO2 surface. The in situ GISAXS measurements under an N2 atmosphere reveal that the virus morphology remains intact under UV light. This provides evidence that the presence of both oxygen and UV light is necessary to initiate photocatalytic reactions on the surface and subsequently inactivate the adsorbed viruses. The chemical insights into the virus inactivation process obtained in this study contribute significantly to the development of solid materials for the inactivation of enveloped viruses.

Atomistic Prediction of Structures, Conformational Ensembles and Binding Energetics for the SARS-CoV-2 Spike JN.1, KP.2 and KP.3 Variants Using AlphaFold2 and Molecular Dynamics Simulations: Mutational Profiling and Binding Free Energy Analysis Reveal Epistatic Hotspots of the ACE2 Affinity and Immune Escape

The most recent wave of SARS-CoV-2 Omicron variants descending from BA.2 and BA.2.86 exhibited improved viral growth and fitness due to convergent evolution of functional hotspots. These hotspots operate in tandem to optimize both receptor binding for effective infection and immune evasion efficiency, thereby maintaining overall viral fitness. The lack of molecular details on structure, dynamics and binding energetics of the latest FLiRT and FLuQE variants with the ACE2 receptor and antibodies provides a considerable challenge that is explored in this study. We combined AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested that the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that enable to protect and restore ACE2 binding affinity while conferring beneficial immune escape. To examine immune escape mechanisms, we performed structure-based mutational profiling of the spike protein binding with several classes of antibodies that displayed impaired neutralization against BA.2.86, JN.1, KP.2 and KP.3. The results confirmed the experimental data that JN.1, KP.2 and KP.3 harboring the L455S and F456L mutations can significantly impair the neutralizing activity of class-1 monoclonal antibodies, while the epistatic effects mediated by F456L can facilitate the subsequent convergence of Q493E changes to rescue ACE2 binding. Structural and energetic analysis provided a rationale to the experimental results showing that BD55-5840 and BD55-5514 antibodies that bind to different binding epitopes can retain neutralizing efficacy against all examined variants BA.2.86, JN.1, KP.2 and KP.3. The results support the notion that evolution of Omicron variants may favor emergence of lineages with beneficial combinations of mutations involving mediators of epistatic couplings that control balance of high ACE2 affinity and immune evasion.

Optical detection of infectious SARS-CoV-2 virions by counting spikes

Existing methods for the mass detection of viruses are limited to the registration of small amounts of a viral genome or specific protein markers. In spite of high sensitivity, the applied methods cannot distinguish between virulent viral particles and non-infectious viral particle debris. We report an approach to solve this long-standing challenge using the SARS-CoV-2 virus as an example. We show that wide-field optical microscopy with the state-of-the-art mesoscopic fluorescent labels, formed by a core-shell plasmonic nanoparticle with fluorescent dye molecules in the core-shell that are strongly coupled to the plasmonic nanoparticle, not only rapidly, i.e. in less than 20 minutes after sampling, detects SARS-CoV-2 virions directly in a patient sample without a pre-concentration step, but can also distinguish between infectious and non-infectious virus strains by counting the spikes on the lipid envelope of individual viral particles.

The palisade layer of the poxvirus core is composed of flexible A10 trimers

Due to its asymmetric shape, size and compactness, the structure of the infectious mature virus (MV) of vaccinia virus (VACV), the best-studied poxvirus, remains poorly understood. Instead, subviral particles, in particular membrane-free viral cores, have been studied with cryo-electron microscopy. Here, we compared viral cores obtained by detergent stripping of MVs with cores in the cellular cytoplasm, early in infection. We focused on the prominent palisade layer on the core surface, combining cryo-electron tomography, subtomogram averaging and AlphaFold2 structure prediction. We showed that the palisade is composed of densely packed trimers of the major core protein A10. Trimers display a random order and their classification indicates structural flexibility. A10 on cytoplasmic cores is organized in a similar manner, indicating that the structures obtained in vitro are physiologically relevant. We discuss our results in the context of the VACV replicative cycle, and the assembly and disassembly of the infectious MV.

Exploring conformational landscapes and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variant complexes with the ACE2 receptor using AlphaFold2-based structural ensembles and molecular dynamics simulations

In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles evolution and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamics (MD) simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and MD simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and MD simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.

Role of N343 glycosylation on the SARS-CoV-2 S RBD structure and co-receptor binding across variants of concern

