AbstractThe human immunodeficiency virus-(HIV) is group of the genus Lentivirus within the family of Retroviridae, subfamily Ortho retrovirinae. Based on genetic characteristics and differences in the viral antigens, HIV is classified into the types 1 and 2 (HIV-1, HIV-2). HIV is identical single – stranded RNA molecule that are enclosed within the core of the virus particle proteins, the genome of the HIV Provirus, also known as DNA, is generated by the Protease against reverse transcriptase RNA genome into DNA, degradation of the RNA and integration of the double – stranded HIV DNA into the human genome. The aim of this study is to determine antigenic peptides from p10, p21, and p51 proteins that can be used for multiple peptide vaccine design using In-Silico study. A total of 73 sequences of three proteins were obtained from NCBI and subjected to multiple sequence alignments using CLUSTALW tool to determine conserved regions.Immune Epitope Data Base tools were used to determine B cell epitopes, these tools are Bepipred Linear B cell epitopes prediction, surface accessibility and antigenicity prediction. Epitope binding to MHC class I and class II and their population coverage were also determined using IEDB software. The analysis results are as follow, for B cell binding from p10 (708QGYSP712), from p21 (704QGYSP708, 73CVPTDPNPQ81) and (346“FKNL349) from p51. All these peptides have high score in Linear B cell epitopes prediction, surface accessibility and antigenicity prediction. On another hand peptides that reacted to MHC class I were (47EANTTLFCA55, 53FCASDAKAY61, 55,ASDAKAYET63) form p10,(38YYGVPVWKE46, 10PQEVFLVNV18 and 29AAGSTMGAA37) from p21 and (63“EWEFVNTPP71, 70PPLVKLWYQ78 and 79EKEPIVGA87) from p51 protein respectively. It worth noting that the peptides (119IISLWDQSL127,108CVKLTPLCV116) from p10, (38YYGVPVWKE46, 20LLQYWSQEL34, 16FNMWKNNMV30) from p21 and (7WKGSPAIFQ21, 11WEFVNTPPL25 and 58 FLWMGYELH72) protein is also binds to MHC class II with high affinity. All T cell peptides had highest population coverage, and the combined coverage for all peptides in this study was found to be 100%. Using In-Silico studies will ensure less risk of virulence and side effects. Evaluation of antibodies response in animal models is needed to confirm efficacy of these epitopes in inducing protective immune response.
In Silico Prediction of Linear B-Cell Epitopes on Proteins