Reverse Vaccinology and Its Applications

  • Amol M. Kanampalliwar
Part of the Methods in Molecular Biology book series (MIMB, volume 2131)


The application of the fields of pharmacogenomics and pharmacogenetics to vaccine design, profoundly combined with bioinformatics, has been recently termed “vaccinomics.” The enormous amount of information generated by whole genome sequencing projects and the rise of bioinformatics has triggered the birth of a new era of vaccine research and development, leading to a “third generation” of vaccines, which are based on the application of vaccinomics science to vaccinology. The first example of such an approach is reverse vaccinology. Reverse vaccinology reduces the period of vaccine target detection and evaluation to 1–2 years. This approach targets the genomic sequence and predicts those antigens that are most likely to be vaccine candidates. This approach allows not only the identification of all the antigens obtained by the previous methods but also the discovery of new antigens that work on a totally different paradigm. Hence this method helps in the discovery of novel mechanisms of immune intervention. Epitope-based immune-derived vaccines (IDV) are generally considered to be safe when compared to other vectored or attenuated live vaccines. Epitope-based IDV may also provide essential T-cell help for antibody-directed vaccines. Such vaccines may have a significant advantage over earlier vaccine design approaches, as the cautious assortment of the components may diminish.

Key words

Vaccinomics Reverse vaccinology IDV Epitope 


  1. 1.
    Poland GA, Ovsyannikova IG, Jacobson RM (2009) Application of pharmacogenomics to vaccines. Pharmacogenomics 10(5):837–852CrossRefGoogle Scholar
  2. 2.
    Bagnoli F et al (2011) Designing the next generation of vaccines for global public health. OMICS 15(9):545–566CrossRefGoogle Scholar
  3. 3.
    Rappuoli R (2000) Reverse vaccinology. Curr Opin Microbiol 3(5):445–450CrossRefGoogle Scholar
  4. 4.
    Elliott SL et al (2008) Phase I trial of a CD8+ T-cell peptide epitope-based vaccine for infectious mononucleosis. J Virol 82(3):1448–1457CrossRefGoogle Scholar
  5. 5.
    Gahery H et al (2006) New CD4+ and CD8+ T cell responses induced in chronically HIV type-1-infected patients after immunizations with an HIV type 1 lipopeptide vaccine. AIDS Res Hum Retrovir 22(7):684–694CrossRefGoogle Scholar
  6. 6.
    Asjo B et al (2002) Phase I trial of a therapeutic HIV type 1 vaccine, Vacc-4x, in HIV type 1-infected individuals with or without antiretroviral therapy. AIDS Res Hum Retrovir 18(18):1357–1365CrossRefGoogle Scholar
  7. 7.
    Kran AM et al (2004) HLA- and dose-dependent immunogenicity of a peptide-based HIV-1 immunotherapy candidate (Vacc-4x). AIDS 18(14):1875–1883CrossRefGoogle Scholar
  8. 8.
    De Groot AS et al (2011) Tools for vaccine design: prediction and validation of highly immunogenic and conserved class II epitopes and development of epitope-driven vaccines, in development of vaccines. John Wiley & Sons, Inc., Hoboken, New Jersey, pp 65–94Google Scholar
  9. 9.
    Lara HH, Garza-Treviño EN, Ixtepan-Turrent L, Singh DK (2011) Silver nanoparticles are broad-spectrum bactericidal and virucidal compounds. J Nanobiotechnology 9:30CrossRefGoogle Scholar
  10. 10.
    Geels MJ et al (2011) European vaccine initiative: lessons from developing malaria vaccines. Expert Rev Vaccines 10(12):1697–1708CrossRefGoogle Scholar
  11. 11.
    Rinaudo CD, Telford JL, Rappuoli R, Seib KL (2009) Vaccinology in the genome era. J Clin Invest 119(9):2515–2525CrossRefGoogle Scholar
  12. 12.
    LM L (2010) New strategies for vaccine development. SPCV 2:e4Google Scholar
  13. 13.
    Lefébure T, Stanhope MJ (2007) Evolution of the core and pan-genome of streptococcus: positive selection, recombination, and genome composition. Genome Biol 8:R71CrossRefGoogle Scholar
  14. 14.
    Donati C, Rappuoli R (2013) Reverse vaccinology in the 21st century: improvements over the original design. Ann N Y Acad Sci 1285:115–132CrossRefGoogle Scholar
  15. 15.
    Ansari HR, Raghava GP (2010) Identification of conformational B-cell epitopes in an antigen from its primary sequence. Immunome Res 6:6CrossRefGoogle Scholar
  16. 16.
    Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis 18(15):2714–2723CrossRefGoogle Scholar
  17. 17.
    Goodsell DS, Olson AJ (1990) Automated docking of substrates to proteins by simulated annealing. Proteins 8(3):195–202CrossRefGoogle Scholar
  18. 18.
    Sotriffer CA et al (2000) Automated docking of ligands to antibodies: methods and applications. Methods 20(3):280–291CrossRefGoogle Scholar
  19. 19.
    Walker LM et al (2011) Broad neutralization coverage of HIV by multiple highly potent antibodies. Nature 477(7365):466–470CrossRefGoogle Scholar
  20. 20.
    Walker LM et al (2009) Broad and potent neutralizing antibodies from an African donor reveal a new HIV-1 vaccine target. Science 326(5950):285–289CrossRefGoogle Scholar
  21. 21.
    Trkola A et al (1996) Human monoclonal antibody 2G12 defines a distinctive neutralization epitope on the gp120 glycoprotein of human immunodeficiency virus type 1. J Virol 70(2):1100–1108CrossRefGoogle Scholar
  22. 22.
    Kanampalliwar AM, Soni R, Girdhar A, Tiwari A (2013) Web based tools and databases for epitope prediction and analysis: a contextual review. Int J Comput Bioinform In Silico Model 2(4):180–185Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  • Amol M. Kanampalliwar
    • 1
  1. 1.Master of Technology, School of Biotechnology, UTDRajiv Gandhi Proudyogiki VishwavidyalayaBhopalIndia

Personalised recommendations