Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variant Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms

Comparison of the ACE2 receptor and monoclonal antibodies immobilisation strategies for the sensitive detection of SARS-CoV-2 variants of concern

Investigation of antibody or receptor immobilisation and binding to the target analyte is essential for the development of effective immunoassays. In our research, we applied the combination of two surface-sensitive methods: spectroscopic ellipsometry and quartz crystal microbalance with dissipation. It enabled quantitative investigation of optical and mechanical properties of formed biomolecule layers consisting of monoclonal antibodies (mAb) or angiotensin-converting enzyme 2 (ACE2) receptors coupled with the Fc fragment, in complex with severe acute respiratory syndrome coronavirus 2 spike Omicron variant (SCoV2-oS). Random and site-directed immobilisation of ACE2 receptor gave 1.8 and 2.4 times higher dry surface mass density compared to random and site-direct mAbs immobilisation, respectively. Therefore, ACE2 had better potential for more sensitive detection of the target analyte SCoV2-oS. However, the binding of SCoV2-oS to site-directed ACE2 resulted in a low 80 ng/cm2 surface mass compared to other samples. Moreover, ΔD/ΔF data revealed two-step binding of SCoV2-oS to ACE2 and mAbs. Furthermore, calculated affinity constants (KD) showed that both ACE2 and mAb have high affinity to SCoV2-oS (in the range of 10-10 to 10-11 M), and their orientation on the surface had only a minor impact on KD values. Our findings in this investigation indicated that ACE2 coupled with the Fc fragment is as effective in the recognition of SARS-CoV-2 as mAbs and it can be successfully applied for the development of immunoassays. Considering SARS-CoV-2 mutates for a better S protein binding to the ACE2 receptor, using ACE2 as a biorecognition element is useful.

Exploring Diverse Binding Mechanisms of Broadly Neutralizing Antibodies S309, S304, CYFN-1006 and VIR-7229 Targeting SARS-CoV-2 Spike Omicron Variants: Integrative Computational Modeling Reveals Balance of Evolutionary and Dynamic Adaptability in Shaping Molecular Determinants of Immune Escape

Evolution of SARS-CoV-2 has led to the emergence of variants with increased immune evasion capabilities, posing significant challenges to antibody-based therapeutics and vaccines. The cross-neutralization activity of antibodies against Omicron variants is governed by a complex and delicate interplay of multiple energetic factors and interaction contributions. In this study, we conducted a comprehensive analysis of the interactions between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and four neutralizing antibodies S309, S304, CYFN1006, and VIR-7229. Using integrative computational modeling that combined all-atom molecular dynamics (MD) simulations, mutational scanning, and MM-GBSA binding free energy calculations, we elucidated the structural, energetic, and dynamic determinants of antibody binding. Our findings reveal distinct dynamic binding mechanisms and evolutionary adaptation driving broad neutralization effect of these antibodies. We show that S309 targets conserved residues near the ACE2 interface, leveraging synergistic van der Waals and electrostatic interactions, while S304 focuses on fewer but sensitive residues, making it more susceptible to escape mutations. The analysis of CYFN-1006.1 and CYFN-1006.2 antibody binding highlights broad epitope coverage with critical anchors at T345, K440, and T346, enhancing its efficacy against variants carrying the K356T mutation which caused escape from S309 binding. Our analysis of broadly potent VIR-7229 antibody binding to XBB.1.5 and EG.5 Omicron variants emphasized a large and structurally complex epitope, demonstrating certain adaptability and compensatory effects to F456L and L455S mutations. Mutational profiling identified key residues crucial for antibody binding, including T345, P337, and R346 for S309, and T385 and K386 for S304, underscoring their roles as evolutionary "weak spots" that balance viral fitness and immune evasion. The results of this energetic analysis demonstrate a good agreement between the predicted binding hotspots and critical mutations with respect to the latest experiments on average antibody escape scores. The results of this study dissect distinct energetic mechanisms of binding and importance of targeting conserved residues and diverse epitopes to counteract viral resistance. Broad-spectrum antibodies CYFN1006 and VIR-7229 maintain efficacy across multiple variants and achieve neutralization by targeting convergent evolution hotspots while enabling tolerance to mutations in these positions through structural adaptability and compensatory interactions at the binding interface. The results of this study underscore the diversity of binding mechanisms employed by different antibodies and molecular basis for high affinity and excellent neutralization activity of the latest generation of antibodies.

