Mohammed Alshahrani

Broadly neutralizing antibodies targeting the silent face of the SARS-CoV-2 receptor-binding do-main (RBD) provide essential templates for pan-sarbecovirus therapeutics, yet the precise bio-physical mechanisms dictating their neutralization breadth, energetic propensities, and escape re-silience remain unresolved. By combining all-atom and coarse-grained molecular dynamics, systematic mutational scanning, rigorous MM-GBSA binding free energy analysis, and residue interaction network modeling we delineate the comparative structural, energetic, and allosteric signatures of Site V (CC25.4, CC25.43, CC25.56, 7D6, 6D6 ) and CR3022-site (Group 1: CC25.54, CC84.2, CC84.24) antibodies. We discover that these two classes by engaging spatially opposite faces of the RBD fold produce mutually exclusive energetic hotspot modules. Site V antibodies are anchored along a surface-exposed lateral ridge by residues R355, R357, R466, I468, F464, and K462, whereas CR3022-site antibodies engage a buried β-sheet-core module comprising R408, K378, C379, Y380, F377, and Q414. Remarkably, despite these distinct epitopes, both classes converge on an ultra-conserved paratope tyrosine triad (Y99, Y100, Y49), establishing a universal structural motif for silent-face recognition. Network centrality modeling demonstrates that Site V and CR3022-site antibodies modulate ACE2 receptor interface dynamics via distinct upstream allo-steric pathways that converge on shared RBM-loop relays at Y423, Y396, and F464. Crucially, in CR3022-site antibodies, binding free energy hotspots and allosteric communication hubs coincide directly within the structurally constrained β-sheet core. This enforces a dual-constraint mecha-nism where escape mutations inherently compromise viral fold integrity. Conversely, Site V binding hotspots and allosteric networks are structurally segregated, exposing cryptic allosteric liabilities where mutations at non-contact positions (F456, R509) dynamically rewire network communication to impair neutralization without altering static interface affinity. Furthermore, within-class resilience is governed by epitope architecture: focused antibodies (CC25.56, 6D6, CC25.54) concentrate binding energy into single dominant anchors vulnerable to point mutations, whereas broad antibodies (CC84.2, CC84.24, CC25.4, CC25.43) distribute binding energetics across multi-residue contact networks. These quantitative findings align directly with experimental neutralization data. The structural immutability of the β-sheet-core module provides a mechanistic explanation for why CR3022-site antibodies CC84.2 and CC84.24 retain activity against highly evasive Omicron sublineages BA.2.86 and JN.1. A complete absence of energetic or allosteric hotspots at major Class 1/2 escape loci explains the cross-variant breadth exhibited by both si-lent-face classes. By establishing how silent-face antibodies balance potency, breadth, and resili-ence, this work offers a predictive biophysical framework for tracking viral antigenic drift and designing durable, multi-epitope antibody cocktails.

Neutralizing antibodies targeting the SARS-CoV-2 spike receptor-binding domain (RBD) exhibit distinct patterns of potency, breadth, and resilience, yet the molecular mechanisms underlying these differences remain incompletely understood.

The relentless evolution of SARS-CoV-2 and the emergence of highly antibody-evasive variants underscore the need to decipher the molecular principles that govern antibody neutralization breadth and resilience. In this study, we employ an integrated computational framework combining structural analysis, conformational dynamics, mutational scanning, binding energetics, and allosteric network modeling to dissect the mechanistic signatures of class 3 and class 4 antibodies targeting the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Through comprehensive analysis of antibody-RBD complexes including individual antibodies (COV2-3835, COV2-3891, COV2-3906) and synergistic dual-antibody pairs we uncover a fundamental mechanistic dichotomy that distinguishes these two antibody classes and explains their differential patterns of neutralization potency, breadth, and resilience to viral escape. Our analysis reveals that class 3 antibodies achieve neutralization with mechanical perturbation strictly confined to the binding interface. In contrast, class 4 antibodies employ a long-range allosteric destabilization mechanism, anchoring to a structurally rigid hydrophobic core and establishing a mechanical conduit through the β-sheet core that transmits conformational changes. Mutational scanning and rigorous energetic analysis reveal fundamentally different vulnerability landscapes: class 4 epitopes are defined by an immutable hydrophobic core that is exquisitely sensitive to mutation yet evolutionarily constrained across sarbecoviruses, explaining their ultra-broad binding and limited escape potential. Class 3 epitopes exhibit a plastic periphery with a conserved anchor and variable sensitivity in peripheral regions, creating multiple escape pathways. These predictions show excellent agreement with experimental deep mutational scanning data, validating our computational approach and establishing a quantitative framework for predicting immune escape. Allosteric network analysis identifies the β-sheet core as the critical communication conduit for class 4 antibodies, with specific residues serving as essential hubs that connect the hydrophobic core to the RBM loop. The convergence of high communication centrality with extreme perturbation sensitivity at these positions establishes them as the most critical allosteric hotspots, essential for function and resistant to mutation. The proposed multi-pronged computational framework provides a generalizable approach for understanding antibody neutralization mechanisms and predicting immune escape across diverse viral targets, with implications for the rational design of next-generation antibody therapeutics that balance potency, breadth, and resilience.

