Structural dynamics in the evolution of SARS-CoV-2 spike glycoprotein

Water-glycan interactions drive the SARS-CoV-2 spike dynamics: insights into glycan-gate control and camouflage mechanisms

To develop therapeutic strategies against COVID-19, we introduce a high-resolution all-atom polarizable model capturing many-body effects of protein, glycan, solvent, and membrane components in SARS-CoV-2 spike protein open and closed states. Employing μs-long molecular dynamics simulations powered by high-performance cloud-computing and unsupervised density-driven adaptive sampling, we investigated the differences in bulk-solvent-glycan and protein-solvent-glycan interfaces between these states. We unraveled a sophisticated solvent-glycan polarization interaction network involving the N165/N343 glycan-gate patterns that provide structural support for the open state and identified key water molecules that could potentially be targeted to destabilize this configuration. In the closed state, the reduced solvent polarization diminishes the overall N165/N343 dipoles, yet internal interactions and a reorganized sugar coat stabilize this state. Despite variations, our glycan-solvent accessibility analysis reveals the glycan shield capability to conserve constant interactions with the solvent, effectively camouflaging the virus from immune detection in both states. The presented insights advance our comprehension of viral pathogenesis at an atomic level, offering potential to combat COVID-19.

Significance of Artificial Intelligence in the Study of Virus-Host Cell Interactions

A highly critical event in a virus's life cycle is successfully entering a given host. This process begins when a viral glycoprotein interacts with a target cell receptor, which provides the molecular basis for target virus-host cell interactions for novel drug discovery. Over the years, extensive research has been carried out in the field of virus-host cell interaction, generating a massive number of genetic and molecular data sources. These datasets are an asset for predicting virus-host interactions at the molecular level using machine learning (ML), a subset of artificial intelligence (AI). In this direction, ML tools are now being applied to recognize patterns in these massive datasets to predict critical interactions between virus and host cells at the protein-protein and protein-sugar levels, as well as to perform transcriptional and translational analysis. On the other end, deep learning (DL) algorithms-a subfield of ML-can extract high-level features from very large datasets to recognize the hidden patterns within genomic sequences and images to develop models for rapid drug discovery predictions that address pathogenic viruses displaying heightened affinity for receptor docking and enhanced cell entry. ML and DL are pivotal forces, driving innovation with their ability to perform analysis of enormous datasets in a highly efficient, cost-effective, accurate, and high-throughput manner. This review focuses on the complexity of virus-host cell interactions at the molecular level in light of the current advances of ML and AI in viral pathogenesis to improve new treatments and prevention strategies.

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.

New Strategies for Responding to SARS-CoV-2: The Present and Future of Dual-Target Drugs

The 2019 coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in millions of deaths, posing a serious threat to public health and safety. Rapid mutations of SARS-CoV-2 and complex interactions among multiple targets during infection pose a risk of expiry for small molecule inhibitors. This suggests that the traditional concept of "one bug, one drug" could be ineffective in dealing with the coronavirus. The dual-target drug strategy is expected to be the key to ending coronavirus infections. However, the lack of design method and improper combination of dual-targets poses obstacle to the discovery of new dual-target drugs. In this Perspective, we summarized the profiles concerning drug design methods, structure-activity relationships, and pharmacological parameters of dual-target drugs for the treatment of COVID-19. Importantly, we underscored how target combination and rational drug design illuminate the development of dual-target drugs for SARS-CoV-2.

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.

