Applications of Protein Folding Models in Immunotherapeutic Research

Advances in protein folding and structure prediction models have enabled new computational approaches to immunotherapeutic research by providing access to high-quality structural information at scale. In this talk, we present three core application areas. (1) Antigen structure prediction, where folding models are used to characterize the three-dimensional structure of viral, tumor-associated, and neoantigen targets in the absence of experimental data. (2) Antibody–antigen complex prediction, where multimeric and joint modeling approaches are leveraged to infer binding modes, paratope–epitope interactions, and structural determinants of specificity. (3) Immunogenicity prediction, where predicted structures are analyzed to assess surface accessibility, conformational stability, and geometric features that influence immune recognition. Together, these applications illustrate how protein folding models function not only as structure predictors, but as foundational components in quantitative pipelines for immunotherapeutic discovery and design.