Designing a New Multi-Epitope Pertussis Vaccine with Highly Population Coverage Based on a Novel Sequence and Structural Filtration Algorithm.

Abstract

Pertussis vaccine is produced from physicochemically inactivated toxin for many years. Recent advancements in immunoinformatics [N. Tomar and R. K. De, "Immunoinformatics: an integrated scenario," Immunology, vol. 131, no. 2, pp. 153-168, 2010] and structural bioinformatics can provide a new multidisciplinary approach to overcome the concerns including unwanted antibodies and incomplete population coverage. In this study we focused on solving the challenging issues by designing a multi-epitope vaccine (MEV) using rational bioinformatics analyses. The frequencies of All HLA DP, DQ, and DR alleles were evaluated in almost all countries. Strong binder surface epitopes on the pertussis toxin were selected based on our novel filtration strategy. Finally, the population coverage of MEV was determined in the candidate country. Filtration steps yielded 312 strong binder epitopes. Finally, 8 surface strong binder epitopes were selected as candidate epitopes. The population coverage of the MEV in France and the world was 98 and 100 percent, respectively. Our algorithm successfully filtered many unwanted strong binder epitopes. Considering the HLA type of all individuals in a country, we theoretically provided the maximum chance to all humans to be vaccinated efficiently. Application of a MEV would be led to production of highly efficient target specific antibodies, significant reduction of unwanted antibodies, and avoid possible raising of auto-antibodies as well.