Epitopes of an antibody that neutralizes a wide range of SARS-CoV-2 variants in a conserved subdomain 1 of the spike protein

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued, enabling the virus to escape from host immunity by changing its spike antigen, while biased toward the receptor-binding domain and N-terminal domain. Here, we isolated a novel pan-SARS-CoV-2 neutralizing antibody (which we named MO11) for even the recent dominators XBB.1.16 and EG.5.1, from a convalescent patient who had received three doses of an original mRNA COVID-19 vaccination. A cryo-electron microscopy analysis of the spike-MO11 complex at 2.3 Å atomic resolution revealed that it recognizes a conserved epitope hidden behind a glycan shield at N331 on subdomain 1 (SD1), holding both the N- and C-terminal segments comprising SD1. Our identification of MO11 unveiled the functional importance of SD1 for the spike's function, and we discuss the potential availability of a novel common epitope among the SARS-CoV-2 variants.IMPORTANCENovel severe acute respiratory syndrome coronavirus 2 variants with immune evasion ability are still repeatedly emerging, nonetheless, a part of immunity developed in responding to the antigen of earlier variants retains efficacy against recent variants irrespective of the numerous mutations. In exploration for the broadly effective antibodies, we identified a cross-neutralizing antibody, named MO11, from the B cells of the convalescent patient. MO11 targets a novel epitope in subdomain 1 (SD1) and was effective against all emerging variants including XBB.1.16 and EG.5.1. The neutralizing activity covering from D614G to EG.5.1 variants was explained by the conservation of the epitope, and it revealed the importance of the subdomain on regulating the function of the antigen for viral infection. Demonstrated identification of the neutralizing antibody that recognizes a conserved epitope implies basal contribution of such group of antibodies for prophylaxis against COVID-19.

Variation in structural motifs within SARS-related coronavirus spike proteins

SARS-CoV-2 is the third known coronavirus (CoV) that has crossed the animal-human barrier in the last two decades. However, little structural information exists related to the close genetic species within the SARS-related coronaviruses. Here, we present three novel SARS-related CoV spike protein structures solved by single particle cryo-electron microscopy analysis derived from bat (bat SL-CoV WIV1) and civet (cCoV-SZ3, cCoV-007) hosts. We report complex glycan trees that decorate the glycoproteins and density for water molecules which facilitated modeling of the water molecule coordination networks within structurally important regions. We note structural conservation of the fatty acid binding pocket and presence of a linoleic acid molecule which are associated with stabilization of the receptor binding domains in the "down" conformation. Additionally, the N-terminal biliverdin binding pocket is occupied by a density in all the structures. Finally, we analyzed structural differences in a loop of the receptor binding motif between coronaviruses known to infect humans and the animal coronaviruses described in this study, which regulate binding to the human angiotensin converting enzyme 2 receptor. This study offers a structural framework to evaluate the close relatives of SARS-CoV-2, the ability to inform pandemic prevention, and aid in the development of pan-neutralizing treatments.

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.

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.

Vero cell-adapted SARS-CoV-2 strain shows increased viral growth through furin-mediated efficient spike cleavage

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes several host proteases to cleave the spike (S) protein to enter host cells. SARS-CoV-2 S protein is cleaved into S1 and S2 subunits by furin, which is closely involved in the pathogenicity of SARS-CoV-2. However, the effects of the modulated protease cleavage activity due to S protein mutations on viral replication and pathogenesis remain unclear. Herein, we serially passaged two SARS-CoV-2 strains in Vero cells and characterized the cell-adapted SARS-CoV-2 strains in vitro and in vivo. The adapted strains showed high viral growth, effective S1/S2 cleavage of the S protein, and low pathogenicity compared with the wild-type strain. Furthermore, the viral growth and S1/S2 cleavage were enhanced by the combination of the Δ68-76 and H655Y mutations using recombinant SARS-CoV-2 strains generated by the circular polymerase extension reaction. The recombinant SARS-CoV-2 strain, which contained the mutation of the adapted strain, showed increased susceptibility to the furin inhibitor, suggesting that the adapted SARS-CoV-2 strain utilized furin more effectively than the wild-type strain. Pathogenicity was attenuated by infection with effectively cleaved recombinant SARS-CoV-2 strains, suggesting that the excessive cleavage of the S proteins decreases virulence. Finally, the high-growth-adapted SARS-CoV-2 strain could be used as the seed for a low-cost inactivated vaccine; immunization with this vaccine can effectively protect the host from SARS-CoV-2 variants. Our findings provide novel insights into the growth and pathogenicity of SARS-CoV-2 in the evolution of cell-cell transmission.

