Immunoinformatics Approach in Designing Epitope-based Vaccine against Meningitis-inducing Bacteria (Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae Type b)

Authors

  • Hilyatuz Zahroh Genetic Research Center, University of YARSI, Indonesia.
  • Ahmad Ma’rup Department of Chemistry, Universitas Islam Negeri Syarif Hidayatullah, Indonesia.
  • Usman Sumo Friend Tambunan Bioinformatics Research Group, Department of Chemistry, Faculty of Mathematics and Science, University of Indonesia, Indonesia.
  • Arli Aditya Parikesit Bioinformatics Research Group, Department of Chemistry, Faculty of Mathematics and Science, University of Indonesia, Indonesia.

DOI:

https://doi.org/10.33393/dti.2016.1421

Keywords:

meningitis, immunoinformatics, epitope-based vaccine, epitope prediction, molecular docking

Abstract

Meningitis infection is one of the major threats during Hajj season in Mecca. Meningitis vaccines are available, but their uses are limited in some countries due to religious reasons. Furthermore, they only give protection to certain serogroups, not to all types of meningitis-inducing bacteria. Recently, research on epitope-based vaccines has been developed intensively. Such vaccines have potential advantages over conventional vaccines in that they are safer to use and well responded to the antibody. In this study, we developed epitope-based vaccine candidates against various meningitis-inducing bacteria, including Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae type b. The epitopes were selected from their protein of polysaccharide capsule. B-cell epitopes were predicted by using BCPred, while T-cell epitope for major histocompatibility complex (MHC) class I was predicted using PAProC, TAPPred, and Immune Epitope Database. Immune Epitope Database was also used to predict T-cell epitope for MHC class II. Population coverage and molecular docking simulation were predicted against previously generated epitope vaccine candidates. The best candidates for MHC class I- and class II-restricted T-cell epitopes were MQYGDKTTF, MKEQNTLEI, ECTEGEPDY, DLSIVVPIY, YPMAMMWRNASNRAI, TLQMTLLGIVPNLNK, ETSLHHIPGISNYFI, and SLLYILEKNAEMEFD, which showed 80% population coverage. The complexes of class I T-cell epitopes–HLA-C*03:03 and class II T-cell epitopes–HLA-DRB1*11:01 showed better affinity than standards as evaluated from their ΔGbinding value and the binding interaction between epitopes and HLA molecules. These peptide constructs may further be undergone in vitro and in vivo testings for the development of targeted vaccine against meningitis infection.

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Published

2016-11-01

How to Cite

Zahroh, H., Ma’rup, A., Friend Tambunan, U. S., & Parikesit, A. A. (2016). Immunoinformatics Approach in Designing Epitope-based Vaccine against Meningitis-inducing Bacteria (Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae Type b). Drug Target Insights, 10(1). https://doi.org/10.33393/dti.2016.1421

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Original Research Article

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