From Contact to Context: A Comprehensive Approach to Epitope Characterization and Similarity Scoring

Abstract

Epitopes play a crucial role in antibody-based diagnostics and therapeutics, making their accurate char- acterization essential for assessing off-target effects and antigen similarity. In this study, we present a comprehensive framework for epitope characterization and similarity scoring that integrates structural, sequence, and physicochemical data. To identify epitope-like regions on protein surfaces, we employed structural similarity methods such as TM-align. Our approach incorporates two distinct epitope char- acterization strategies: a distance-based method, where epitopes are defined by their proximity to the paratope, and a patch-based approach, which represents epitopes as regions on the antigen’s molecular surface. Our findings demonstrate that combining sequence and physicochemical features with structural similarity provides a more accurate assessment of potential cross-reactivity. This approach enables sys- tematic evaluation of epitope similarity, aiding in the identification of closely related or distinct antigens. Furthermore, our framework supports the development of diverse training datasets for predictive mod- eling, ultimately improving the reliability of antibody design and reducing unintended immune responses.