The continued evolution of SARS-CoV-2 has enabled an escape from most monoclonal antibodies, yet a subset of broadly neutralizing antibodies targeting three newly identified super-conserved RBD epitopes—SCORE-A, SCORE-B, and SCORE-C—retains remarkable activity against even the most recent JN.1-derived sublineages. Here, we employed an integrated computational framework combining conformational dynamics, mutational scanning, MM-GBSA binding energetics, and frustration profiling to dissect the molecular mechanisms by which XGI antibodies achieve broad neutralization and resistance to immune escape. Structural analysis revealed that all three SCORE epitopes share a common architecture: a highly conserved, minimally frustrated core that provides stable anchoring, flanked by peripheral regions that accommodate antibody-specific variations. Conformational dynamics showed that SCORE-A antibodies (XGI-183) rigidify the lateral epitope while leaving the RBM partially mobile; SCORE-B antibodies (XGI-198, XGI-203) clamp the RBM apex, directly blocking ACE2; and SCORE-C antibodies (XGI-171) allosterically loosen the RBM loop, impairing receptor engagement indirectly. Mutational scanning identified a hierarchical hotspot organization where primary hotspots (e.g., K356, T500, Y380, T385) are evolutionarily constrained and minimally frustrated, while secondary hotspots (e.g., V503, Y508, S383) are neutrally frustrated and represent the principal sites of immune-driven mutations. MM-GBSA decomposition revealed that van der Waals-driven hydrophobic packing dominates binding, with electrostatic interactions providing auxiliary stabilization. Critically, frustration analysis demonstrated that immune escape hotspots reside precisely in zones of neutral frustration—“energetic playgrounds” that permit mutational exploration without destabilizing the RBD—while minimally frustrated cores are evolutionarily locked. The comparative analysis of conformational versus mutational frustration distributions revealed a unifying principle: aligned neutral frustration yields permissive, escape-prone interfaces; decoupling enables the targeting of constrained cores; and the convergence of minimal frustration in both distributions creates invulnerable interfaces. These findings establish that broad neutralization arises not from ultra-high-affinity anchors but from strategic energy distribution across rigid, evolutionarily informed interfaces, providing a roadmap for designing next-generation therapeutics that target the invulnerable cores of viral surface proteins.

The continued evolution of SARS-CoV-2 has enabled escape from most monoclonal antibodies, yet a subset of broadly neutralizing antibodies targeting three newly identified super-conserved RBD epitopes—SCORE-A, SCORE-B, and SCORE-C—retains remarkable activity against even the most recent JN.1-derived sublineages. Here we employed an integrated computational framework combining conformational dynamics, mutational scanning, MM-GBSA binding energetics, and frustration profiling to dissect the molecular mechanisms by which XGI antibodies achieve broad neutralization and resistance to immune escape. Structural analysis revealed that all three SCORE epitopes share a common architecture: a highly conserved, minimally frustrated core that provides stable anchoring, flanked by peripheral regions that accommodate antibody-specific variations. Conformational dynamics showed that SCORE-A antibodies (XGI-183) rigidify the lateral epitope while leaving the RBM partially mobile; SCORE-B antibodies (XGI-198, XGI-203) clamp the RBM apex, directly blocking ACE2; and SCORE-C antibodies (XGI-171) allosterically loosen the RBM loop, impairing receptor engagement indirectly. Mutational scanning identified a hierarchical hotspot organization where primary hotspots (e.g., K356, T500, Y380, T385) are evolutionarily constrained and minimally frustrated, while secondary hotspots (e.g., V503, Y508, S383) are neutrally frustrated and represent the principal sites of immune-driven mutations. MM-GBSA decomposition revealed that van der Waals-driven hydrophobic packing dominates binding, with electrostatic interactions providing auxiliary stabilization. Critically, frustration analysis demonstrated that immune escape hotspots reside precisely in zones of neutral frustration—"energetic playgrounds" that permit mutational explora-tion without destabilizing the RBD—while minimally frustrated cores are evolutionarily locked. The comparative analysis of conformational versus mutational frustration dis-tributions revealed a unifying principle: aligned neutral frustration yields permissive, escape-prone interfaces; decoupling enables targeting of constrained cores; and convergence of minimal frustration in both distributions creates invulnerable interfaces. These findings establish that broad neutralization arises not from ultra-high-affinity anchors but from strategic energy distribution across rigid, evolutionarily informed interfaces, providing a roadmap for designing next-generation therapeutics that target the invulnerable cores of viral surface proteins.

The relentless evolution of SARS-CoV-2 underscores the urgent need to decipher the molecular principles that enable certain antibodies to maintain exceptional breadth and resilience against immune escape.

