scholarly journals Delineating blueprint of an epitope-based peptide vaccine against the multiple serovars of dengue virus: A hierarchical reverse vaccinology approach

2020 ◽  
Vol 20 ◽  
pp. 100430
Author(s):  
Rahatul Islam ◽  
Md Sorwer Alam Parvez ◽  
Saeed Anwar ◽  
Mohammad Jakir Hosen
Keyword(s):  
Dengue Virus ◽  
Peptide Vaccine ◽  
Reverse Vaccinology

scholarly journals EpitoCore: mining conserved epitope vaccine candidates in the core proteome of multiple bacteria strains

2019 ◽  
Author(s):  
T.S. Fiuza ◽  
J.P.M.S. Lima ◽  
G.A. de Souza
Keyword(s):  
Peptide Vaccine ◽  
Computational Prediction ◽  
Reverse Vaccinology ◽  
Automated Identification ◽  
Single Strain ◽  
Vaccine Candidates ◽  
The Core ◽  
Core Proteins ◽  
Conserved Genes ◽  
Core Proteome

ABSTRACTIn reverse vaccinology approaches, complete proteomes of bacteria are submitted to multiple computational prediction steps in order to filter proteins that are possible vaccine candidates. Most available tools perform such analysis only in a single strain, or a very limited number of strains. But the vast amount of genomic data had shown that most bacteria contain pangenomes, i.e. their genomic information contains core, conserved genes, and random accessory genes specific to each strain. Therefore, it is of the utmost importance to define core proteins, and also core epitopes, in reverse vaccinology methods. EpitoCore is a decision-tree pipeline developed to fulfill that need. It provides surfaceome prediction of proteins from related strains, defines clusters of core proteins within those, calculate the immunogenicity of such clusters, predicts epitopes for a given set of MHC alleles defined by the user, and then reports if epitopes are located extracellularly and if they are conserved among the core homologues. Pipeline performance is illustrated by mining peptide vaccine candidates in Mycobacterium avium hominissuis strains. From a total proteome of approximately 4,800 proteins per strain, EpitoCore mined 103 highly immunogenic core homologues located at cell surface, many of those related to virulence and drug resistance. Conserved epitopes identified among these homologues allows the users to define sets of peptides with potential to immunize the largest coverage of tested HLA alleles using peptide-based vaccines. Therefore, EpitoCore is able to provide automated identification of conserved epitopes in bacterial pangenomic datasets.

Epitope Prediction for Peptide Vaccine Against Chikungunya and Dengue Virus, Using Immunoinformatics Tools

2021 ◽  
pp. 213-237
Author(s):  
Krishna S. Gayatri ◽  
Geethu Gopinath ◽  
Bhawana Rathi ◽  
Anupama Avasthi
Keyword(s):  
Dengue Virus ◽  
Peptide Vaccine ◽  
Epitope Prediction

scholarly journals In silico prediction of b-cell epitopes of dengue virus – A reverse vaccinology approach

2020 ◽  
Author(s):  
Mohan Manikandan ◽  
Shanmugaraja Prabu ◽  
Krishnan Rajeswari ◽  
Rajagopalan Kamaraj ◽  
Sundar Krishnan
Keyword(s):  
Dengue Virus ◽  
B Cell ◽  
In Silico ◽  
Reverse Vaccinology ◽  
In Silico Prediction ◽  
B Cell Epitopes

scholarly journals Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

2018 ◽  
Author(s):  
Mahmudul Hasan ◽  
ProggaParomita Ghosh ◽  
KaziFaizul Azim ◽  
Shamsunnahar Mukta ◽  
Ruhshan Ahmed Abir ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Avian Influenza ◽  
Influenza A ◽  
Subunit Vaccine ◽  
Peptide Vaccine ◽  
Reverse Vaccinology ◽  
Cell Mediated Immunity ◽  
Viral Pathogen ◽  
Mhc Molecules ◽  
Cell Immunity

AbstractH7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, hydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted forE. colistrain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.

MAGE-3 Peptide Vaccine

2020 ◽  
Author(s):  
Keyword(s):  
Peptide Vaccine
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