Glycosylation of the SARS-CoV-2 spike (S) protein represents a key target for viral evolution because it affects both viral evasion and fitness. Successful variations in the glycan shield are difficult to achieve though, as protein glycosylation is also critical to folding and structural stability. Within this framework, the identification of glycosylation sites that are structurally dispensable can provide insight into the evolutionary mechanisms of the shield and inform immune surveillance. In this work, we show through over 45 μs of cumulative sampling from conventional and enhanced molecular dynamics (MD) simulations, how the structure of the immunodominant S receptor binding domain (RBD) is regulated by N-glycosylation at N343 and how this glycan's structural role changes from WHu-1, alpha (B.1.1.7), and beta (B.1.351), to the delta (B.1.617.2), and omicron (BA.1 and BA.2.86) variants. More specifically, we find that the amphipathic nature of the N-glycan is instrumental to preserve the structural integrity of the RBD hydrophobic core and that loss of glycosylation at N343 triggers a specific and consistent conformational change. We show how this change allosterically regulates the conformation of the receptor binding motif (RBM) in the WHu-1, alpha, and beta RBDs, but not in the delta and omicron variants, due to mutations that reinforce the RBD architecture. In support of these findings, we show that the binding of the RBD to monosialylated ganglioside co-receptors is highly dependent on N343 glycosylation in the WHu-1, but not in the delta RBD, and that affinity changes significantly across VoCs. Ultimately, the molecular and functional insight we provide in this work reinforces our understanding of the role of glycosylation in protein structure and function and it also allows us to identify the structural constraints within which the glycosylation site at N343 can become a hotspot for mutations in the SARS-CoV-2 S glycan shield.

Reconstruction of the real 3D shape of the SARS-CoV-2 virus

The photographs of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus taken by electron transmission microscopy and cryoelectron microscopy provide only a 2D silhouette. The viruses appear to look like distorted circles. The present paper questions the real shape of the SARS-CoV-2 virus and makes an attempt to give an answer. Is this a general ellipsoid, a spheroid with rotational symmetry, a sphere, or something else? The answer requires the application of tools from three different disciplines: structural mechanics, microbiology, and statistics. A total of 590 virus photographs taken from 22 recently published papers were examined. From this experimental data pool, the histogram of diameter ratios was built from the 283 measurements where the virus images could be approximated as ellipses. The curve peaks at the diameter ratio of 1.22. The transformation equation for the spatial shape to the planar shade was derived for a fixed light source of the microscope. This equation involves an unknown orientation of the viruses with respect to the microscope. Two sets of models were developed, one with a uniform distribution of the virus orientation and the other with the orientation defined by the normalized beta distribution. In both sets of models, the unknown diameter ratio of the spheroidal virus was regarded as a random realization from translated gamma distributions. The parameters of the distribution of the kernel functions were determined by minimizing the mean square difference between the predicted and measured 2D histograms. The information included in the measured histograms was found to be insufficient to find an unknown distribution of the virus's orientation. Simply too many unknown parameters render the solution physically unrealistic. The minimization procedure with a uniform probability of virus orientation predicted the peak of the aspect ratio of the 3D spheroid at 1.32. Based on this result, models of the virus will be developed in the continuation of this research for a full dynamic analysis.

AlphaFold2 Predictions of Conformational Ensembles and Atomistic Simulations of the SARS-CoV-2 Spike XBB Lineages Reveal Epistatic Couplings between Convergent Mutational Hotspots that Control ACE2 Affinity

In this study, we combined AlphaFold-based atomistic structural modeling, microsecond molecular simulations, mutational profiling, and network analysis to characterize binding mechanisms of the SARS-CoV-2 spike protein with the host receptor ACE2 for a series of Omicron XBB variants including XBB.1.5, XBB.1.5+L455F, XBB.1.5+F456L, and XBB.1.5+L455F+F456L. AlphaFold-based structural and dynamic modeling of SARS-CoV-2 Spike XBB lineages can accurately predict the experimental structures and characterize conformational ensembles of the spike protein complexes with the ACE2. Microsecond molecular dynamics simulations identified important differences in the conformational landscapes and equilibrium ensembles of the XBB variants, suggesting that combining AlphaFold predictions of multiple conformations with molecular dynamics simulations can provide a complementary approach for the characterization of functional protein states and binding mechanisms. Using the ensemble-based mutational profiling of protein residues and physics-based rigorous calculations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of the Q493 hotspot in the synchronization of epistatic couplings between L455F and F456L mutations, providing a quantitative insight into the energetic determinants underlying binding differences between XBB lineages. We also proposed a network-based perturbation approach for mutational profiling of allosteric communications and uncovered the important relationships between allosteric centers mediating long-range communication and binding hotspots of epistatic couplings. The results of this study support a mechanism in which the binding mechanisms of the XBB variants may be determined by epistatic effects between convergent evolutionary hotspots that control ACE2 binding.

STOPGAP: an open-source package for template matching, subtomogram alignment and classification

Cryo-electron tomography (cryo-ET) enables molecular-resolution 3D imaging of complex biological specimens such as viral particles, cellular sections and, in some cases, whole cells. This enables the structural characterization of molecules in their near-native environments, without the need for purification or separation, thereby preserving biological information such as conformational states and spatial relationships between different molecular species. Subtomogram averaging is an image-processing workflow that allows users to leverage cryo-ET data to identify and localize target molecules, determine high-resolution structures of repeating molecular species and classify different conformational states. Here, STOPGAP, an open-source package for subtomogram averaging that is designed to provide users with fine control over each of these steps, is described. In providing detailed descriptions of the image-processing algorithms that STOPGAP uses, this manuscript is also intended to serve as a technical resource to users as well as for further community-driven software development.