Computational Analysis of the Fully Activated Orexin Receptor 2 across Various Thermodynamic Ensembles with Surface Tension Monitoring and Markov State Modeling

In this study, we investigated the stability of the fully activated conformation of the orexin receptor 2 (OX2R) embedded in a pure POPC bilayer using MD simulations. Various thermodynamic ensembles (i.e., NPT, NVT, NVE, NPAT, μVT, and NPγT) were employed to explore the dynamical heterogeneity of the system in a comprehensive way. In addition, informational similarity metrics (e.g., Jensen-Shannon divergence) as well as Markov state modeling approaches were utilized to elucidate the receptor kinetics. Special attention was paid to assessing surface tension within the simulation box, particularly under NPγT conditions, where 21 nominal surface tension constants were evaluated. Our findings suggest that traditional thermodynamic ensembles such as NPT may not adequately control physical properties of the POPC membrane, impacting the plausibility of the OX2R model. In general, the performed study underscores the importance of employing the NPγT ensemble for computational investigations of membrane-embedded receptors, as it effectively maintains zero surface tension in the simulated system. These results offer valuable insights for future research aimed at understanding receptor dynamics and designing targeted therapeutics.

Mutational Scanning and Binding Free Energy Computations of the SARS-CoV-2 Spike Complexes with Distinct Groups of Neutralizing Antibodies: Energetic Drivers of Convergent Evolution of Binding Affinity and Immune Escape Hotspots

The rapid evolution of SARS-CoV-2 has led to the emergence of variants with increased immune evasion capabilities, posing significant challenges to antibody-based therapeutics and vaccines. In this study, we conducted a comprehensive structural and energetic analysis of SARS-CoV-2 spike receptor-binding domain (RBD) complexes with neutralizing antibodies from four distinct groups (A-D), including group A LY-CoV016, group B AZD8895 and REGN10933, group C LY-CoV555, and group D antibodies AZD1061, REGN10987, and LY-CoV1404. Using coarse-grained simplified simulation models, rapid energy-based mutational scanning, and rigorous MM-GBSA binding free energy calculations, we elucidated the molecular mechanisms of antibody binding and escape mechanisms, identified key binding hotspots, and explored the evolutionary strategies employed by the virus to evade neutralization. The residue-based decomposition analysis revealed energetic mechanisms and thermodynamic factors underlying the effect of mutations on antibody binding. The results demonstrate excellent qualitative agreement between the predicted binding hotspots and the latest experiments on antibody escape. These findings provide valuable insights into the molecular determinants of antibody binding and viral escape, highlighting the importance of targeting conserved epitopes and leveraging combination therapies to mitigate the risk of immune evasion.

Quantitative Characterization and Prediction of the Binding Determinants and Immune Escape Hotspots for Groups of Broadly Neutralizing Antibodies Against Omicron Variants: Atomistic Modeling of the SARS-CoV-2 Spike Complexes with Antibodies

A growing body of experimental and computational studies suggests that the cross-neutralization antibody activity against Omicron variants may be driven by the balance and tradeoff between multiple energetic factors and interaction contributions of the evolving escape hotspots involved in antigenic drift and convergent evolution. However, the dynamic and energetic details quantifying the balance and contribution of these factors, particularly the balancing nature of specific interactions formed by antibodies with epitope residues, remain largely uncharacterized. In this study, we performed molecular dynamics simulations, an ensemble-based deep mutational scanning of SARS-CoV-2 spike residues, and binding free energy computations for two distinct groups of broadly neutralizing antibodies: the E1 group (BD55-3152, BD55-3546, and BD5-5840) and the F3 group (BD55-3372, BD55-4637, and BD55-5514). Using these approaches, we examined the energetic determinants by which broadly potent antibodies can largely evade immune resistance. Our analysis revealed the emergence of a small number of immune escape positions for E1 group antibodies that correspond to the R346 and K444 positions in which the strong van der Waals and interactions act synchronously, leading to the large binding contribution. According to our results, the E1 and F3 groups of Abs effectively exploit binding hotspot clusters of hydrophobic sites that are critical for spike functions along with the selective complementary targeting of positively charged sites that are important for ACE2 binding. Together with targeting conserved epitopes, these groups of antibodies can lead expand the breadth and resilience of neutralization to the antigenic shifts associated with viral evolution. The results of this study and the energetic analysis demonstrate excellent qualitative agreement between the predicted binding hotspots and critical mutations with respect to the latest experiments on average antibody escape scores. We argue that the E1 and F3 groups of antibodies targeting binding epitopes may leverage strong hydrophobic interactions with the binding epitope hotspots that are critical for the spike stability and ACE2 binding, while escape mutations tend to emerge in sites associated with synergistically strong hydrophobic and electrostatic interactions.

