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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.

Zika virus (ZIKV) caused explosive epidemics across the Americas, starting in Brazil in 2015, and has been associated with severe manifestations such as microcephaly in babies born to infected mothers and Guillain-Barré syndrome in adults. As the underlying mechanisms of pathogenesis remain largely unknown, diverse investigations have focused on a potential role for flavivirus cross-reactive antibodies in enhancing ZIKV infection. Antibody-dependent enhancement is especially concerning due to structural similarities between ZIKV and other flaviviruses, especially dengue virus (DENV), that co-circulate in areas affected by ZIKV. Conversely, investigating cross-neutralizing antibodies is important for understanding protection among flaviviruses, including ZIKV. In this review, we discuss the latest findings regarding ZIKV-induced adaptive immunity, such as monoclonal and polyclonal antibody responses, structural immunology, and T cell-mediated responses. Much progress has been made in a short amount of time, but many questions remain. Fully understanding the specificity, magnitude, and kinetics of B cell/antibody and T cell responses in ZIKV-infected individuals with or without prior exposure to flaviviruses is of great relevance for diagnostics and vaccine development.

The T cell costimulatory molecule TIM-1 (T cell/transmembrane, mucin and immunoglobulin domain protein 1) sorts mainly to endosomes in lymphoid cells. At difference from the cell surface protein, endosomal TIM-1 translocates to the immune synapse (IS), where it can contribute to antigen-dependent T cell costimulation. TIM-1 ligands increase the amount of cell surface protein, preventing its traffic to the IS. The bipolar sorting of TIM-1 observed during IS formation is determined by differences in its subcellular location, and probably modulates antigen-driven immune responses.

The antibody crystallizable fragment (Fc) is recognized by effector proteins as part of the immune system. Pathogens produce proteins that bind Fc in order to subvert or evade the immune response. The structural characterization of the determinants of Fc–protein association is essential to improve our understanding of the immune system at the molecular level and to develop new therapeutic agents. Furthermore, Fc-binding peptides and proteins are frequently used to purify therapeutic antibodies. Although several structures of Fc–protein complexes are available, numerous others have not yet been determined. Protein–protein docking could be used to investigate Fc–protein complexes; however, improved approaches are necessary to efficiently model such cases. In this study, a docking-based structural bioinformatics approach is developed for predicting the structures of Fc–protein complexes. Based on the available set of X-ray structures of Fc–protein complexes, three regions of the Fc, loosely corresponding to three turns within the structure, were defined as containing the essential features for protein recognition and used as restraints to filter the initial docking search. Rescoring the filtered poses with an optimal scoring strategy provided a success rate of approximately 80% of the test cases examined within the top ranked 20 poses, compared to approximately 20% by the initial unrestrained docking. The developed docking protocol provides a significant improvement over the initial unrestrained docking and will be valuable for predicting the structures of currently undetermined Fc–protein complexes, as well as in the design of peptides and proteins that target Fc. This work was supported by grant number BIO2013‐48213‐R from Spanish Government. M.A. is a recipient of an NHMRC Early Career Fellowship (GNT1054245). We acknowledge the computational resources provided by the Australian Government through the Victorian Life Sciences Computational Initiative under the National Computational Merit Allocation Scheme (project dq3). The authors gratefully acknowledge the contribution toward this study fromthe VictorianOperational Infrastructure Support Program received by the Burnet Institute.