A Reproducible Sequence-Level Strategy to Enhance Peptide Immunogenicity While Preserving Wild-Type Epitope Recognition

<b>Background:</b> Short peptide epitopes are valuable for mechanistic studies, yet their intrinsic low immunogenicity and lack of commercial antibodies hinder rapid antibody generation. <b>Methods:</b> We developed a reproducible, sequence-level workflow combining cross-species/structural triage, independent MHC-I/II prioritization, and conservative heteroclitic-style substitutions to enhance predicted MHC affinity while preserving native epitope features. Using visfatin as a model, two optimized fragments were conjugated to KLH and tested in mice for antibody titers, isotype profiles, and binding kinetics. <b>Results:</b> Mutant peptides improved MHC-binding prediction, elicited stronger antibody titers, and promoted isotype maturation (increased IgG1). Importantly, antibodies maintained measurable binding to wild-type sequences, indicating preserved cross-recognition. Similar effects were reproduced with additional antigens. <b>Conclusions:</b> This proof-of-concept study, based on small exploratory mouse cohorts (<i>n</i> = 3 per group), demonstrates that strategic, minimal sequence edits can significantly enhance peptide immunogenicity while preserving native epitope recognition. This streamlined workflow provides a low-barrier route to generate epitope-directed antibodies when commercial reagents are unavailable.