scholarly journals Accurate Prediction of Immunogenic T-Cell Epitopes from Epitope Sequences Using the Genetic Algorithm-Based Ensemble Learning

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0128194 ◽  
Author(s):  
Wen Zhang ◽  
Yanqing Niu ◽  
Hua Zou ◽  
Longqiang Luo ◽  
Qianchao Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
T Cell ◽  
Ensemble Learning ◽  
Accurate Prediction ◽  
T Cell Epitopes

HLA-B*27 subtype specificity determines the targeting of HLA-B*27 restricted HCV-specific CD8+ T cell epitopes

2013 ◽  
Vol 51 (01) ◽  
Author(s):  
K Nitschke ◽  
J Schmidt ◽  
HE Blum ◽  
R Thimme ◽  
C Neumann-Haefelin
Keyword(s):  
T Cell ◽  
Cd8 T Cell ◽  
T Cell Epitopes ◽  
Subtype Specificity

Use of T Cell Epitopes for Vaccine Development

2001 ◽  
Vol 1 (3) ◽  
pp. 303-313 ◽  
Author(s):  
H. Sbai ◽  
A. Mehta ◽  
A. DeGroot
Keyword(s):  
T Cell ◽  
Vaccine Development ◽  
T Cell Epitopes

Prediction of Prophylactic Peptide Vaccine Candidates for Human Papillomavirus (HPV): An Immunoinformatics and Reverse Vaccinology Approach

2020 ◽  
Vol 17 ◽  
Author(s):  
Mehreen Ismail ◽  
Zureesha Sajid ◽  
Amjad Ali ◽  
Xiaogang Wu ◽  
Syed Aun Muhammad ◽  
...  
Keyword(s):  
T Cells ◽  
Human Papillomavirus ◽  
T Cell ◽  
Binding Affinity ◽  
Cd8 T Cells ◽  
Reverse Vaccinology ◽  
Host Immune System ◽  
T Cell Epitopes ◽  
Multiple Alleles ◽  
Vaccine Candidates

Background: Human Papillomavirus (HPV) is responsible for substantial morbidity and mortality worldwide. We predicted immunogenic promiscuous monovalent and polyvalent T-cell epitopes from the polyprotein of the Human Papillomavirus (HPV) using a range of bioinformatics tools and servers. Methods: We used immunoinformatics and reverse vaccinology-based approaches to design prophylactic peptides by antigenicity analysis, Tcell epitopes prediction, proteasomal and conservancy evaluation, host-pathogen protein interactions, and in silico binding affinity analysis. Results: We found two early proteins (E2 and E6) and two late proteins (L1 and L2) of HPV as potential vaccine candidates. Of these proteins (E2, E6, L1 & L2), 2-epitopes of each candidate protein for multiple alleles of MHC class I and II bearing significant binding affinity (>-6.0 kcal/mole). These potential epitopes for CD4+ and CD8+ T-cells were also linked to design polyvalent construct using GPGPG linkers. Cholera toxin B and mycobacterial heparin-binding hemagglutinin adjuvant with a molecular weight of 12.5 and 18.5 kDa were used for epitopes of CD4+ and CD8+ T-cells respectively. The molecular docking indicated the optimum binding affinity of HPV peptides with MHC molecules. This interaction showed that our predicted vaccine candidates are suitable to trigger the host immune system to prevent HPV infections. Conclusion: The predicted conserved T-cell epitopes would contribute to the imminent design of HPV vaccine candidates, which will be able to induce a broad range of immune-responses in a heterogeneous HLA population.

Immuno-informatics-based identification of novel potential B cell and T cell epitopes to fight Zika virus infections

2020 ◽  
Vol 20 ◽  
Author(s):  
Wahiba Ezzemani ◽  
Marc P. Windisch ◽  
Anass Kettani ◽  
Haya Altawalah ◽  
Jalal Nourlil ◽  
...  
Keyword(s):  
Major Histocompatibility Complex ◽  
T Cell ◽  
Major Histocompatibility Complex Class ◽  
B Cell ◽  
Zika Virus ◽  
T Cell Epitopes ◽  
Complex Class ◽  
Major Histocompatibility ◽  
Virus Infections ◽  
Histocompatibility Complex

Background: Globally, the recent outbreak of Zika virus (ZIKV) in Brazil, Asia Pacific, and other countries highlighted the unmet medical needs. Currently, there are neither effective vaccines nor therapeutics available to prevent or treat ZIKV infection. Objective: In this study, we aimed to design an epitope-based vaccine for ZIKV using an in silico approach to predict and analyze B- and T-cell epitopes. Methods: The prediction of the most antigenic epitopes has targeted the capsid and the envelope proteins as well as nonstructural proteins NS5 and NS3 using immune-informatics tools PROTPARAM, CFSSP, PSIPRED, and Vaxijen v2.0. B and T-cell epitopes were predicted using ABCpred, IEDB, TepiTool, and their toxicity were evaluated using ToxinPred. The 3-dimensional epitope structures were generated by PEP-FOLD. Energy minimization was performed using Swiss-Pdb Viewer, and molecular docking was conducted using PatchDock and FireDock server. Results: As a result, we predicted 307 epitopes of MHCI (major histocompatibility complex class I) and 102 epitopes of MHCII (major histocompatibility complex class II). Based on immunogenicity and antigenicity scores, we identified the four most antigenic MHC I epitopes: MVLAILAFLR (HLA-A*68 :01), ETLHGTVTV (HLA-A*68 :02), DENHPYRTW (HLA-B*44 :02),QEGVFHTMW (HLA-B*44 :03) and TASGRVIEEW (HLA-B*58:01), and MHC II epitopes: IIKKFKKDLAAMLRI (HLA-DRB3*02 :02), ENSKMMLELDPPFGD (HLA-DRB3*01:01), HAETWFFDENHPYRT (HLA-DRB3*01:01), TDGVYRVMTRRLLGS (HLA-DRB1*11 :01), and DGCWYGMEIRPRKEP (HLA-DRB5*01:01). Conclusion : This study provides novel potential B cell and T cell epitopes to fight Zika virus infections and may prompt further development of vaccines against ZIKV and other emerging infectious diseases. However, further investigations for protective immune response by in vitro and in vivo studies to ratify the immunogenicity, safety of the predicted structure, and ultimately the vaccine properties to prevent ZIKV infections are warranted.

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