Joint epitope selection and spacer design for string-of-beads vaccines

Area of Science:

• Computational vaccinology
• Bioinformatics
• Immunoinformatics

Background:

• Epitope-based vaccine design involves selecting immunogenic epitopes and arranging them into effective vaccine constructs.
• Current methods sequentially address epitope selection and arrangement, neglecting interdependencies and potentially compromising in vivo efficacy.
• This sequential approach often prioritizes theoretical immunogenicity over optimal vaccine processing.

Purpose of the Study:

• To develop a computational approach that simultaneously optimizes epitope selection and arrangement for enhanced vaccine design.
• To address the limitations of sequential design methods in epitope-based vaccine development.
• To improve the in vivo immunogenicity and processing efficiency of string-of-beads vaccines.

Main Methods:

• Development of JessEV, a computational tool utilizing linear programming for simultaneous epitope selection and arrangement.
• Monte Carlo cleavage simulations to assess epitope recovery probability within vaccine constructs.
• Evaluation of the impact of simultaneous design on vaccine processing and immunogenicity.

Main Results:

• JessEV simultaneously optimizes epitope selection and assembly, balancing immunogenic potential with construct recovery.
• Simulations demonstrate that accommodating cleavage requirements during epitope selection significantly enhances recovery probability.
• The approach improves effective immunogenicity, pathogen coverage, and population coverage by at least 2-fold compared to fixed epitope sets.

Conclusions:

• Simultaneous optimization in epitope-based vaccine design is crucial for maximizing in vivo immunogenicity.
• JessEV provides a novel computational framework for designing more effective string-of-beads vaccines.
• The developed method enhances vaccine efficacy by considering both epitope immunogenicity and processing efficiency concurrently.