IMPORTANCE

The efficacy of the S protein cleavage generally differs among the SARS-CoV-2 variants, resulting in distinct viral characteristics. The relationship between a mutation and the entry of SARS-CoV-2 into host cells remains unclear. In this study, we analyzed the sequence of high-growth Vero cell-adapted SARS-CoV-2 and factors determining the enhancement of the growth of the adapted virus and confirmed the characteristics of the adapted strain by analyzing the recombinant SARS-CoV-2 strain. We successfully identified mutations Δ68-76 and H655Y, which enhance viral growth and the S protein cleavage by furin. Using recombinant viruses enabled us to conduct a virus challenge experiment in vivo. The pathogenicity of SARS-CoV-2 introduced with the mutations Δ68-76, H655Y, P812L, and Q853L was attenuated in hamsters, indicating the possibility of the attenuation of excessive cleaved SARS-CoV-2. These findings provide novel insights into the infectivity and pathogenesis of SARS-CoV-2 strains, thereby significantly contributing to the field of virology.

Functional assessment of cell entry and receptor use for merbecoviruses

The merbecovirus subgenus of coronaviruses includes Middle East Respiratory Syndrome Coronavirus (MERS-CoV), which is a zoonotic respiratory pathogen that transmits from dromedary camels to humans and causes severe respiratory disease. Viral discovery efforts have uncovered hundreds of merbecoviruses in different species across multiple continents, but few of these viruses have been isolated or studied under laboratory conditions, leaving basic questions regarding their threat to humans unresolved. Viral entry into host cells is considered an early and critical step for transmission between hosts. In this study, a scalable approach to assessing novel merbecovirus cell entry was developed and used to measure receptor use across the entire merbecovirus subgenus. Merbecoviruses are sorted into four clades based on the receptor binding domain of the spike glycoprotein. Receptor tropism is clade-specific, with only one clade using DPP4 and multiple clades using ACE2, including the entire HKU5 cluster of bat coronaviruses.

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.

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.

Defining neutralization and allostery by antibodies against COVID-19 variants

The changing landscape of SARS-CoV-2 Spike protein is linked to the emergence of variants, immune-escape and reduced efficacy of the existing repertoire of anti-viral antibodies. The functional activity of neutralizing antibodies is linked to their quaternary changes occurring as a result of antibody-Spike trimer interactions. Here, we reveal the conformational dynamics and allosteric perturbations linked to binding of novel human antibodies and the viral Spike protein. We identified epitope hotspots, and associated changes in Spike dynamics that distinguish weak, moderate and strong neutralizing antibodies. We show the impact of mutations in Wuhan-Hu-1, Delta, and Omicron variants on differences in the antibody-induced conformational changes in Spike and illustrate how these render certain antibodies ineffective. Antibodies with similar binding affinities may induce destabilizing or stabilizing allosteric effects on Spike, with implications for neutralization efficacy. Our results provide mechanistic insights into the functional modes and synergistic behavior of human antibodies against COVID-19 and may assist in designing effective antiviral strategies.

Comparative Analysis of Conformational Dynamics and Systematic Characterization of Cryptic Pockets in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 Spike Complexes with the ACE2 Host Receptor: Confluence of Binding and Structural Plasticity in Mediating Networks of Conserved Allosteric Sites

In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full-length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results are significant for understanding the functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.

