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Prediction of cross‐clade HIV‐1 T‐cell epitopes using immunoinformatics analysis
Author(s) -
Khairkhah Niloofar,
Namvar Ali,
Kardani Kimia,
Bolhassani Azam
Publication year - 2018
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.25609
Subject(s) - epitope , human leukocyte antigen , biology , docking (animal) , peptide vaccine , virology , population , computational biology , antigen , genetics , medicine , nursing , environmental health
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.