Structural impact of a new spike Y170W mutation detected in early emerging SARS-CoV-2 Omicron variants in France

To assess the genetic characteristics of the early emerging SARS-CoV-2 Omicron variant strains, we retrospectively analyzed a collection of 150 nasopharyngeal samples taken from a series of outpatient cases tested positive by a referenced qRT-PCR assay during the reported period of Omicron variant emergence in December 2021, in northeastern region of France. Next Generation Sequencing (NGS) analysis of SARS-CoV-2 spike sequences revealed that only 3 (2 %) of these detected strains were Omicron variants, while 147 (98 %) were identified as previously described delta variants. Our phylogenetic analyzes of SARS-CoV-2 RNA genomes showed that these French early emerging Omicron variants may have originated from South Africa or India. In addition, whole viral genome sequences NGS comparison analyzes allowed us to identify an original and uncharacterized Y170W spike mutation that was weakly and transiently detected during the period of SARS-CoV-2 Omicron variant emergence in human populations. Molecular modeling and docking experiments indicated that this original mutated residue Y170W was neither directly involved in binding to the SARS-CoV-2 receptor ACE2 nor in interacting with known neutralizing antibody sites. However, this new mutation may be responsible for preventing the transition from the closed to the open Spike conformation, thus promoting the early emergence of the Omicron variant. Overall, these results underscore the epidemiological utility of a routine whole-genome viral NGS strategy that enables genotypic characterization of emerging or mutant SARS-CoV-2 variants, which could have significant implications for public health policy.

Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

Thinner is not always better: Optimizing cryo-lamellae for subtomogram averaging

Cryo-electron tomography (cryo-ET) is a powerful method to elucidate subcellular architecture and to structurally analyze biomolecules in situ by subtomogram averaging, yet data quality critically depends on specimen thickness. Cells that are too thick for transmission imaging can be thinned into lamellae by cryo-focused ion beam (cryo-FIB) milling. Despite being a crucial parameter directly affecting attainable resolution, optimal lamella thickness has not been systematically investigated nor the extent of structural damage caused by gallium ions used for FIB milling. We thus systematically determined how resolution is affected by these parameters. We find that ion-induced damage does not affect regions more than 30 nanometers from either lamella surface and that up to ~180-nanometer lamella thickness does not negatively affect resolution. This shows that there is no need to generate very thin lamellae and lamella thickness can be chosen such that it captures cellular features of interest, thereby opening cryo-ET also for studies of large complexes.

Ensemble-Based Mutational Profiling and Network Analysis of the SARS-CoV-2 Spike Omicron XBB Lineages for Interactions with the ACE2 Receptor and Antibodies: Cooperation of Binding Hotspots in Mediating Epistatic Couplings Underlies Binding Mechanism and Immune Escape

In this study, we performed a computational study of binding mechanisms for the SARS-CoV-2 spike Omicron XBB lineages with the host cell receptor ACE2 and a panel of diverse class one antibodies. The central objective of this investigation was to examine the molecular factors underlying epistatic couplings among convergent evolution hotspots that enable optimal balancing of ACE2 binding and antibody evasion for Omicron variants BA.1, BA2, BA.3, BA.4/BA.5, BQ.1.1, XBB.1, XBB.1.5, and XBB.1.5 + L455F/F456L. By combining evolutionary analysis, molecular dynamics simulations, and ensemble-based mutational scanning of spike protein residues in complexes with ACE2, we identified structural stability and binding affinity hotspots that are consistent with the results of biochemical studies. In agreement with the results of deep mutational scanning experiments, our quantitative analysis correctly reproduced strong and variant-specific epistatic effects in the XBB.1.5 and BA.2 variants. It was shown that Y453W and F456L mutations can enhance ACE2 binding when coupled with Q493 in XBB.1.5, while these mutations become destabilized when coupled with the R493 position in the BA.2 variant. The results provided a molecular rationale of the epistatic mechanism in Omicron variants, showing a central role of the Q493/R493 hotspot in modulating epistatic couplings between convergent mutational sites L455F and F456L in XBB lineages. The results of mutational scanning and binding analysis of the Omicron XBB spike variants with ACE2 receptors and a panel of class one antibodies provide a quantitative rationale for the experimental evidence that epistatic interactions of the physically proximal binding hotspots Y501, R498, Q493, L455F, and F456L can determine strong ACE2 binding, while convergent mutational sites F456L and F486P are instrumental in mediating broad antibody resistance. The study supports a mechanism in which the impact on ACE2 binding affinity is mediated through a small group of universal binding hotspots, while the effect of immune evasion could be more variant-dependent and modulated by convergent mutational sites in the conformationally adaptable spike regions.

Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations

In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles and binding mechanisms of convergent evolution for the SARS-CoV-2 Spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron Spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamic simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron Spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and molecular dynamics simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and molecular dynamics simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.

