Prediction of cross-clade HIV-1 T-cell epitopes using immunoinformatics analysis

Epitope mapping has emerged as a powerful tool to develop peptide vaccines against hypervariable viruses such as HIV. This method has led to stimulate a specific immune response and achieve advanced vaccine formulations. In this study, we identified peptides that were potentially immunostimulatory and highly conserved in HIV-1 main group. The analyses included were CTL assay, Tap transport, and the potential allergenicity. The highest population coverage rate was also found for all potential T-cell epitopes in 16 specified geographic regions of the world. The current study is the first attempt to explore peptide-protein flexible docking across all the major epitopes of HIV-1. Our data indicated that REV^54-63 and VPU^58-66 with the highest epitope identification scores, GP160^37-46 and VPR^38-47 with the highest conservation (98.89%), and NEF^134-144 and GP160^37-46 epitopes with a higher quality of peptide-protein interaction models in docking procedure were chosen as putative epitopes among all HLA class I epitopes. TAT^40-67 , VPR^65-82 , and VPU^30-44 with the highest score of binding affinity, VPR^65-82 with the highest conservation (97.55%), and GP160^481-498 epitope with a higher quality of peptide-protein interaction models in docking procedure were determined as putative epitopes among all HLA-DR epitopes. Furthermore, two epitopes of GP160^481-498 and VIF^144-159 were predicted to bind 22 and 21 HLA-II alleles, respectively. Accumulative population coverage of potential helper T-cell epitopes and CTL epitopes varied between 90.82% and 100%. Generally, these predicted highly immunogenic T-cell epitopes can contribute to design HIV-1 peptide vaccine candidates. Combination of bioinformatics tools with in vivo methods will be necessary for HIV-1 vaccine development.