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A novel approach to design a multiepitope peptide as a vaccine candidate for Bordetella pertussis
Esmaeil Roohparvar Basmenj1, Habib Izadkhah2, Maryam Hosseinpour3
1Biophysics Department, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
Insights
This study introduces a novel computational vaccine candidate against Bordetella pertussis, a highly contagious bacterium causing pertussis. The vaccine utilizes a highly immunogenic, non-toxic antigen identified through in silico screening.
Area of Science:
- * Computational vaccinology and bioinformatics
- * Infectious disease research
- * Bacterial pathogenesis and immunology
Background:
- * Bordetella pertussis causes highly contagious pertussis, a leading infectious cause of death, particularly in infants.
- * Emerging antibiotic-resistant strains and increasing pertussis prevalence necessitate novel vaccine strategies.
- * Current vaccination efforts face challenges due to rising disease incidence.
Purpose of the Study:
- * To design and computationally evaluate a novel vaccine candidate against Bordetella pertussis.
- * To identify a highly immunogenic, non-toxic, and non-allergenic antigen from the B. pertussis genome.
- * To develop a comprehensive in silico vaccine construct using identified epitopes and computational validation.
Main Methods:
- * Genome-wide computational screening of Bordetella pertussis 18323 to identify potential vaccine antigens.
- * In silico analysis of antigen immunogenicity, toxicity, and allergenicity.
- * Epitope identification, vaccine construct design, and extensive computational validation including structural and dynamic simulations.
Main Results:
- * Identification of a novel antigen with high immunogenicity and absence of toxicity and allergenicity.
- * Successful in silico construction of a B. pertussis vaccine candidate incorporating optimized epitopes.
- * Comprehensive computational validation, including secondary/tertiary structure analysis, physicochemical properties, docking, and molecular dynamics simulations, confirmed vaccine viability.
Conclusions:
- * The developed in silico vaccine candidate demonstrates significant potential for effective pertussis prevention.
- * Computational screening is a powerful approach for identifying novel and safe vaccine targets against challenging pathogens.
- * Further experimental validation is warranted to translate this promising computational vaccine into a clinical reality.
Abstract:
Bordetella pertussis is a very contagious pathogen in humans, causing pertussis disease. Pertussis is one of the 10 leading causes of death due to infectious diseases, especially among infants and children. Antibiotic-resistant strains have recently emerged in this bacterium, and despite the high vaccination coverage, the prevalence of this disease has been increasing recently in both developed and developing countries. The objective of this study is to introduce a novel in silico vaccine candidate aimed at countering B. pertussis effectively. Differing from other comparable studies, this research employed a computational screening methodology to assess the genome of 'Bordetella pertussis 18323.' The purpose was to identify an innovative antigen for the development of a vaccine against B. pertussis. Notably, our investigation introduces an innovative antigen distinguished by its elevated immunogenicity score. Importantly, this antigen lacks toxicity and allergenicity, making it recognizable to the immune system and thus capable of inducing a robust immune response. In the subsequent phase, our antigen was utilized to identify potential epitopes conducive to the construction of a B. pertussis vaccine. These epitopes, alongside linkers, his-tag and adjuvants, were amalgamated to form the vaccine candidate. Subsequently, a comprehensive evaluation of the vaccine was conducted, encompassing various computational tests such as secondary and tertiary structure analysis, physicochemical examination, and structural analysis involving docking and molecular dynamics simulations. Importantly, our vaccine successfully passed all in silico tests.Communicated by Ramaswamy H. Sarma.
