Determination of intermediate state structures in the opening pathway of SARS-CoV-2 spike using cryo-electron microscopy

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.

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.

Two-Stage Recognition Mechanism of the SARS-CoV-2 Receptor-Binding Domain to Angiotensin-Converting Enzyme-2 (ACE2)

The SARS-CoV-2 virus, commonly known as COVID-19, occurred in 2019. It is a highly contagious illness with effects ranging from mild symptoms to severe illness. It is also one of the best-known pathogens since more than 200,000 scientific papers occurred in the last few years. With the publication of the SARS-CoV-2 (SARS-CoV-2-CTD) spike (S) protein in a complex with human ACE2 (hACE2) (PDB (6LZG)), the molecular analysis of one of the most crucial steps on the infection pathway was possible. The aim of this manuscript is to simulate the most widely spread mutants of SARS-CoV-2, namely Alpha, Beta, Gamma, Delta, Omicron, and the first recognized variant (natural wild type). With the wide search of the hypersurface of the potential energy performed using the UNRES force field, the intermediate state of the ACE2-RBD complex was found. R403, K/N/T417, L455, F486, Y489, F495, Y501, and Y505 played a crucial role in the protein recognition mechanism. The intermediate state cannot be very stable since it will prevent the infection cascade.

Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules

The electron microscopy metainference integrative structural biology method enables the combination of cryo-electron microscopy electron density maps with molecular modeling techniques such as molecular dynamics to unveil the atomistic biomolecular structural ensemble and the error in the map data in an efficient manner. Here we illustrate the electron microscopy metainference protocol and analysis used to elucidate the atomistic structural ensemble of the microtubule-associated protein tau bound to microtubules by using state-of-the-art molecular mechanic force field and the electron density map.

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.

Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-β structure of amyloid fibrils.

The SARS-CoV-2 spike protein structure: a symmetry tale on distortion trail

A preliminary step in the SARS-CoV-2 human infection process is a conformational change of the receptor binding domain (RBD) of its spike protein, characterized by a significant loss of symmetry. During this process, the residues which later on bind to the human angiotensin converting enzyme 2 (ACE2) receptor, become exposed at the surface of the protein. Symmetry analysis of a data set of 33 protein structures from experimental measurements and 32 structures from molecular dynamics simulation, show that the initial state carries clear indications on the structure of the final state, with respect to the local distortion along the sequence. This surprising finding implies that this type of analysis predicts the mechanism of change. We further show that the level of local distortion at the initial state increases with variant's transmissibility, for the wild type (WT) along with past and present variants of concern (WT ∼ alpha < beta < delta < Omicron BA.1), in accordance with the trend of their evolutionary path. In other words, the initial structure of the variant which is most infectious is also the most distorted, making its path to the final state shorter. It has been claimed that the RBD migration of the spike protein is allosterically controlled. Our analysis provides a quantitative support to a major theorem in this respect - that information about an allosteric process is encoded in the structure itself, suggesting that the path of local distortion is related to an allosteric information network.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

Towards Quantum-Chemical Level Calculations of SARS-CoV-2 Spike Protein Variants of Concern by First Principles Density Functional Theory

The spike protein (S-protein) is a crucial part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with its many domains responsible for binding, fusion, and host cell entry. In this review we use the density functional theory (DFT) calculations to analyze the atomic-scale interactions and investigate the consequences of mutations in S-protein domains. We specifically describe the key amino acids and functions of each domain, which are essential for structural stability as well as recognition and fusion processes with the host cell; in addition, we speculate on how mutations affect these properties. Such unprecedented large-scale ab initio calculations, with up to 5000 atoms in the system, are based on the novel concept of amino acid-amino acid-bond pair unit (AABPU) that allows for an alternative description of proteins, providing valuable information on partial charge, interatomic bonding and hydrogen bond (HB) formation. In general, our results show that the S-protein mutations for different variants foster an increased positive partial charge, alter the interatomic interactions, and disrupt the HB networks. We conclude by outlining a roadmap for future computational research of biomolecular virus-related systems.

Guide for determination of protein structural ensembles by combining cryo-EM data with metadynamics

Metadynamics electron microscopy metaInference (MEMMI) is an integrative structural biology method that enables a rapid and accurate characterization of protein structural dynamics at the atomic level and the error in the cryo-EM experimental data, even in cases where conformations are separated by high energy barriers. It achieves this by incorporating (a) cryo-electron microscopy electron density maps with (b) metadynamic-enhanced-sampling molecular dynamics. Here, I showcase the setup and analysis protocol of MEMMI, used to discover the atomistic structural ensemble and error in the cryo-EM electron density map of the fuzzy coat of IAPP, a fibril implicated in type II diabetes.

SARS-CoV-2 spike opening dynamics and energetics reveal the individual roles of glycans and their collective impact

The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, binds to human ACE2, initiated by at least one protomer's receptor binding domain (RBD) switching from a "down" (closed) to an "up" (open) state. Here, we used large-scale molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations with more than a thousand windows and an aggregate total of 160 μs of simulation to investigate this transition with and without glycans. We find that the glycosylated spike has a higher barrier to opening and also energetically favors the down state over the up state. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state, while glycans at N165 and N343 can stabilize both the down and up states. Finally, we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the BD-368-2 antibody's epitope is continuously exposed, explaining its high efficacy.

