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Molecular modeling studies of carbohydrate vaccine antigens: informing the future of vaccine design
This thesis delves into the intricate world of carbohydrate-based vaccine antigens by employing molecular dynamics simulations to explore the link between their structure, conformation, and immune function. Through a series of four case studies focused on distinct antigen targets, this research aims...
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| Format: | Thesis |
| Language: | Eng |
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Department of Chemistry
2025
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| Summary: | This thesis delves into the intricate world of carbohydrate-based vaccine antigens by employing molecular dynamics simulations to explore the link between their structure, conformation, and immune function. Through a series of four case studies focused on distinct antigen targets, this research aims to predict potential cross-reactivity and cross-protection, rationalize observed immunological reactivity, and provide valuable insights into key epitopes and mechanisms for antigen-antibody binding. The case studies encompass the following antigens: Haemophilus influenzae types a and b, Pasteurella multocida types B and E, Shigella flexneri serotype 6, and Streptococcus pneumoniae serogroup 10. Each case study investigates the conformational aspects of the target antigens and proposes mechanisms for observed immunological phenomena. The collective findings propose connections between structural features, conformation, and their functional implications in immune responses, drawing parallels across individual case studies to elucidate recurring motifs employed by pathogens such as antigen flexibility, structural modifications, and backbone shielding. By broadening the applicability of this molecular modeling methodology, this research extends its reach to new target antigens and pathogens, offering a complementary approach to establish structurefunction relationships and inform rational vaccine design. The continued application of this methodology to a diverse range of vaccine targets promises to expand the knowledge base in the field, potentially revealing additional features harnessed by pathogens to gain a competitive advantage and evade the immune system. As computational power continues to grow, the cost and time associated with modeling may decrease, further enhancing the accessibility of this methodology for future vaccine development endeavors. |
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