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
Open Access
Abstract
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.Keywords
Funding Information
- Kay Family Foundation (A20-0032, 1R01AI181600-01, 6069-SC24-11)
- National Institutes of Health (A20-0032, 1R01AI181600-01, 6069-SC24-11)
- Subaward (A20-0032, 1R01AI181600-01, 6069-SC24-11)
This publication has 139 references indexed in Scilit:
- Allosteric pathways of SARS and SARS‐CoV‐2 spike protein identified by neural relational inferenceProteins: Structure, Function, and Bioinformatics, 2024
- Alarming antibody evasion properties of rising SARS-CoV-2 BQ and XBB subvariantsCell, 2022
- Potent cross-reactive antibodies following Omicron breakthrough in vaccineesCell, 2022
- Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 BindingCell, 2020
- Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2Cell, 2020
- Structure, Function, and Antigenicity of the SARS-CoV-2 Spike GlycoproteinCell, 2020
- 3Drefine: Consistent protein structure refinement by optimizing hydrogen bonding network and atomic‐level energy minimizationProteins: Structure, Function, and Bioinformatics, 2012
- Improved prediction of protein side‐chain conformations with SCWRL4Proteins: Structure, Function, and Bioinformatics, 2009
- CHARMM‐GUI: A web‐based graphical user interface for CHARMMJournal of Computational Chemistry, 2008
- Locating the active sites of enzymes using mechanical propertiesProteins: Structure, Function, and Bioinformatics, 2007