Intelligent Batch Epitope Identification and Partitioning: an intelligent tool for the identification of B cell dominant epitopes.

Abstract

Identifying B cell dominant epitopes helps to improve vaccine design and better understand immune evasion of pathogens. Herein, we present the Intelligent Batch Epitope Identification and Partitioning (IBEIP), an intelligent tool for identifying B cell dominant epitope regions based on antigen-neutralizing antibody (Ag-nAb) complex data. IBEIP can accurately map the epitopes on any appointed Ag-nAb complex by analyzing antigen-antibody interactions at a molecular level. Combined with a hierarchical iterative merging model, IBEIP can intelligently merge and analyze mapped epitopes to identify B cell dominant epitopes. It is also applicable to analyzing high-mutant antigens and complex epitope structures. We demonstrated the performance of IBEIP by analyzing 127 Ag-nAb complexes from the respiratory syncytial virus (RSV) fusion, SARS-CoV-2 spike, and high-mutant influenza hemagglutinin. Over 90% of the residues overlapped between IBEIP and reported epitopes, confirming its reliability. IBEIP also uncovered new and important B cell dominant epitope regions and structures of these pathogens for researchers. Our study provides a reliable, intelligent tool for B cell dominant epitope analysis and offers some valuable insights for preventing RSV, SARS-CoV-2, and influenza infections.