Statistical physics model of vaccine design for mutating diseases

We propose a statistical physics model to study vaccine design for mutating diseases. The naive and memory T-cell immune response is represented by a random-energy-type model, the generalized NK model. Two different vaccines are designed by using different numbers of an epitope, which is about a nine-amino-acid-long peptide chain recognized by T-cells. A single-epitope vaccine contains only one epitope, and a multiple-epitope vaccine contains several similar epitopes differing by only one or two amino acids from each other. Using the generalized NK model, we calculate the specific (-)lysis of the memory T-cell immune responses against mutating diseases with the single-epitope vaccine and the multiple-epitope vaccine and find that for slowly mutating diseases, the single-epitope vaccine is more effective than the multiple-epitope vaccine while for rapidly mutating diseases, the multiple-epitope is more effective. The results may provide guidance for the process of experimental multi-component vaccine development against mutating viral diseases.