A Comparative Analysis of Innate Immune Responses and the Structural Characterization of Spike from SARS-CoV-2 Gamma Variants and Subvariants

The SARS-CoV-2 P.1 variant, responsible for an outbreak in Manaus, Brazil, is distinguished by 12 amino acid differences in the S protein, potentially increasing its ACE-2 affinity and immune evasion capability. We investigated the innate immune response of this variant compared to the original B.1 strain, particularly concerning cytokine production. Blood samples from three severe COVID-19 patients were analyzed post-infection with both strains. Results showed no significant difference in cytokine production of mononuclear cells and neutrophils for either variant. While B.1 had higher cytopathogenicity, neither showed viral replication in mononuclear cells. Structural analyses of the S protein highlighted physicochemical variations, which might be linked to the differences in infectivity between the strains. Our studies point to the increased infectivity of P.1 could stem from altered immunogenicity and receptor-binding affinity.

Label-Free Single Nanoparticle Identification and Characterization in Demanding Environment, Including Infectious Emergent Virus

Unknown particle screening-including virus and nanoparticles-are keys in medicine, industry, and also in water pollutant determination. Here, RYtov MIcroscopy for Nanoparticles Identification (RYMINI) is introduced, a staining-free, non-invasive, and non-destructive optical approach that is merging holographic label-free 3D tracking with high-sensitivity quantitative phase imaging into a compact optical setup. Dedicated to the identification and then characterization of single nano-object in solution, it is compatible with highly demanding environments, such as level 3 biological laboratories, with high resilience to external source of mechanical and optical noise. Metrological characterization is performed at the level of each single particle on both absorbing and transparent particles as well as on immature and infectious HIV, SARS-CoV-2 and extracellular vesicles in solution. The capability of RYMINI to determine the nature, concentration, size, complex refractive index and mass of each single particle without knowledge or model of the particles' response is demonstrated. The system surpasses 90% accuracy for automatic identification between dielectric/metallic/biological nanoparticles and ≈80% for intraclass chemical determination of metallic and dielectric. It falls down to 50-70% for type determination inside the biological nanoparticle's class.

Engineered mRNA Delivery Systems for Biomedical Applications

Messenger RNA (mRNA)-based therapeutic strategies have shown remarkable promise in preventing and treating a staggering range of diseases. Optimizing the structure and delivery system of engineered mRNA has greatly improved its stability, immunogenicity, and protein expression levels, which has led to a wider range of uses for mRNA therapeutics. Herein, a thorough analysis of the optimization strategies used in the structure of mRNA is first provided and delivery systems are described in great detail. Furthermore, the latest advancements in biomedical engineering for mRNA technology, including its applications in combatting infectious diseases, treating cancer, providing protein replacement therapy, conducting gene editing, and more, are summarized. Lastly, a perspective on forthcoming challenges and prospects concerning the advancement of mRNA therapeutics is offered. Despite these challenges, mRNA-based therapeutics remain promising, with the potential to revolutionize disease treatment and contribute to significant advancements in the biomedical field.

Elucidating the behavior of the SARS-CoV-2 virus surface at vapor-liquid interfaces using molecular dynamics simulation

Aerosols play a major role in the transmission of the SARS-CoV-2 virus. The behavior of the virus within aerosols is therefore of fundamental importance. On the surface of a SARS-CoV-2 virus, there are about 40 spike proteins, which each have a length of about 20 nm. They are glycosylated trimers, which are highly flexible, due to their structure. These spike proteins play a central role in the intrusion of the virus into human host cells and are, therefore, a focus of vaccine development. In this work, we have studied the behavior of spike proteins of the SARS-CoV-2 virus in the presence of a vapor-liquid interface by molecular dynamics (MD) simulations. Systematically, the behavior of the spike protein at different distances to a vapor-liquid interface were studied. The results reveal that the spike protein of the SARS-CoV-2 virus is repelled from the vapor-liquid interface and has a strong affinity to stay inside the bulk liquid phase. Therefore, the spike protein bends when a vapor-liquid interface approaches the top of the protein. This has important consequences for understanding the behavior of the virus during the dry-out of aerosol droplets.

SARS-CoV-2 Omicron XBB lineage spike structures, conformations, antigenicity, and receptor recognition

A recombinant lineage of the SARS-CoV-2 Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryo-EM structures of XBB.1.5, XBB.1.16, EG.5 and EG.5.1 spike (S) ectodomains to reveal reinforced 3-RBD-down receptor inaccessible closed states mediated by interprotomer receptor binding domain (RBD) interactions previously observed in BA.1 and BA.2. Improved XBB.1.5 and XBB.1.16 RBD stability compensated for stability loss caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. S1 subunit mutations had long-range impacts on conformation and epitope presentation in the S2 subunit. Our results reveal continued S protein evolution via simultaneous optimization of multiple parameters including stability, receptor binding and immune evasion, and the dramatic effects of relatively few residue substitutions in altering the S protein conformational landscape.

AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles, and Binding Energetics of the SARS-CoV-2 Omicron BA.2.86 Spike Protein with ACE2 Host Receptor and Antibodies: Compensatory Functional Effects of Binding Hotspots in Modulating Mechanisms of Receptor Binding and Immune Escape

The latest wave of SARS-CoV-2 Omicron variants displayed a growth advantage and increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with atomistic simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both the structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that the AlphaFold2-predicted structural ensemble of the BA.2.86 spike protein complex with ACE2 can accurately capture the main conformational states of the Omicron variant. Complementary to AlphaFold2 structural predictions, microsecond molecular dynamics simulations reveal the details of the conformational landscape and produced equilibrium ensembles of the BA.2.86 structures that are used to perform mutational scanning of spike residues and characterize structural stability and binding energy hotspots. The ensemble-based mutational profiling of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 revealed a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 convergent mutational hotspots R403K, F486P, and R493Q. To examine the immune evasion properties of BA.2.86 in atomistic detail, we performed structure-based mutational profiling of the spike protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against the BA.2.86 variant. The results revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have evolved to outcompete other Omicron subvariants by improving immune evasion while preserving binding affinity with ACE2 via through a compensatory effect of R493Q and F486P convergent mutational hotspots. This study demonstrated that an integrative approach combining AlphaFold2 predictions with complementary atomistic molecular dynamics simulations and robust ensemble-based mutational profiling of spike residues can enable accurate and comprehensive characterization of structure, dynamics, and binding mechanisms of newly emerging Omicron variants.

A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions

Electron tomography is an imaging technique that allows for the elucidation of three-dimensional structural information of biological specimens in a very general context, including cellular in situ observations. The approach starts by collecting a set of images at different projection directions by tilting the specimen stage inside the microscope. Therefore, a crucial preliminary step is to precisely define the acquisition geometry by aligning all the tilt images to a common reference. Errors introduced in this step will lead to the appearance of artifacts in the tomographic reconstruction, rendering them unsuitable for the sample study. Focusing on fiducial-based acquisition strategies, this work proposes a deep-learning algorithm to detect misalignment artifacts in tomographic reconstructions by analyzing the characteristics of these fiducial markers in the tomogram. In addition, we propose an algorithm designed to detect fiducial markers in the tomogram with which to feed the classification algorithm in case the alignment algorithm does not provide the location of the markers. This open-source software is available as part of the Xmipp software package inside of the Scipion framework, and also through the command-line in the standalone version of Xmipp.

Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries

Most membrane proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, shielding potentially large fractions of protein surface. High glycan conformational freedom hinders complete structural elucidation of glycoproteins. Computer simulations may be used to model glycosylated proteins but require hundreds of thousands of computing hours on supercomputers, thus limiting routine use. Here, we describe GlycoSHIELD, a reductionist method that can be implemented on personal computers to graft realistic ensembles of glycan conformers onto static protein structures in minutes. Using molecular dynamics simulation, small-angle X-ray scattering, cryoelectron microscopy, and mass spectrometry, we show that this open-access toolkit provides enhanced models of glycoprotein structures. Focusing on N-cadherin, human coronavirus spike proteins, and gamma-aminobutyric acid receptors, we show that GlycoSHIELD can shed light on the impact of glycans on the conformation and activity of complex glycoproteins.

Application of a Biomimetic Nanoparticle-Based Mock Virus to Determine SARS-CoV-2 Neutralizing Antibody Levels in Blood Samples Using a Lateral Flow Assay

The presence of neutralizing antibodies against SARS-CoV-2 in blood, acquired through previous infection or vaccination, is known to prevent the (re)occurrence of outbreaks unless the virus mutates. Therefore, the measurement of neutralizing antibodies constitutes an indispensable tool in assessing an individual's and a population's immunity against SARS-CoV-2. For this reason, we have developed an innovative lateral flow assay (LFA) capable of detecting blood-derived neutralizing antibodies using a biomimetic SARS-CoV-2 mock virus system. Here, functionalized gold nanoparticles (AuNPs) featuring the trimeric spike (S) protein at its surface imitate the virus's structure and are applied to monitor the presence and efficacy of neutralizing antibodies in blood samples. The detection principle relies on the interaction between mock virus and the immobilized angiotensin-converting enzyme 2 (ACE2) receptor, which is inhibited when neutralizing antibodies are present. To further enhance the sensitivity of our competitive assay and identify low titers of neutralizing antibodies, an additional mixing pad is embedded into the device to increase the interaction time between mock virus and neutralizing antibodies. The developed LFA is benchmarked against the WHO International Standard (21/338) and demonstrated reliable quantification of neutralizing antibodies that inhibit ACE2 binding events down to a detection limit of an antibody titer of 59 IU/mL. Additional validation using whole blood and plasma samples showed reproducible results and good comparability to a laboratory-based reference test, thus highlighting its applicability for point-of-care testing.

Integrating cellular electron microscopy with multimodal data to explore biology across space and time

Biology spans a continuum of length and time scales. Individual experimental methods only glimpse discrete pieces of this spectrum but can be combined to construct a more holistic view. In this Review, we detail the latest advancements in volume electron microscopy (vEM) and cryo-electron tomography (cryo-ET), which together can visualize biological complexity across scales from the organization of cells in large tissues to the molecular details inside native cellular environments. In addition, we discuss emerging methodologies for integrating three-dimensional electron microscopy (3DEM) imaging with multimodal data, including fluorescence microscopy, mass spectrometry, single-particle analysis, and AI-based structure prediction. This multifaceted approach fills gaps in the biological continuum, providing functional context, spatial organization, molecular identity, and native interactions. We conclude with a perspective on incorporating diverse data into computational simulations that further bridge and extend length scales while integrating the dimension of time.

