Spike Protein Mutation-Induced Changes in the Kinetic and Thermodynamic Behavior of Its Receptor Binding Domains Explain Their Higher Propensity to Attain Open States in SARS-CoV-2 Variants of Concern

Learning from Protein Engineering by Deconvolution of Multi-Mutational Variants

This review analyzes a development in biochemistry, enzymology and biotechnology that originally came as a surprise. Following the establishment of directed evolution of stereoselective enzymes in organic chemistry, the concept of partial or complete deconvolution of selective multi-mutational variants was introduced. Early deconvolution experiments of stereoselective variants led to the finding that mutations can interact cooperatively or antagonistically with one another, not just additively. During the past decade, this phenomenon was shown to be general. In some studies, molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) computations were performed in order to shed light on the origin of non-additivity at all stages of an evolutionary upward climb. Data of complete deconvolution can be used to construct unique multi-dimensional rugged fitness pathway landscapes, which provide mechanistic insights different from traditional fitness landscapes. Along a related line, biochemists have long tested the result of introducing two point mutations in an enzyme for mechanistic reasons, followed by a comparison of the respective double mutant in so-called double mutant cycles, which originally showed only additive effects, but more recently also uncovered cooperative and antagonistic non-additive effects. We conclude with suggestions for future work, and call for a unified overall picture of non-additivity and epistasis.

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.

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.

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.

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.

Discordant Antigenic Properties of Soluble and Virion SARS-CoV-2 Spike Proteins

Efforts to develop vaccine and immunotherapeutic countermeasures against the COVID-19 pandemic focus on targeting the trimeric spike (S) proteins of SARS-CoV-2. Vaccines and therapeutic design strategies must impart the characteristics of virion S from historical and emerging variants onto practical constructs such as soluble, stabilized trimers. The virus spike is a heterotrimer of two subunits: S1, which includes the receptor binding domain (RBD) that binds the cell surface receptor ACE2, and S2, which mediates membrane fusion. Previous studies suggest that the antigenic, structural, and functional characteristics of virion S may differ from current soluble surrogates. For example, it was reported that certain anti-glycan, HIV-1 neutralizing monoclonal antibodies bind soluble SARS-CoV-2 S but do not neutralize SARS-CoV-2 virions. In this study, we used single-molecule fluorescence correlation spectroscopy (FCS) under physiologically relevant conditions to examine the reactivity of broadly neutralizing and non-neutralizing anti-S human monoclonal antibodies (mAbs) isolated in 2020. Binding efficiency was assessed by FCS with soluble S trimers, pseudoviruses and inactivated wild-type virions representing variants emerging from 2020 to date. Anti-glycan mAbs were tested and compared. We find that both anti-S specific and anti-glycan mAbs exhibit variable but efficient binding to a range of stabilized, soluble trimers. Across mAbs, the efficiencies of soluble S binding were positively correlated with reactivity against inactivated virions but not pseudoviruses. Binding efficiencies with pseudoviruses were generally lower than with soluble S or inactivated virions. Among neutralizing mAbs, potency did not correlate with binding efficiencies on any target. No neutralizing activity was detected with anti-glycan antibodies. Notably, the virion S released from membranes by detergent treatment gained more efficient reactivity with anti-glycan, HIV-neutralizing antibodies but lost reactivity with all anti-S mAbs. Collectively, the FCS binding data suggest that virion surfaces present appreciable amounts of both functional and nonfunctional trimers, with neutralizing anti-S favoring the former structures and non-neutralizing anti-glycan mAbs binding the latter. S released from solubilized virions represents a nonfunctional structure bound by anti-glycan mAbs, while engineered soluble trimers present a composite structure that is broadly reactive with both mAb types. The detection of disparate antigenicity and immunoreactivity profiles in engineered and virion-associated S highlight the value of single-virus analyses in designing future antiviral strategies against SARS-CoV-2.

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.