Immunoinformatics: The Next Step in Vaccine Design

Cohen, Tobias; Moise, Lenny; Martin, William; Groot, Anne S. De

doi:10.1007/978-1-4419-1327-2_11

Cited by 6 publications

(4 citation statements)

References 99 publications

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“…The epitopes predicted in this study could become a clinical candidate sooner or later for the treatment of HPVs infection and cervical cancer, as epitopes such as KLPQLCTEL 18-26 and FAFRDLCIV 52-60 of E6 proteins, have been tested in a transgenic mice for IC 50 value which resulted in immune response in experimental conditions [ 67 ]. Previous studies already verified that peptide FAFRDLCIVYR 52-62 possess antitumor effect and is reported to be processed by T-cell endogenously [ 68 , 69 ]. The current study predicted epitopes for the E6 proteins, which also contain regions from epitope, such as FAFRDLCIVYR 52-62 , thus increasing the accuracy and validating our study to be taken to the experimental room.…”

Section: Discussionmentioning

confidence: 91%

Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches

Khan¹,

Junaid²,

Kaushik³

et al. 2018

PLoS ONE

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High-risk human papillomaviruses (hrHPVs) are the most prevalent viruses in human diseases including cervical cancers. Expression of E6 protein has already been reported in cervical cancer cases, excluding normal tissues. Continuous expression of E6 protein is making it ideal to develop therapeutic vaccines against hrHPVs infection and cervical cancer. Therefore, we carried out a meta-analysis of multiple hrHPVs to predict the most potential prophylactic peptide vaccines. In this study, immunoinformatics approach was employed to predict antigenic epitopes of hrHPVs E6 proteins restricted to 12 Human HLAs to aid the development of peptide vaccines against hrHPVs. Conformational B-cell and CTL epitopes were predicted for hrHPVs E6 proteins using ElliPro and NetCTL. The potential of the predicted peptides were tested and validated by using systems biology approach considering experimental concentration. We also investigated the binding interactions of the antigenic CTL epitopes by using docking. The stability of the resulting peptide-MHC I complexes was further studied by molecular dynamics simulations. The simulation results highlighted the regions from 46–62 and 65–76 that could be the first choice for the development of prophylactic peptide vaccines against hrHPVs. To overcome the worldwide distribution, the predicted epitopes restricted to different HLAs could cover most of the vaccination and would help to explore the possibility of these epitopes for adaptive immunotherapy against HPVs infections.

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Section: Discussionmentioning

confidence: 91%

Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches

Khan¹,

Junaid²,

Kaushik³

et al. 2018

PLoS ONE

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“…T-cells are reported to be mediators exhibiting competent immune responses elicited by the target vaccine. 15 Such reports have catalyzed research into and development of in silico immunoinformatics methods for further exploring T-cell epitopes in peptide sequences. 16 The first step in vaccine designing to identify the T-cell epitope is to determine which peptide of the proteome of the virulent bacterial pathogen will bind to the major histocompatibility complex (MHC) molecules.…”

Section: Introductionmentioning

confidence: 99%

Computer-aided vaccine designing approach against fish pathogens Edwardsiella tarda and Flavobacterium columnare using bioinformatics softwares

Mahendran

Suganya

Sitharaman

et al. 2016

DDDT

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Edwardsiella tarda and Flavobacterium columnare are two important intracellular pathogenic bacteria that cause the infectious diseases edwardsiellosis and columnaris in wild and cultured fish. Prediction of major histocompatibility complex (MHC) binding is an important issue in T-cell epitope prediction. In a healthy immune system, the T-cells must recognize epitopes and induce the immune response. In this study, T-cell epitopes were predicted by using in silico immunoinformatics approach with the help of bioinformatics tools that are less expensive and are not time consuming. Such identification of binding interaction between peptides and MHC alleles aids in the discovery of new peptide vaccines. We have reported the potential peptides chosen from the outer membrane proteins (OMPs) of E. tarda and F. columnare, which interact well with MHC class I alleles. OMPs from E. tarda and F. columnare were selected and analyzed based on their antigenic and immunogenic properties. The OMPs of the genes TolC and FCOL_04620, respectively, from E. tarda and F. columnare were taken for study. Finally, two epitopes from the OMP of E. tarda exhibited excellent protein–peptide interaction when docked with MHC class I alleles. Five epitopes from the OMP of F. columnare had good protein–peptide interaction when docked with MHC class I alleles. Further in vitro studies can aid in the development of potential peptide vaccines using the predicted peptides.

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“…Modern immunoinformatics tools provide the new platform for designing peptide vaccines against pathogenic microorganisms [33]. Though many tools are available for predicting immunogenic CTL epitopes, the accuracy of any of these tools is not appreciative.…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Prediction of Human Papilloma Virus Specific T-Cell Epitopes Using a Combination of Matrix Based Computational Tools

Mohan

Sundar

2017

Int J Pharm Pharm Sci

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Objective: To predict the immunogenic epitopes from human papillomavirus (HPV) virus using matrix based computational tools. Methods:In the present study, three matrix based algorithms, SYFPETHI, BIMAS and RANKPEP were used to predict the cytotoxic T lymphocyte (CTL) epitopes of HPV 16 and 18. The ability of the peptides to bind HLA A_0201, a most common allele, was evaluated using these algorithms. High scoring peptides were considered as potential binders.Results: Evaluation of HPV 16 proteome resulted in the prediction of 249 peptides as potential binders. Out of these only 25 peptides were predicted as binders by all three algorithms. Analysis of HPV 18 predicted 215 peptides, as potential binders. Among the 215 peptides only 20 peptides were predicted as binders by all three algorithms. Conclusion:The efficacy of these peptides in inducing a stronger immune response needs to be tested using in vitro and in vivo assays. The identified epitopes could be used in designing a novel epitope vaccine for HPV.

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Immunoinformatics: The Next Step in Vaccine Design

Cited by 6 publications

References 99 publications

Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches

Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches

Computer-aided vaccine designing approach against fish pathogens Edwardsiella tarda and Flavobacterium columnare using bioinformatics softwares

Genome-Wide Prediction of Human Papilloma Virus Specific T-Cell Epitopes Using a Combination of Matrix Based Computational Tools

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