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

Abstract

Motivation: Conceptually, epitope-based vaccine design poses two distinct problems: (1) selecting the best epitopes eliciting the strongest possible immune response, and (2) arranging and linking the selected epitopes through short spacer sequences to string-of-beads vaccines so as to increase the recovery likelihood of each epitope during antigen processing. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing and resulting in vaccines with less effective immunogencity. Results: In this work, we present a computational approach based on linear programming that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte-Carlo cleavage simulations to show that, indeed, a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen, and population coverage of the resulting vaccines by at least two fold. Availability: The software and the data analyzed are available at https://github.com/SchubertLab/JessEV

Graph-theoretical formulation of the generalized epitope-based vaccine design problem

“…We have also been working on an improved framework [ 61 ] to design string-of-beads vaccines with optimal spacers that approaches the two problems together and, unlike the present framework, allows residue-level control of cleavage probabilities. It further uses Monte Carlo cleavage simulations to provide a more realistic evaluation of the vaccines’ effectiveness.…”