Integrated immunoinformatics and subtractive proteomics approach for multi-epitope vaccine designing to combat S. pneumoniae TIGR4

Abstract

Streptococcus pneumoniae is one of the major precarious pathogens accountable for over 1.2 million fatalities annually. The key drivers for pneumococcal vaccine development involve high morbidity and mortality in over one million cases, especially in very young children and the elderly. In this study, immunoinformatics was integrated with subtractive proteomics to find antigenic proteins for designing a multi-epitope vaccine against S. pneumoniae. As prospective vaccine targets, the developed pipeline identified two antigenic proteins, i.e., penicillin-binding protein and ATP synthase subunit. Several immunoinformatics and bioinformatics resources were used to forecast T- and B-cell epitopes from specific proteins. By employing a mixture of five cytotoxic T-cell lymphocytes, six helper T-cell lymphocytes, and seven linear B-cell lymphocyte epitopes, a 392 amino acid-long vaccine was designed. To enhance immune responses, the designed vaccine was coupled with a cholera enterotoxin subunit B adjuvant. The designed vaccine was highly antigenic, non-allergenic, and stable for human usage. The stability of the vaccine with toll-like receptor-4 was evaluated by molecular docking and molecular dynamic simulation. In addition, immunological simulation was performed to test its real-world potency. The vaccine codon was then cloned in silico. Overall, this study paves the way for the development of a multi-epitope S. pneumoniae vaccine under laboratory conditions. Furthermore, the current findings warrant for the experimental validation of the final multi-epitope vaccine construct to demonstrate its immunological reinforcing capability and clinical applicability.

Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches

“…Integrated epitope prediction was utilized, focusing on selecting CTL epitopes with consensus scores below 2. A lower score indicates an enhanced capability of these epitopes to bind to MHC-I molecules, making them favorable candidates for the construction of vaccine sequences ( 24 ). The purpose of CTLPred is to identify putative T cell epitopes in a particular protein sequence by emphasizing their capacity to bind to MHC-I molecules, which makes it easier for cytotoxic T cells to recognize them ( 25 ).…”

“…The tertiary structure was also determined using MEV. ElliPro uses the protein’s 3D structure as input to detect areas where amino acids conjoin to form epitope ( 24 ). The PI score is used for identifying discontinuous B-cell epitopes.…”

“…Cytotoxic T lymphocyte (CTL) cells plays a vital part in the immune system by admit certain antigens (22). To identify CTL epitopes, the interested protein sequences were given that in FASTA format, CTLPred was used in MHC class I complex (23). Integrated epitope prediction was utilized, focusing on selecting CTL epitopes with consensus scores below 2.…”