Contrasting dynamic and mechanistic signatures of Class 3 and Class 4 neutralizing antibodies targeting SARS-CoV-2 spike protein: dissecting molecular determinants of neutralization mechanisms using a multi-pronged computational approach.
TL;DR
An integrated computational framework combining structural analysis, conformational dynamics, mutational scanning, binding energetics, and allosteric network modeling to systematically dissect Class 3 and Class 4 antibodies provides a generalizable paradigm for understanding antibody neutralization mechanisms, predicting immune escape, and guiding rational design of next-generation therapeutics that balance potency, breadth, and resilience.
Abstract
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. Here, we employ an integrated computational framework combining structural analysis, conformational dynamics, mutational scanning, binding energetics, and allosteric network modeling to systematically dissect Class 3 and Class 4 antibodies. Analysis of single-antibody complexes (COV2-3835, COV2-3891, COV2-3906) and synergistic dual-antibody pairs reveals a fundamental mechanistic dichotomy: Class 3 antibodies exert localized mechanical constraint strictly confined to the binding interface, whereas Class 4 antibodies propagate long-range allosteric destabilization from an evolutionarily conserved hydrophobic core through the β-sheet core to the RBM loop. Mutational scanning and energetic analyses demonstrate that Class 4 epitopes are anchored by an immutable hydrophobic core exquisitely sensitive to mutation yet conserved across viruses, conferring ultra-broad binding and limited escape potential, while Class 3 epitopes exhibit a plastic periphery with variable sensitivity that creates multiple escape pathways. Predictions show excellent agreement with deep mutational scanning data, validating our approach. Allosteric network analysis identifies β-sheet core residues as essential communication hubs, where convergence of high centrality and extreme perturbation sensitivity establishes critical hotspots resistant to mutation. This multi-pronged framework provides a generalizable paradigm for understanding antibody neutralization mechanisms, predicting immune escape, and guiding rational design of next-generation therapeutics that balance potency, breadth, and resilience.