Designing Novel Multi Epitope Peptide Vaccine Against by Using Immunoinformatic Approach

Abstract

Campylobacter jejuni is a type of bacteria that can cause foodborne illness in humans. It is one of the most common causes of bacterial gastroenteritis worldwide, with symptoms including diarrhea, stomach cramps, fever, and vomiting and is considered to be a global killer. C. jejuni infection is one of the most widespread infectious diseases of the last decades. It mainly targets young children mostly under the age of 5 as well as individuals and is recognized as a major food borne pathogen in developing countries. There is a need for a highly efficient vaccination that can provide long-term protection against C. jejuni infection, but there is presently no such vaccine available. This study used the Vaxign software to screen C. jejuni proteome for protective antigens. To identify predicted antigens that might make acceptable vaccine candidates, this study used a variety of computational approaches to determine their immunological characteristics. To validate the epitopes predicted by the NetCTL method, a more accurate server, Net MHC pan 4.0, was used, and the findings were compared using peptide scores. In the initial phase of the study three epitopes MSNVYAYRF, LSDDINLNI, and ATSTSTITL have been discovered as the most potential epitopes binding with MHC class I HLA alleles such as B*58:01, A*01:01, and B*07:02, respectively. These three epitopes demonstrated the lowest binding energies and formed complex docked structures across the largest number of populations worldwide using Autodock vina. In the second phase of the study three potent T cell peptides YFYGLAGGG, PFIMFSMLM and YIILNNFKI were found to have antigenicity scores of 1.1509, 97 1.8830, and 1.3252, respectively. In the final part of the investigation, a reverse vaccinology approach was employed to discover vaccine targets from the proteome of diarrheagenic Campylobacter jejuni strain NCTC11168 to produce chimeric vaccine candidates newline