Abstract:
Vaccines remain the most efficacious means to avoid and eliminate morbid
diseases associated with high morbidity and mortality. Clinical trials indicate the gaining
impetus of peptide vaccines against diseases for which an effective treatment still remains
obscure. CD4 T-cell-based peptide vaccines involve immunization with antigenic
determinants from pathogens or neoplastic cells that possess the ability to elicit a robust
T helper cell response, which subsequently activates other arms of the immune system.
The available in silico predictors of human leukocyte antigen II (HLA-II) binding
peptides are sequence-based techniques, which ostensibly have balanced sensitivity and
specificity. Structural analysis and understanding of the cognate peptide and HLA-II
interactions are essential to empirically derive a successful peptide vaccine. However, the
availability of structure-based epitope prediction algorithms is inadequate compared with
sequence-based prediction methods. The present study is an attempt to understand the
structural aspects of HLA-II binders by analyzing the Protein Data Bank (PDB)
complexes of pHLA-II. Furthermore, we mimic the peptide exchange mechanism and demonstrate the structural implication of an
acidic environment on HLA-II binders. Finally, we discuss a structure-guided approach to decipher potential HLA-II binders within
an antigenic protein. This strategy may accurately predict the peptide epitopes and thus aid in designing successful peptide vaccines