Assessing the role of deep eutectic solvents in Yarrowia lipolytica inhibition

Yarrowia lipolytica has gained recognition as a microorganism with biological relevance and extensive biotechnological applications. Some of its features include a high enzyme secretion capacity and a high cell-density fermentation mode. Hexokinase (YlHxk) is a vital enzyme in Y. lipolytica growth since it catalyzes glucose metabolism through phosphorylation in the glycolytic pathway. Given the potential application of deep eutectic solvents (DES) as novel solvents in biotechnological processes, this study evaluated the influence of eighteen DES on the growth of Y. lipolytica. Furthermore, this work examined the effects of individual ions on the YlHxk enzyme by analyzing its enzymatic tunnel structure, molecule transport, and molecular docking. The results revealed a significant reduction in yeast growth in the presence of most DES compared to the control (medium without DES), with the exception of the [N8881]Cl: hexanoic acid (1:1) DES. The growth varied between 11.95 ± 0.60 and 0.68 ± 0.17 g dry cell weight L-1. According to the enzymatic tunnel analysis, DES components associated with the lowest microbial growth values were transported through tunnel 1. On the other hand, DES components had their pathway facilitated through tunnel 2 ([N8881]+ and hexanoic acid) and showed growth values close to the control. Molecular docking analysis identified a similarity between all the ligands in this tunnel (including substrate and product), presenting binding interactions with the ASN273 amino acid of the YlHxk active site. Combining experimental results with computational tools provided promising insights at the molecular level, while also potentially reducing analysis costs and time, paving the way for similar approaches in broad biocatalytic reactions.

Quantitative Characterization and Prediction of the Binding Determinants and Immune Escape Hotspots for Groups of Broadly Neutralizing Antibodies Against Omicron Variants: Atomistic Modeling of the SARS-CoV-2 Spike Complexes with Antibodies

The growing body of experimental and computational studies suggested that the cross-neutralization antibody activity against Omicron variants may be driven by balance and tradeoff of multiple energetic factors and interaction contributions of the evolving escape hotspots involved in antigenic drift and convergent evolution. However, the dynamic and energetic details quantifying the balance and contribution of these factors, particularly the balancing nature of specific interactions formed by antibodies with the epitope residues remain scarcely characterized. In this study, we performed molecular dynamics simulations, ensemble-based deep mutational scanning of SARS-CoV-2 spike residues and binding free energy computations for two distinct groups of broadly neutralizing antibodies : E1 group (BD55-3152, BD55-3546 and BD5-5840) and F3 group (BD55-3372, BD55-4637 and BD55-5514). Using these approaches, we examine the energetic determinants by which broadly potent antibodies can largely evade immune resistance. Our analysis revealed the emergence of a small number of immune escape positions for E1 group antibodies that correspond to R346 and K444 positions in which the strong van der Waals and interactions act synchronously leading to the large binding contribution. According to our results, E1 and F3 groups of Abs effectively exploit binding hotspot clusters of hydrophobic sites critical for spike functions along with selective complementary targeting of positively charged sites that are important for ACE2 binding. Together with targeting conserved epitopes, these groups of antibodies can lead to the expanded neutralization breadth and resilience to antigenic shift associated with viral evolution. The results of this study and the energetic analysis demonstrate excellent qualitative agreement between the predicted binding hotspots and critical mutations with respect to the latest experiments on average antibody escape scores. We argue that E1 and F3 groups of antibodies targeting binding epitopes may leverage strong hydrophobic interactions with the binding epitope hotspots critical for the spike stability and ACE2 binding, while escape mutations tend to emerge in sites associated with synergistically strong hydrophobic and electrostatic interactions.