Fluidization and Application of Carbon Nano Agglomerations

Carbon nanomaterials are unique with excellent functionality and diverse structures. However, agglomerated structures are commonly formed because of small-size effects and surface effects. Their hierarchical assembly into micro particles enables carbon nanomaterials to break the boundaries of classical Geldart particle classification before stable fluidization under gas-solid interactions. Currently, there are few systematic reports regarding the structural evolution and fluidization mechanism of carbon nano agglomerations. Based on existing research on carbon nanomaterials, this article reviews the fluidized structure control and fluidization principles of prototypical carbon nanotubes (CNTs) as well as their nanocomposites. The controlled agglomerate fluidization technology leads to the successful mass production of agglomerated and aligned CNTs. In addition, the self-similar agglomeration of individual ultralong CNTs and nanocomposites with silicon as model systems further exemplify the important role of surface structure and particle-fluid interactions. These emerging nano agglomerations have endowed classical fluidization technology with more innovations in advanced applications like energy storage, biomedical, and electronics. This review aims to provide insights into the connections between fluidization and carbon nanomaterials by highlighting their hierarchical structural evolution and the principle of agglomerated fluidization, expecting to showcase the vitality and connotation of fluidization science and technology in the new era.

Mechanisms of allostery at the viral surface through the eyes of molecular simulation

The outermost surface layer of any virus is formed by either a capsid shell or envelope. Such layers have traditionally been thought of as immovable structures, but it is becoming apparent that they cannot be viewed exclusively as static architectures protecting the viral genome. A limited number of proteins on the virion surface must perform a multitude of functions in order to orchestrate the viral life cycle, and allostery can regulate their structures at multiple levels of organization, spanning individual molecules, protomers, large oligomeric assemblies, or entire viral surfaces. Here, we review recent contributions from the molecular simulation field to viral surface allostery, with a particular focus on the trimeric spike glycoprotein emerging from the coronavirus surface, and the icosahedral flaviviral envelope complex. As emerging viral pathogens continue to pose a global threat, an improved understanding of viral dynamics and allosteric regulation will prove crucial in developing novel therapeutic strategies.

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.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

STOPGAP, an open-source package for template matching, subtomogram alignment, and classification

Cryo-electron tomography (cryo-ET) enables molecular-resolution 3D imaging of complex biological specimens such as viral particles, cellular sections, and in some cases, whole cells. This enables the structural characterization of molecules in their near-native environments, without the need for purification or separation, thereby preserving biological information such as conformational states and spatial relationships between different molecular species. Subtomogram averaging is an image processing workflow that allows users to leverage cryo-ET data to identify and localize target molecules, determine high-resolution structures of repeating molecular species, and classifying different conformational states. Here we describe STOPGAP, an open-source package for subtomogram averaging designed to provide users with fine control over each of these steps. In providing detailed descriptions of the image processing algorithms that STOPGAP uses, we intend for this manuscript to also serve as a technical resource to users as well as further community-driven software development.

Evolving spike-protein N-glycosylation in SARS-CoV-2 variants

Since >3 years, SARS-CoV-2 has plunged humans into a colossal pandemic. Henceforth, multiple waves of infection have swept through the human population, led by variants that were able to partially evade acquired immunity. The co-evolution of SARS-CoV-2 variants with human immunity provides an excellent opportunity to study the interaction between viral pathogens and their human hosts. The heavily N-glycosylated spike-protein of SARS-CoV-2 plays a pivotal role in initiating infection and is the target for host immune-response, both of which are impacted by host-installed N-glycans. Using highly-sensitive DeGlyPHER approach, we compared the N-glycan landscape on spikes of the SARS-CoV-2 Wuhan-Hu-1 strain to seven WHO-defined variants of concern/interest, using recombinantly expressed, soluble spike-protein trimers, sharing same stabilizing-mutations. We found that N-glycan processing is conserved at most sites. However, in multiple variants, processing of N-glycans from high mannose- to complex-type is reduced at sites N165, N343 and N616, implicated in spike-protein function.

Landscape of molecular crosstalk between SARS-CoV-2 infection and cardiovascular diseases: emphasis on mitochondrial dysfunction and immune-inflammation

BACKGROUND

SARS-CoV-2, the pathogen of COVID-19, is a worldwide threat to human health and causes a long-term burden on the cardiovascular system. Individuals with pre-existing cardiovascular diseases are at higher risk for SARS-CoV-2 infection and tend to have a worse prognosis. However, the relevance and pathogenic mechanisms between COVID-19 and cardiovascular diseases are not yet completely comprehended.

METHODS

Common differentially expressed genes (DEGs) were obtained in datasets of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) infected with SARS-CoV-2 and myocardial tissues from heart failure patients. Further GO and KEGG pathway analysis, protein-protein interaction (PPI) network construction, hub genes identification, immune microenvironment analysis, and drug candidate predication were performed. Then, an isoproterenol-stimulated myocardial hypertrophy cell model and a transverse aortic constriction-induced mouse heart failure model were employed to validate the expression of hub genes.