Correlation between the binding affinity and the conformational entropy of nanobody SARS-CoV-2 spike protein complexes

Understanding the structural principles that determine the binding affinity of nanobodies to the spike protein of severe acute respiratory syndrome coronavirus 2 has been difficult. We analyzed electron microscopy maps of nanobody-spike complexes and quantified the conformational entropy of binding. This informed the design of an engineered nanobody with improved binding to the spike protein. This result offers a guiding principle for the rational maturation of nanobodies directed against the spike. High-binding potency nanobodies have been shown to be effective in animal models; thus, this technology could have application in future pandemics.

Camelid single-domain antibodies, also known as nanobodies, can be readily isolated from naïve libraries for specific targets but often bind too weakly to their targets to be immediately useful. Laboratory-based genetic engineering methods to enhance their affinity, termed maturation, can deliver useful reagents for different areas of biology and potentially medicine. Using the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and a naïve library, we generated closely related nanobodies with micromolar to nanomolar binding affinities. By analyzing the structure–activity relationship using X-ray crystallography, cryoelectron microscopy, and biophysical methods, we observed that higher conformational entropy losses in the formation of the spike protein–nanobody complex are associated with tighter binding. To investigate this, we generated structural ensembles of the different complexes from electron microscopy maps and correlated the conformational fluctuations with binding affinity. This insight guided the engineering of a nanobody with improved affinity for the spike protein.

Molecular simulations of complex carbohydrates and glycoconjugates

Complex carbohydrates (glycans) are the most abundant and versatile biopolymers in nature. The broad diversity of biochemical functions that carbohydrates cover is a direct consequence of the variety of 3D architectures they can adopt, displaying branched or linear arrangements, widely ranging in sizes, and with the highest diversity of building blocks of any other natural biopolymer. Despite this unparalleled complexity, a common denominator can be found in the glycans' inherent flexibility, which hinders experimental characterization, but that can be addressed by high-performance computing (HPC)-based molecular simulations. In this short review, I present and discuss the state-of-the-art of molecular simulations of complex carbohydrates and glycoconjugates, highlighting methodological strengths and weaknesses, important insights through emblematic case studies, and suggesting perspectives for future developments.

Computational design of stapled peptide inhibitor against SARS‐CoV ‐2 receptor binding domain

Since its first detection in 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) has been the cause of millions of deaths worldwide. Despite the development and administration of different vaccines, the situation is still worrisome as the virus is constantly mutating to produce newer variants some of which are highly infectious. This raises an urgent requirement to understand the infection mechanism and thereby design therapeutic‐based treatment for COVID‐19. The gateway of the virus to the host cell is mediated by the binding of the receptor binding domain (RBD) of the virus spike protein to the angiotensin‐converting enzyme 2 (ACE2) of the human cell. Therefore, the RBD of SARS‐CoV‐2 can be used as a target to design therapeutics. The α1 helix of ACE2, which forms direct contact with the RBD surface, has been used as a template in the current study to design stapled peptide therapeutics. Using computer simulation, the mechanism and thermodynamics of the binding of six stapled peptides with RBD have been estimated. Among these, the one with two lactam stapling agents has shown binding affinity, sufficient to overcome RBD‐ACE2 binding. Analyses of the mechanistic detail reveal that a reorganization of amino acids at the RBD‐ACE2 interface produces favorable enthalpy of binding whereas conformational restriction of the free peptide reduces the loss in entropy to result higher binding affinity. The understanding of the relation of the nature of the stapling agent with their binding affinity opens up the avenue to explore stapled peptides as therapeutic against SARS‐CoV‐2.

The inherent flexibility of receptor binding domains in SARS-CoV-2 spike protein

Spike (S) protein is the primary antigenic target for neutralization and vaccine development for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It decorates the virus surface and undergoes large motions of its receptor binding domains (RBDs) to enter the host cell. Here, we observe Down, one-Up, one-Open, and two-Up-like structures in enhanced molecular dynamics simulations, and characterize the transition pathways via inter-domain interactions. Transient salt-bridges between RBDA and RBDC and the interaction with glycan at N343B support RBDA motions from Down to one-Up. Reduced interactions between RBDA and RBDB in one-Up induce RBDB motions toward two-Up. The simulations overall agree with cryo-electron microscopy structure distributions and FRET experiments and provide hidden functional structures, namely, intermediates along Down-to-one-Up transition with druggable cryptic pockets as well as one-Open with a maximum exposed RBD. The inherent flexibility of S-protein thus provides essential information for antiviral drug rational design or vaccine development.