Toward the Design of Allosteric Effectors: Gaining Comprehensive Control of Drug Properties and Actions

While the therapeutic potential of allosteric drugs is increasingly realized, the discovery of effectors is largely incidental. The rational design of allosteric effectors requires new state-of-the-art approaches to account for the distinct characteristics of allosteric ligands and their modes of action. We present a broadly applicable computational framework for obtaining allosteric site-effector pairs, providing targeted, highly specific, and tunable regulation to any functional site. We validated the framework using the main protease from SARS-CoV-2 and the K-RasG12D oncoprotein. High-throughput per-residue quantification of the energetics of allosteric signaling and effector binding revealed known drugs capable of inducing the required modulation upon binding. Starting from fragments of known well-characterized drugs, allosteric effectors and binding sites were designed and optimized simultaneously to achieve targeted and specific signaling to distinct functional sites, such as, for example, the switch regions of K-RasG12D. The generic framework proposed in this work will be instrumental in developing allosteric therapies aligned with a precision medicine approach.

AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants: Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance

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 the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that 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.

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.

β-sheets mediate the conformational change and allosteric signal transmission between the AsLOV2 termini

Avena sativa phototropin 1 light-oxygen-voltage 2 domain (AsLOV2) is a model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change begins with the unfolding of the N-terminal A'α helix in the dark state followed by the unfolding of the C-terminal Jα helix. The light state is characterized by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets are identified as crucial components for mediating allosteric signal transmission between the two termini. Through combined experimental and computational investigations, the Hβ and Iβ strands are recognized as the most critical and influential β-sheets in AsLOV2's allosteric mechanism. To elucidate the role of these β-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive molecular dynamics simulations. In-depth hydrogen bond analyses emphasized the role of two hydrogen bonds, Asn482-Leu453 and Gln479-Val520, in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. This illustrates the role of β-sheets in the transmission of the allosteric signal upon the photoactivation of the light state.

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.

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.

Allosteric drugs: New principles and design approaches

Focusing on an important biomedical implication of allostery - design of allosteric drugs, we describe characteristics of allosteric sites, effectors, and their modes of actions distinguishing them from the orthosteric counterparts and calling for new principles and protocols in the quests for allosteric drugs. We show the importance of considering both binding affinity and allosteric signaling in establishing the structure-activity relationships (SARs) toward design of allosteric effectors, arguing that pairs of allosteric sites and their effector ligands - the site-effector pairs - should be generated and adjusted simultaneously in the framework of what we call directed design protocol. Key ideas and approaches for designing allosteric effectors including reverse perturbation, targeted and agnostic analysis are also discussed here. Several promising computational approaches are highlighted, along with the need for and potential advantages of utilizing generative models to facilitate discovery/design of new allosteric drugs.

Microsecond Molecular Dynamics Simulations and Markov State Models of Mutation-Induced Allosteric Mechanisms for the Light-Oxygen-Voltage 2 Protein : Revealing Structural Basis of Signal Transmission Induced by Photoactivation of the Light Protein State

Avena Sativa phototropin 1 Light-oxygen-voltage 2 domain (AsLOV2) is the model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change is initiated by the unfolding of the N-terminal helix in the dark state followed by the unfolding of the C-terminal helix. The light state is defined by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets have been identified as crucial components for mediating allosteric signal transmission between the two termini. In this study, we combined microsecond all-atm molecular dynamics simulations and Markov state modeling of conformational states to quantify molecular basis of mutation-induced allostery in the AsLOV2 protein. Through a combination of computational investigations, we determine that the Hβ and Iβ strands are the most critical structural elements involved in the allosteric mechanism. To elucidate the role of these β-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive simulation analysis. The results highlighted the role of two hydrogen bond Asn482-Leu453 and Gln479-Val520 in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. The comprehensive atomistic-level analysis of the conformational landscapes revealed the critical functional role of β-sheet segments in the transmission of the allosteric signal upon the photoactivation of the light state.

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.

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.