The long-term value of efficient antigen discovery includes gaining insights into the variety of potential cancer neoantigens, effective vaccines lacking adverse effects, and adaptive immune receptor (IR) targets for blocking adaptive IR-antigen interactions in autoimmunity. While the preceding goals have been partially addressed via big data approaches to HLA-epitope binding, there has been little such progress in the big data setting for adaptive IR-epitope binding. This delay in progress for the latter is likely due to, among other things, the much more complicated adaptive IR repertoire in an individual compared to individual HLA alleles. Thus, results described here represent the application of an algorithm for efficient assessment of IGH CDR3-gliadin epitope interactions, with a focus on epitopes known to be associated with an immune response in celiac disease. The hydrophobic, chemical complementarity between celiac case IGH CDR3s and known celiac epitopes was found to be greater in comparison to the hydrophobic, chemical complementarity between the same celiac case IGH CDR3s and a series of control epitopes. Thus, the approaches indicated here likely offer guidance for the development of conveniently applied algorithms for antigen verification and discovery.
Keywords: adaptive immune receptor recombinations; celiac disease antigen; complementarity determining region-3; hydrophobic chemical complementarity.
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