RESULTS

A total of 315 up-regulated and 78 down-regulated common DEGs were identified. Functional enrichment analysis revealed mitochondrial metabolic disorders and extensive immune inflammation as the most prominent shared features of COVID-19 and cardiovascular diseases. Then, hub DEGs, as well as hub immune-related and mitochondria-related DEGs, were screened. Additionally, nine potential therapeutic agents for COVID-19-related cardiovascular diseases were proposed. Furthermore, the expression patterns of most of the hub genes related to cardiovascular diseases in the validation dataset along with cellular and mouse myocardial damage models, were consistent with the findings of bioinformatics analysis.

CONCLUSIONS

The study unveiled the molecular networks and signaling pathways connecting COVID-19 and cardiovascular diseases, which may provide novel targets for intervention of COVID-19-related cardiovascular diseases.

AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance

In this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.

Antibody-mediated SARS-CoV-2 entry in cultured cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells by first engaging its cellular receptor angiotensin converting enzyme 2 (ACE2) to induce conformational changes in the virus-encoded spike protein and fusion between the viral and target cell membranes. Here, we report that certain monoclonal neutralizing antibodies against distinct epitopic regions of the receptor-binding domain of the spike can replace ACE2 to serve as a receptor and efficiently support membrane fusion and viral infectivity in vitro. These receptor-like antibodies can function in the form of a complex of their soluble immunoglobulin G with Fc-gamma receptor I, a chimera of their antigen-binding fragment with the transmembrane domain of ACE2 or a membrane-bound B cell receptor, indicating that ACE2 and its specific interaction with the spike protein are dispensable for SARS-CoV-2 entry. These results suggest that antibody responses against SARS-CoV-2 may help expand the viral tropism to otherwise nonpermissive cell types with potential implications for viral transmission and pathogenesis.

Accurate Characterization of Conformational Ensembles and Binding Mechanisms of the SARS-CoV-2 Omicron BA.2 and BA.2.86 Spike Protein with the Host Receptor and Distinct Classes of Antibodies Using AlphaFold2-Augmented Integrative Computational Modeling

The latest wave SARS-CoV-2 Omicron variants displayed a growth advantage and the increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with all-atom MD simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that AlphaFold2-predicted conformational ensemble of the BA.2.86 spike protein complex can accurately capture the main dynamics signatures obtained from microscond molecular dynamics simulations. The ensemble-based dynamic mutational scanning of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 dissected the role of the BA.2 and BA.2.86 backgrounds in modulating binding free energy changes revealing a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 mutational sites R403K, F486P and R493Q. To examine immune evasion properties of BA.2.86 in atomistic detail, we performed large scale structure-based mutational profiling of the S protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against BA.2.86 variant. The results quantified specific function of the BA.2.86 mutations to ensure broad resistance against different classes of RBD antibodies. This study revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have primarily evolved to improve immune escape while modulating binding affinity with ACE2 through cooperative effect of R403K, F486P and R493Q mutations. The study supports a hypothesis that the impact of the increased ACE2 binding affinity on viral fitness is more universal and is mediated through cross-talk between convergent mutational hotspots, while the effect of immune evasion could be more variant-dependent.

Inconspicuous Yet Indispensable: The Coronavirus Spike Transmembrane Domain

Membrane-spanning portions of proteins' polypeptide chains are commonly known as their transmembrane domains (TMDs). The structural organisation and dynamic behaviour of TMDs from proteins of various families, be that receptors, ion channels, enzymes etc., have been under scrutiny on the part of the scientific community for the last few decades. The reason for such attention is that, apart from their obvious role as an "anchor" in ensuring the correct orientation of the protein's extra-membrane domains (in most cases functionally important), TMDs often actively and directly contribute to the operation of "the protein machine". They are capable of transmitting signals across the membrane, interacting with adjacent TMDs and membrane-proximal domains, as well as with various ligands, etc. Structural data on TMD arrangement are still fragmentary at best due to their complex molecular organisation as, most commonly, dynamic oligomers, as well as due to the challenges related to experimental studies thereof. Inter alia, this is especially true for viral fusion proteins, which have been the focus of numerous studies for quite some time, but have provoked unprecedented interest in view of the SARS-CoV-2 pandemic. However, despite numerous structure-centred studies of the spike (S) protein effectuating target cell entry in coronaviruses, structural data on the TMD as part of the entire spike protein are still incomplete, whereas this segment is known to be crucial to the spike's fusogenic activity. Therefore, in attempting to bring together currently available data on the structure and dynamics of spike proteins' TMDs, the present review aims to tackle a highly pertinent task and contribute to a better understanding of the molecular mechanisms underlying virus-mediated fusion, also offering a rationale for the design of novel efficacious methods for the treatment of infectious diseases caused by SARS-CoV-2 and related viruses.