Exploring Conformational Landscapes and Cryptic Binding Pockets in Distinct Functional States of the SARS-CoV-2 Omicron BA.1 and BA.2 Trimers: Mutation-Induced Modulation of Protein Dynamics and Network-Guided Prediction of Variant-Specific Allosteric Binding Sites

A significant body of experimental structures of SARS-CoV-2 spike trimers for the BA.1 and BA.2 variants revealed a considerable plasticity of the spike protein and the emergence of druggable binding pockets. Understanding the interplay of conformational dynamics changes induced by the Omicron variants and the identification of cryptic dynamic binding pockets in the S protein is of paramount importance as exploring broad-spectrum antiviral agents to combat the emerging variants is imperative. In the current study, we explore conformational landscapes and characterize the universe of binding pockets in multiple open and closed functional spike states of the BA.1 and BA.2 Omicron variants. By using a combination of atomistic simulations, a dynamics network analysis, and an allostery-guided network screening of binding pockets in the conformational ensembles of the BA.1 and BA.2 spike conformations, we identified all experimentally known allosteric sites and discovered significant variant-specific differences in the distribution of binding sites in the BA.1 and BA.2 trimers. This study provided a structural characterization of the predicted cryptic pockets and captured the experimentally known allosteric sites, revealing the critical role of conformational plasticity in modulating the distribution and cross-talk between functional binding sites. We found that mutational and dynamic changes in the BA.1 variant can induce the remodeling and stabilization of a known druggable pocket in the N-terminal domain, while this pocket is drastically altered and may no longer be available for ligand binding in the BA.2 variant. Our results predicted the experimentally known allosteric site in the receptor-binding domain that remains stable and ranks as the most favorable site in the conformational ensembles of the BA.2 variant but could become fragmented and less probable in BA.1 conformations. We also uncovered several cryptic pockets formed at the inter-domain and inter-protomer interface, including functional regions of the S2 subunit and stem helix region, which are consistent with the known role of pocket residues in modulating conformational transitions and antibody recognition. The results of this study are particularly significant for understanding the dynamic and network features of the universe of available binding pockets in spike proteins, as well as the effects of the Omicron-variant-specific modulation of preferential druggable pockets. The exploration of predicted druggable sites can present a new and previously underappreciated opportunity for therapeutic interventions for Omicron variants through the conformation-selective and variant-specific targeting of functional sites involved in allosteric changes.

Examining Functional Linkages Between Conformational Dynamics, Protein Stability and Evolution of Cryptic Binding Pockets in the SARS-CoV-2 Omicron Spike Complexes with the ACE2 Host Receptor: Recombinant Omicron Variants Mediate Variability of Conserved Allosteric Sites and Binding Epitopes

In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results of are significant for understanding functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.

TMEM106B is a receptor mediating ACE2-independent SARS-CoV-2 cell entry

SARS-CoV-2 is associated with broad tissue tropism, a characteristic often determined by the availability of entry receptors on host cells. Here, we show that TMEM106B, a lysosomal transmembrane protein, can serve as an alternative receptor for SARS-CoV-2 entry into angiotensin-converting enzyme 2 (ACE2)-negative cells. Spike substitution E484D increased TMEM106B binding, thereby enhancing TMEM106B-mediated entry. TMEM106B-specific monoclonal antibodies blocked SARS-CoV-2 infection, demonstrating a role of TMEM106B in viral entry. Using X-ray crystallography, cryogenic electron microscopy (cryo-EM), and hydrogen-deuterium exchange mass spectrometry (HDX-MS), we show that the luminal domain (LD) of TMEM106B engages the receptor-binding motif of SARS-CoV-2 spike. Finally, we show that TMEM106B promotes spike-mediated syncytium formation, suggesting a role of TMEM106B in viral fusion. Together, our findings identify an ACE2-independent SARS-CoV-2 infection mechanism that involves cooperative interactions with the receptors heparan sulfate and TMEM106B.

Mechanism and evolution of human ACE2 binding by SARS-CoV-2 spike

Spike glycoprotein of SARS-CoV-2 mediates viral entry into host cells by facilitating virus attachment and membrane fusion. ACE2 is the main receptor of SARS-CoV-2 and its interaction with spike has shaped the virus' emergence from an animal reservoir and subsequent evolution in the human host. Many structural studies on the spike:ACE2 interaction have provided insights into mechanisms driving viral evolution during the on-going pandemic. This review describes the molecular basis of spike binding to ACE2, outlines mechanisms that have optimised this interaction during viral evolution, and suggests directions for future research.

