Computational tools for epitope vaccine design and evaluation

Abstract

Rational approaches will be required to develop universal vaccines for viral pathogens such as human immunodeficiency virus, hepatitis C virus, and influenza, for which empirical approaches have failed. The main objective of a rational vaccine strategy is to design novel immunogens that are capable of inducing long-term protective immunity. In practice, this requires structure-based engineering of the target neutralizing epitopes and a quantitative readout of vaccine-induced immune responses. Therefore, computational tools that can facilitate these two areas have played increasingly important roles in rational vaccine design in recent years. Here we review the computational techniques developed for protein structure prediction and antibody repertoire analysis, and demonstrate how they can be applied to the design and evaluation of epitope vaccines.

Figure 1

(A) A general strategy for epitope vaccine design consisting of epitope identification, immunogen design by epitope grafting, particulate presentation of designed immunogen, animal immunization, next-generation sequencing (NGS) analysis of antibody responses, and functional characterization of elicited broadly neutralizing antibodies (bnAbs). (B) Three categories of protein structure prediction tools: sequence analysis, structural modeling, and machine learning. Potential utility in epitope vaccine design is indicated by asterisk (*).

Figure 2

(A) Application of side chain modeling tools to resurfacing of non-epitope regions of an antigen, optimization of an antibody paratope, and engineering of an antigen epitope. (B) A glycan modeling tool based on a clash-based scoring function, a stochastic search algorithm, and a glycan rotamor library. As an example, HIV-1 gp120 core (PDB ID: 3NGB) is glycosylated in silico using a high-mannose rotamer library.

Figure 3

(A) Epitope scaffold design consisting of scaffold search, epitope grafting, and design optimization. (B) Three key criteria for scaffold selection including size and topology, flexibility, and the structural environment of the graft. (C) Application of a “scaffolding meta-server” to the HIV-1 2F5 epitope. The number of scaffolds identified by each algorithm and the overlap between any two algorithms are listed in an upper-diagonal matrix. (D) Concept of “scaffold family” using three HIV-1 10E8 epitope scaffolds as an example. Three proteins of the same fold family are matched to the 10E8 epitope with an average C_α RMSD of 1.5Å. (E) Structural model of a ferritin nanoparticle presenting 24 copies of an HIV-1 PGT128 epitope scaffold.

Figure 4

(A) A general strategy for antibody repertoire analysis consisting of sample collection, next-generation sequencing (NGS) of antibody library, and bioinformatics analysis, which can be divided into two consecutive stages – primary analysis and in-depth analysis. (B) Dissection of epitope-specific antibody responses through epitope manipulation. (C) Longitudinal tracing of immunogen-specific antibody lineages. Epitope manipulation and longitudinal tracing can be used in combination to analyse the vaccine-induced antibody responses with high resolution.