Hydrophobic remodeling of the SARS-CoV-2 RBD large loop attenuates ACE2 engagement and viral fitness
The SARS-CoV-2 Omicron subvariant JN.4 harbors a unique A475V substitution within the receptor binding domain (RBD) but exhibits limited expansion compared to its parallel descendant JN.1. Here, we investigate how hydrophobic remodeling within RBD large loop (residues 475-490) modulates receptor engagement and spike function. Cryo-electron microscopy reveals that A475V induces local remodeling of the receptor-binding motif (RBM) and alters the RBD-ACE2 interaction geometry. Local refinement revealed that the bulky valine substitution disrupts the local interaction network surrounding residue 475, resulting in a 3.5-fold reduction in ACE2-binding affinity compared with BA.2.86. In contrast to the L455S substitution in JN.1, which primarily alters the receptor-binding interface, A475V within the flexible large loop influences both local loop conformation and global spike conformational properties. Systematic mutagenesis identifies A475 and F486 as functionally constrained hydrophobic residues that preserve the structural framework of ACE2 engagement despite extensive sequence variation within the surrounding loop. Together with molecular dynamics simulations and functional assays, our findings establish the RBD 475-490 large loop as a structurally plastic yet functionally constrained element that balances receptor recognition, conformational stability, and antigenic diversification. These results provide a mechanistic framework for understanding region-specific evolutionary constraints that shape SARS-CoV-2 RBD adaptation.
Authors
- Bin Ju (ORCID: https://orcid.org/0000-0003-0768-6327)
- Anna Imojara (ORCID: https://orcid.org/0000-0002-3954-1889)
- Renhong Yan (ORCID: https://orcid.org/0000-0002-7122-6547)
- Zheng Zhang (ORCID: https://orcid.org/0000-0002-3544-1389)
- He Yang
- Aojie Wang
- Huimin Guo
- Haojin Chen
Institutions
- South China Agricultural University (CN)
- Austrian Research Institute for Artificial Intelligence (AT)
- Southern University of Science and Technology (CN)
- Ministry of Agriculture and Rural Affairs (CN)
- Artificial Intelligence in Medicine (Canada) (CA)
- Shenzhen Third People’s Hospital (CN)
- Shenzhen Medical Academy of Research and Translation (CN)
Publication Details
- Journal
- PLoS Pathogens
- Published
- 2026-10-26
- DOI
- https://doi.org/10.1371/journal.ppat.1014742
- Primary Topic
- SARS-CoV-2 and COVID-19 Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- Southern University of Science and Technology
- Basic and Applied Basic Research Foundation of Guangdong Province