Computational prioritization of RBD-targeting nanobodies across SARS-CoV-2 Omicron sublineages, followed by rational biparatopic design and targeted experimental validation.

Publication date: Jul 23, 2026

The ongoing evolution of SARS-CoV-2, particularly Omicron sublineages harboring extensive RBD mutations, compromises the effectiveness of many existing neutralizing nanobodies. Here, we present an integrated computational-experimental framework to prioritize nanobodies with favorable predicted interaction profiles across mutated RBD backgrounds and to explore their potential for biparatopic engineering. Thirty-two nanobody-RBD complexes from the Protein Data Bank were computationally screened across eight Omicron sublineages (BA. 1-XBB. 1.5). Selected nanobodies were then further evaluated against the Wuhan reference strain and XBB. 1.5-the predominant sublineage at the onset of laboratory testing-using molecular simulations and conventional virus neutralization tests (cVNTs) performed in three biological replicates. These analyses led to the prioritization of MR17 and Sb14. In subsequent cVNT assays, MR17 showed a significantly higher neutralization titer against XBB. 1.5 than against the Wuhan reference strain, whereas Sb14 showed comparable titers against both targets. A biparatopic Sb14-MR17 construct exhibited a significantly higher neutralization titer against XBB. 1.5 than either monomeric nanobody. In addition, the interaction profiles of selected candidates with the emerging NB. 1.8. 1 RBD were evaluated computationally. Collectively, these results highlight multi-sublineage computational triage, together with targeted experimental validation, as a practical strategy for prioritizing nanobody candidates under ongoing SARS-CoV-2 antigenic drift.

Semantics

Original Article