A general controllable release amplification strategy of liposomes for single-particle collision electrochemical biosensing

As an important component of the COVID-19 mRNA vaccines, liposomes play a key role in the efficient protection and delivery of mRNA to cells. Herein, due to the controllable release amplification strategy of liposomes, a reliable and robust single-particle collision electrochemical (SPCE) biosensor was constructed for H9N2 avian influenza virus (H9N2 AIV) detection by combining liposome encapsulation-release strategy with immunomagnetic separation. The liposomes modified with biotin and loaded with platinum nanoparticles (Pt NPs) were used as signal probes for the first time. Biotin facilitated the coupling of biomolecules (DNA or antibodies) through the specific reaction of biotin-streptavidin. Each liposome can encapsulate multiple Pt NPs, which were ruptured under the presence of 1 × PBST (phosphate buffer saline with 0.05% Tween-20) within 2 min, and the encapsulated Pt NPs were released for SPCE experiment. The combination of immunomagnetic separation not only improved the anti-interference capabilities but also avoided the agglomeration of Pt NPs, enabling the SPCE biosensor to realize ultrasensitive detection of 18.1 fg/mL H9N2 AIV. Furthermore, the reliable SPCE biosensor was successfully applied in specific detection of H9N2 AIV in complex samples (chicken serum, chicken liver and chicken lung), which promoted the universality of SPCE biosensor and its application prospect in early diagnosis of diseases.

Energy landscape of the SARS-CoV-2 reveals extensive conformational heterogeneity

Cryo-electron microscopy (cryo-EM) has produced a number of structural models of the SARS-CoV-2 spike, already prompting biomedical outcomes. However, these reported models and their associated electrostatic potential maps represent an unknown admixture of conformations stemming from the underlying energy landscape of the spike protein. As with any protein, some of the spike's conformational motions are expected to be biophysically relevant, but cannot be interpreted only by static models. Using experimental cryo-EM images, we present the energy landscape of the glycosylated spike protein, and identify the diversity of low-energy conformations in the vicinity of its open (so called 1RBD-up) state. The resulting atomic refinement reveal global and local molecular rearrangements that cannot be inferred from an average 1RBD-up cryo-EM model. Here we report varied degrees of "openness" in global conformations of the 1RBD-up state, not revealed in the single-model interpretations of the density maps, together with conformations that overlap with the reported models. We discover how the glycan shield contributes to the stability of these low-energy conformations. Five out of six binding sites we analyzed, including those for engaging ACE2, therapeutic mini-proteins, linoleic acid, two different kinds of antibodies, switch conformations between their known apo- and holo-conformations, even when the global spike conformation is 1RBD-up. This apo-to-holo switching is reminiscent of a conformational preequilibrium. We found only one binding site, namely that of AB-C135 remains in apo state within all the sampled free energy-minimizing models, suggesting an induced fit mechanism for the docking of this antibody to the spike.

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

A Structural Ensemble of a Tau-Microtubule Complex Reveals Regulatory Tau Phosphorylation and Acetylation Mechanisms

Tau is a microtubule-associated protein that regulates the stability of microtubules. We use metainference cryoelectron microscopy, an integrative structural biology approach, to determine an ensemble of conformations representing the structure and dynamics of a tau-microtubule complex comprising the entire microtubule-binding region of tau (residues 202-395). We thus identify the ground state of the complex and a series of excited states of lower populations. A comparison of the interactions in these different states reveals positions along the tau sequence that are important to determine the overall stability of the tau-microtubule complex. This analysis leads to the identification of positions where phosphorylation and acetylation events have destabilizing effects, which we validate by using site-specific post-translationally modified tau variants obtained by chemical mutagenesis. Taken together, these results illustrate how the simultaneous determination of ground and excited states of macromolecular complexes reveals functional and regulatory mechanisms.

DNA Aptamers Block the Receptor Binding Domain at the Spike Protein of SARS-CoV-2

DNA aptamers are versatile molecular species obtained by the folding of short single-stranded nucleotide sequences, with highly specific recognition capabilities against proteins. Here we test the ability of DNA aptamers to interact with the spike (S-)protein of the SARS-CoV-2 viral capsid. The S-protein, a trimer made up of several subdomains, develops the crucial function of recognizing the ACE2 receptors on the surface of human cells, and subsequent fusioning of the virus membrane with the host cell membrane. In order to achieve this, the S1 domain of one protomer switches between a closed conformation, in which the binding site is inaccessible to the cell receptors, and an open conformation, in which ACE2 can bind, thereby initiating the entry process of the viral genetic material in the host cell. Here we show, by means of state-of-the-art molecular simulations, that small DNA aptamers experimentally identified can recognize the S-protein of SARS-CoV-2, and characterize the details of the binding process. We find that their interaction with different subdomains of the S-protein can effectively block, or at least considerably slow down the opening process of the S1 domain, thereby significantly reducing the probability of virus-cell binding. We provide evidence that, as a consequence, binding of the human ACE2 receptor may be crucially affected under such conditions. Given the facility and low cost of fabrication of specific aptamers, the present findings could open the way to both an innovative viral screening technique with sub-nanomolar sensitivity, and to an effective and low impact curative strategy.