Predicting Antibody and ACE2 Affinity for SARS-CoV-2 BA.2.86 with In Silico Protein Modeling and Docking

The emergence of the Omicron sublineage of SARS-CoV-2 virusBA.2.86 (nicknamed “Pirola”) has raised concerns about its potentialimpact on public health and personal health as it hasmany mutations with respect to previous variants. We conductedan in silico analysis of neutralizing antibody binding toBA.2.86. Selected antibodies came from patients who were vaccinatedand/or infected. We predicted binding affinity betweenBA.2.86 and antibodies. We also predicted the binding affinitybetween the same antibodies and several previous SARS-CoV-2 variants (Wuhan and Omicron descendants BA.1, BA.2, andXBB.1.5). Additionally, we examined binding affinity betweenBA.2.86 and human angiotensin converting enzyme 2 (ACE2)receptor, a cell surface protein crucial for viral entry. We foundno statistically significant difference in binding affinity betweenBA.2.86 and other variants, indicating a similar immune response.These findings contradict media reports of BA.2.86’shigh immune evasion potential based on its mutations. We discussthe implications of our findings and highlight the need formodeling and docking studies to go above and beyond mutationand basic serological neutralization analysis. Future researchin this area will benefit from increased structural analyses ofmemory B-cell derived antibodies and should emphasize the importanceof choosing appropriate samples for in silico studies toassess protection provided by vaccination and infection. Thisresearch contributes to understanding the BA.2.86 variant’s potentialimpact on public health. Moreover, we introduce newmethodologies for predictive medicine in ongoing efforts to combatthe evolving SARS-CoV-2 pandemic and prepare for otherhazards.