Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri

Reverse vaccinology (RV) was first introduced by Rappuoli for the development of an effective vaccine against serogroup B Neisseria meningitidis (MenB). With the advances in next generation sequencing technologies, the amount of genomic data has risen exponentially. Since then, the RV approach has w...

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Published in:Methods in Molecular Biology
Main Author: Leow C.Y.; Chuah C.; Abdul Majeed A.B.; Mohd Nor N.
Format: Book chapter
Language:English
Published: Humana Press Inc. 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119699550&doi=10.1007%2f978-1-0716-1900-1_2&partnerID=40&md5=3fbdb732959d698f09e4164b7220f8df
id 2-s2.0-85119699550
spelling 2-s2.0-85119699550
Leow C.Y.; Chuah C.; Abdul Majeed A.B.; Mohd Nor N.
Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
2022
Methods in Molecular Biology
2414

10.1007/978-1-0716-1900-1_2
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119699550&doi=10.1007%2f978-1-0716-1900-1_2&partnerID=40&md5=3fbdb732959d698f09e4164b7220f8df
Reverse vaccinology (RV) was first introduced by Rappuoli for the development of an effective vaccine against serogroup B Neisseria meningitidis (MenB). With the advances in next generation sequencing technologies, the amount of genomic data has risen exponentially. Since then, the RV approach has widely been used to discover potential vaccine protein targets by screening whole genome sequences of pathogens using a combination of sophisticated computational algorithms and bioinformatic tools. In contrast to conventional vaccine development strategies, RV offers a novel method to facilitate rapid vaccine design and reduces reliance on the traditional, relatively tedious, and labor-intensive approach based on Pasteur”s principles of isolating, inactivating, and injecting the causative agent of an infectious disease. Advances in biocomputational techniques have remarkably increased the significance for the rapid identification of the proteins that are secreted or expressed on the surface of pathogens. Immunogenic proteins which are able to induce the immune response in the hosts can be predicted based on the immune epitopes present within the protein sequence. To date, RV has successfully been applied to develop vaccines against a variety of infectious pathogens. In this chapter, we apply a pipeline of bioinformatic programs for identification of Shigella flexneri potential vaccine candidates as an illustration immunoinformatic tools available for RV. © 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
Humana Press Inc.
10643745
English
Book chapter

author Leow C.Y.; Chuah C.; Abdul Majeed A.B.; Mohd Nor N.
spellingShingle Leow C.Y.; Chuah C.; Abdul Majeed A.B.; Mohd Nor N.
Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
author_facet Leow C.Y.; Chuah C.; Abdul Majeed A.B.; Mohd Nor N.
author_sort Leow C.Y.; Chuah C.; Abdul Majeed A.B.; Mohd Nor N.
title Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
title_short Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
title_full Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
title_fullStr Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
title_full_unstemmed Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
title_sort Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri
publishDate 2022
container_title Methods in Molecular Biology
container_volume 2414
container_issue
doi_str_mv 10.1007/978-1-0716-1900-1_2
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119699550&doi=10.1007%2f978-1-0716-1900-1_2&partnerID=40&md5=3fbdb732959d698f09e4164b7220f8df
description Reverse vaccinology (RV) was first introduced by Rappuoli for the development of an effective vaccine against serogroup B Neisseria meningitidis (MenB). With the advances in next generation sequencing technologies, the amount of genomic data has risen exponentially. Since then, the RV approach has widely been used to discover potential vaccine protein targets by screening whole genome sequences of pathogens using a combination of sophisticated computational algorithms and bioinformatic tools. In contrast to conventional vaccine development strategies, RV offers a novel method to facilitate rapid vaccine design and reduces reliance on the traditional, relatively tedious, and labor-intensive approach based on Pasteur”s principles of isolating, inactivating, and injecting the causative agent of an infectious disease. Advances in biocomputational techniques have remarkably increased the significance for the rapid identification of the proteins that are secreted or expressed on the surface of pathogens. Immunogenic proteins which are able to induce the immune response in the hosts can be predicted based on the immune epitopes present within the protein sequence. To date, RV has successfully been applied to develop vaccines against a variety of infectious pathogens. In this chapter, we apply a pipeline of bioinformatic programs for identification of Shigella flexneri potential vaccine candidates as an illustration immunoinformatic tools available for RV. © 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
publisher Humana Press Inc.
issn 10643745
language English
format Book chapter
accesstype
record_format scopus
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