Literature DB >> 27596531

In-silico Hierarchical Approach for the Identification of Potential Universal Vaccine Candidates (PUVCs) from Neisseria gonorrhoeae.

Ravi Jain1, Subash C Sonkar2, Uma Chaudhry1, Manju Bala3, Daman Saluja4.   

Abstract

OBJECTIVES: Resistance to the currently recommended extended-spectrum cephalosporins, which is used to treat Gonorrhea, is increasing continuously and leading to a threat of untreatable infection. It is, therefore, becoming extremely essential to search for new therapeutic strategies to control Gonorrhea. Vaccination may be considered as an effective control measure to control this disease, which is caused by Neisseria gonorrhoeae.
METHODS: In-silico hierarchical approach was used to help identify candidate proteins of N. gonorrhoeae that might contribute significantly in vaccine research. In contrast to the conventional vaccine research which requires at least 10-12 years, the present approach would reduce the time period drastically and help to identify Potential Universal Vaccine Candidates (PUVCs). These proteins were further analyzed for the presence of T-cell and linear B-cell epitopes, by using HLAPred and ABCpred servers respectively, in order to facilitate the identification of Multi Epitope Peptide Vaccine Constructs.
RESULTS: We have identified 23 non-host candidate proteins, using the proteomic information of four sequenced strains of N. gonorrhoeae namely FA 1090, TCDC_NG08107, NCCP11945 and MS11 and labeled them as PUVCs. Since all these identified 23 PUVCs contained both T cell and B cell epitopes, these have been further reiterated as PUVCs which could be used as promising leads for vaccine development.
CONCLUSIONS: This hierarchical approach is the first comprehensive study to identify potential vaccine candidates which once utilized for vaccine development would surely serve as promising tools for effective control of Gonorrhea.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Multi Epitope Peptide Vaccine; Neisseria gonorrhoeae; Potential Universal Vaccine Candidates

Mesh:

Substances:

Year:  2016        PMID: 27596531     DOI: 10.1016/j.jtbi.2016.09.004

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  3 in total

1.  Computational tools for modern vaccine development.

Authors:  Andaleeb Sajid; Yogendra Singh; Pratyoosh Shukla
Journal:  Hum Vaccin Immunother       Date:  2019-12-18       Impact factor: 3.452

Review 2.  Recent Progress Towards a Gonococcal Vaccine.

Authors:  Stavros A Maurakis; Cynthia Nau Cornelissen
Journal:  Front Cell Infect Microbiol       Date:  2022-04-11       Impact factor: 6.073

Review 3.  Human Immune Responses and the Natural History of Neisseria gonorrhoeae Infection.

Authors:  Angela Lovett; Joseph A Duncan
Journal:  Front Immunol       Date:  2019-02-19       Impact factor: 7.561

  3 in total

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