The relentless evolution of SARS-CoV-2 underscores the urgent need to decipher the molecular principles that enable certain antibodies to maintain exceptional breadth and resilience against immune escape. In this study, we employ a multi-pronged computational framework integrating structural analysis, conformational dynamics, mutational scanning, MM-GBSA binding energetics, and conformational and mutational frustration profiling to dissect the mechanisms of ultrapotent neutralization by a cohort of broadly reactive Class 1 antibodies (BD55-1205, 19-77, ZCP4C9, ZCP3B4) and the Class 4/1 antibody ADG20. We reveal a unifying biophysical architecture: these antibodies bind via rigid, pre-configured interfaces that distribute binding energy across extensive epitopes through numerous suboptimal yet synergistic interactions, predominantly with backbone atoms and conserved side chains. This distributed redundancy enables tolerance to mutations at key sites like F456L or A475V without catastrophic loss of affinity. Mutational scanning identifies a hierarchical hotspot organization where primary hotspots (e.g., H505, Y501, Y489, Y421) which overlap with ACE2-contact residues and incur high fitness costs upon mutation are buffered by secondary hotspots (e.g., F456, L455) that are more permissive to variation. MM-GBSA energy decomposition confirms that van der Waals-driven hydrophobic packing dominates binding, with primary hotspots contributing disproportionately to affinity, while electrostatic networks provide auxiliary stabilization that mitigates mutational effects. Critically, both conformational and mutational frustration analyses demonstrate that immune escape hotspots reside in neutral-frustration landscape that permit mutational exploration without destabilizing the RBD, explaining the repeated emergence of convergent mutations across lineages. Our results establish that broad neutralization arises not from ultra-high-affinity anchors, but rather from strategic energy distribution across rigid, evolutionarily informed interfaces. By linking distributed binding, neutral frustration landscapes, and viral fitness constraints, this framework provides a predictive blueprint for designing next-generation therapeutics and vaccines capable of withstanding viral evolution.

Understanding the atomistic basis of multi-layer mechanisms employed by broadly reactive neutralizing antibodies of the SARS-CoV-2 spike protein without directly blocking receptor engagement remains an important challenge in coronavirus immunology. Class 4 antibodies represent an intriguing case: they target a deeply conserved, cryptic epitope on the receptor-binding domain yet exhibit variable neutralization potency across subgroups F1 (CR3022, EY6A, COVA1-16), F2 (DH1047), and F3 (S2X259). The molecular basis for this variability is not fully understood. Here, we employed a multi-modal computational approach integrating atomistic and coarse-grained molecular dynamics simulations, binding free energy calculations, mutational scanning, and dynamic network analysis to elucidate how these antibodies engage the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and influence its function. Our results reveal that neutralization efficacy arises from the interplay of direct interfacial interactions and allosteric effects. Group F1 antibodies (CR3022, EY6A, COVA1-16) primarily operate via classic allostery, modulating flexibility in RBD loop regions to indirectly interfere with the ACE2 receptor binding through long-range effects. Group F2 antibody DH1047 represents an intermediate mechanism, combining partial steric hindrance—through engagement of ACE2-critical residues T376, R408, V503, and Y508—with significant allosteric influence, facilitated by localized communication pathways linking the epitope to the receptor interface. Group F3 antibody S2X259 achieves potent neutralization through a synergistic mechanism involving direct competition with ACE2 and localized allosteric stabilization, albeit with potentially increased escape vulnerability. Dynamic network analysis identified a conserved “allosteric ring” within the RBD core that serves as a structural scaffold for long-range signal propagation, with antibody-specific extensions modulating communication to the ACE2 interface. These findings support a model where Class 4 neutralization strategies evolve through the refinement of peripheral allosteric connections rather than epitope redesign. This study establishes a robust computational framework for understanding the atomistic basis of neutralization activity and immune escape for Class 4 antibodies, highlighting how the interplay of binding energetics, conformational dynamics, and allosteric modulation governs their effectiveness against SARS-CoV-2.

The ongoing evolution of SARS-CoV-2 variants has underscored the need to understand the dynamic and allosteric mechanisms that could contribute to escape-resistant neutralization activities of highly potent antibodies.

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope footprint and distributed hotspot architecture, additionally supported by backbone-mediated specific interactions, which are less sensitive to amino acid substitutions and together enable exceptional tolerance to mutational escape. In contrast, BD-604 and OMI-42 exhibit localized binding modes with strong dependence on side-chain interactions, rendering them particularly vulnerable to escape mutations at K417N, L455M, F456L and A475V. Similarly, P5S-1H1 and P5S-2B10 display intermediate behavior—effective in some contexts but increasingly susceptible to antigenic drift due to narrower epitope coverage and concentrated hotspots. Our computational predictions show strong agreement with experimental deep mutational scanning data, validating the accuracy of the models and reinforcing the value of binding hotspot mapping in predicting antibody vulnerability. This work highlights that neutralization breadth and durability are not solely dictated by epitope location, but also by how binding energy is distributed across the interface. The results provide atomistic insight into mechanisms driving resilience to immune escape for broadly neutralizing antibodies targeting the ACE2 binding interface—which stems from cumulative effects of structural diversity in binding contacts, redundancy in interaction patterns and reduced vulnerability to mutation-prone positions.