The effects of amino acid substitution of spike protein and genomic recombination on the evolution of SARS-CoV-2

Over three years' pandemic of 2019 novel coronavirus disease (COVID-19), multiple variants and novel subvariants have emerged successively, outcompeted earlier variants and become predominant. The sequential emergence of variants reflects the evolutionary process of mutation-selection-adaption of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Amino acid substitution/insertion/deletion in the spike protein causes altered viral antigenicity, transmissibility, and pathogenicity of SARS-CoV-2. Early in the pandemic, D614G mutation conferred virus with advantages over previous variants and increased transmissibility, and it also laid a conservative background for subsequent substantial mutations. The role of genomic recombination in the evolution of SARS-CoV-2 raised increasing concern with the occurrence of novel recombinants such as Deltacron, XBB.1.5, XBB.1.9.1, and XBB.1.16 in the late phase of pandemic. Co-circulation of different variants and co-infection in immunocompromised patients accelerate the emergence of recombinants. Surveillance for SARS-CoV-2 genomic variations, particularly spike protein mutation and recombination, is essential to identify ongoing changes in the viral genome and antigenic epitopes and thus leads to the development of new vaccine strategies and interventions.

hACE2-Induced Allosteric Activation in SARS-CoV versus SARS-CoV-2 Spike Assemblies Revealed by Structural Dynamics

SARS-CoV and SARS-CoV-2 cell entry begins when spike glycoprotein (S) docks with the human ACE2 (hACE2) receptor. While the two coronaviruses share a common receptor and architecture of S, they exhibit differences in interactions with hACE2 as well as differences in proteolytic processing of S that trigger the fusion machine. Understanding how those differences impact S activation is key to understand its function and viral pathogenesis. Here, we investigate hACE2-induced activation in SARS-CoV and SARS-CoV-2 S using hydrogen/deuterium-exchange mass spectrometry (HDX-MS). HDX-MS revealed differences in dynamics in unbound S, including open/closed conformational switching and D614G-induced S stability. Upon hACE2 binding, notable differences in transduction of allosteric changes were observed extending from the receptor binding domain to regions proximal to proteolytic cleavage sites and the fusion peptide. Furthermore, we report that dimeric hACE2, the native oligomeric form of the receptor, does not lead to any more pronounced structural effect in S compared to saturated monomeric hACE2 binding. These experiments provide mechanistic insights into receptor-induced activation of Sarbecovirus spike proteins.

Immune interference in effectiveness of influenza and COVID-19 vaccination

Vaccines are known to function as the most effective interventional therapeutics for controlling infectious diseases, including polio, smallpox, rabies, tuberculosis, influenza and SARS-CoV-2. Smallpox has been eliminated completely and polio is almost extinct because of vaccines. Rabies vaccines and Bacille Calmette-Guérin (BCG) vaccines could effectively protect humans against respective infections. However, both influenza vaccines and COVID-19 vaccines are unable to eliminate these two infectious diseases of their highly variable antigenic sites in viral proteins. Vaccine effectiveness (VE) could be negatively influenced (i.e., interfered with) by immune imprinting of previous infections or vaccinations, and repeated vaccinations could interfere with VE against infections due to mismatch between vaccine strains and endemic viral strains. Moreover, VE could also be interfered with when more than one kind of vaccine is administrated concomitantly (i.e., co-administrated), suggesting that the VE could be modulated by the vaccine-induced immunity. In this review, we revisit the evidence that support the interfered VE result from immune imprinting or repeated vaccinations in influenza and COVID-19 vaccine, and the interference in co-administration of these two types of vaccines is also discussed. Regarding the development of next-generation COVID-19 vaccines, the researchers should focus on the induction of cross-reactive T-cell responses and naive B-cell responses to overcome negative effects from the immune system itself. The strategy of co-administrating influenza and COVID-19 vaccine needs to be considered more carefully and more clinical data is needed to verify this strategy to be safe and immunogenic.