Conventional Understanding of SARS-CoV-2 Mpro and Common Strategies for Developing Its Inhibitors

The Coronavirus Disease 2019 (COVID-19) pandemic has brought a widespread influence on the world, especially in the face of sudden coronavirus infections, and there is still an urgent need for specific small molecule therapies to cope with possible future pandemics. The pathogen responsible for this pandemic is Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and understanding its structure and lifecycle is beneficial for designing specific drugs of treatment for COVID-19. The main protease (Mpro ) which has conservative and specific advantages is essential for viral replication and transcription. It is regarded as one of the most potential targets for anti-SARS-CoV-2 drug development. This review introduces the popular knowledge of SARS-CoV-2 Mpro in drug development and lists a series of design principles and relevant activities of advanced Mpro inhibitors, hoping to provide some new directions and ideas for researchers.

Multi-omic analysis characterizes molecular susceptibility of receptors to SARS-CoV-2 spike protein

In the post COVID-19 era, new SARS-CoV-2 variant strains may continue emerging and long COVID is poised to be another public health challenge. Deciphering the molecular susceptibility of receptors to SARS-CoV-2 spike protein is critical for understanding the immune responses in COVID-19 and the rationale of multi-organ injuries. Currently, such systematic exploration remains limited. Here, we conduct multi-omic analysis of protein binding affinities, transcriptomic expressions, and single-cell atlases to characterize the molecular susceptibility of receptors to SARS-CoV-2 spike protein. Initial affinity analysis explains the domination of delta and omicron variants and demonstrates the strongest affinities between BSG (CD147) receptor and most variants. Further transcriptomic data analysis on 4100 experimental samples and single-cell atlases of 1.4 million cells suggest the potential involvement of BSG in multi-organ injuries and long COVID, and explain the high prevalence of COVID-19 in elders as well as the different risks for patients with underlying diseases. Correlation analysis validated moderate associations between BSG and viral RNA abundance in multiple cell types. Moreover, similar patterns were observed in primates and validated in proteomic expressions. Overall, our findings implicate important therapeutic targets for the development of receptor-specific vaccines and drugs for COVID-19.

Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics

All protein simulations are conducted with varying degrees of simplification, oftentimes with unknown ramifications about how these simplifications affect the interpretability of the results. In this work, we investigated how protein glycosylation and lateral crowding effects modulate an array of properties characterizing the stability and dynamics of influenza neuraminidase. We constructed three systems: (1) glycosylated neuraminidase in a whole virion (i.e., crowded membrane) environment, (2) glycosylated neuraminidase in its own lipid bilayer, and (3) unglycosylated neuraminidase in its own lipid bilayer. We saw that glycans tend to stabilize the protein structure and reduce its conformational flexibility while restricting the solvent movement. Conversely, a crowded membrane environment encouraged exploration of the free energy landscape and a large-scale conformational change, while making the protein structure more compact. Understanding these effects informs what factors one must consider in attempting to recapture the desired level of physical accuracy.

Conformational plasticity and allosteric communication networks explain Shelterin protein TPP1 binding to human telomerase

The Shelterin complex protein TPP1 interacts with human telomerase (TERT) by means of the TEL-patch region, controlling telomere homeostasis. Aberrations in the TPP1-TERT heterodimer formation might lead to short telomeres and severe diseases like dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome. In the present study, we provide a thorough characterization of the structural properties of the TPP1's OB-domain by combining data coming from microsecond-long molecular dynamics calculations, time-series analyses, and graph-based networks. Our results show that the TEL-patch conformational freedom is influenced by a network of long-range amino acid communications that together determine the proper TPP1-TERT binding. Furthermore, we reveal that in TPP1 pathological variants Glu169Δ, Lys170Δ and Leu95Gln, the TEL-patch plasticity is reduced, affecting the correct binding to TERT and, in turn, telomere processivity, which eventually leads to accelerated aging of affected cells. Our study provides a structural basis for the design of TPP1-targeting ligands with therapeutic potential against cancer and telomeropathies.

Structural insights into the modulation of coronavirus spike tilting and infectivity by hinge glycans

Coronavirus spike glycoproteins presented on the virion surface mediate receptor binding, and membrane fusion during virus entry and constitute the primary target for vaccine and drug development. How the structure dynamics of the full-length spikes incorporated in viral lipid envelope correlates with the virus infectivity remains poorly understood. Here we present structures and distributions of native spike conformations on vitrified human coronavirus NL63 (HCoV-NL63) virions without chemical fixation by cryogenic electron tomography (cryoET) and subtomogram averaging, along with site-specific glycan composition and occupancy determined by mass spectrometry. The higher oligomannose glycan shield on HCoV-NL63 spikes than on SARS-CoV-2 spikes correlates with stronger immune evasion of HCoV-NL63. Incorporation of cryoET-derived native spike conformations into all-atom molecular dynamic simulations elucidate the conformational landscape of the glycosylated, full-length spike that reveals a role of hinge glycans in modulating spike bending. We show that glycosylation at N1242 at the upper portion of the stalk is responsible for the extensive orientational freedom of the spike crown. Subsequent infectivity assays implicated involvement of N1242-glyan in virus entry. Our results suggest a potential therapeutic target site for HCoV-NL63.