Predicting and Designing Epitope Ensemble Vaccines against HTLV-1

Autor: Alam Saruar, Hasan Md. Kamrul, Manjur Omar Hamza Bin, Khan Akib Mahmud, Sharmin Zinat, Pavel Mahmud Arif, Hossain Md. Faruk
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Integrative Bioinformatics, Vol 16, Iss 4, Pp 69-73 (2020)
Druh dokumentu: article
ISSN: 1613-4516
DOI: 10.1515/jib-2018-0051
Popis: The infection mechanism and pathogenicity of Human T-lymphotropic virus 1 (HTLV-1) are ambiguously known for hundreds of years. Our knowledge about this virus is recently emerging. The purpose of the study is to design a vaccine targeting the envelope glycoprotein, GP62, an outer membrane protein of HTLV-1 that has an increased number of epitope binding sites. Data collection, clustering and multiple sequence alignment of HTLV-1 glycoprotein B, variability analysis of envelope Glycoprotein GP62 of HTLV-1, population protection coverage, HLA-epitope binding prediction, and B-cell epitope prediction were performed to predict an effective vaccine. Among all the predicted peptides, ALQTGITLV and VPSSSTPL epitopes interact with three MHC alleles. The summative population protection coverage worldwide by these epitopes as vaccine candidates was found nearly 70%. The docking analysis revealed that ALQTGITLV and VPSSSTPL epitopes interact strongly with the epitope-binding groove of HLA-A*02:03, and HLA-B*35:01, respectively, as this HLA molecule was found common with which every predicted epitope interacts. Molecular dynamics simulations of the docked complexes show they form stable complexes. So, these potential epitopes might pave the way for vaccine development against HTLV-1.
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