Structural Motifs, Disorder, and the Efficacy of Viral Vaccines

Abstract

We demonstrate that it is possible to draw direct numerical correlations between virus particles and effective virus-like particle (VLP) derived vaccines through extraction of a Bragg-Williams order parameter from electron microscopy. The method has its roots in studies of disorder in metal alloys, and is adapted to describe the type and occurrence of structural motifs within the arrangement of viral coat proteins, captured by the value of the order parameter as a measure of disorder. A conventional approach to viral vaccine design consists of replicating select proteins to create a VLP designed to trigger an immune response while remaining non-infectious. Understanding variations between viruses and vaccine strains therefore tends to focus on differences between proteins, which can be characterized through genetic analysis. While such an approach provides vital information about the functioning and interactions of the proteins, it does not yet yield an early-stage pathway towards predicting the efficacy of a vaccine, and so large-scale clinical trials are required to obtain critical information. With the urgency associated with pandemics, including Coronavirus Disease-2019 (COVID-19) originating from the SARS-CoV-2 virus, there is a need for earlier indications of whether a vaccine has the necessary characteristics. Application of the methodology to Dengue and influenza virus particles indicates that temperature and pH during incubation could potentially be exploited to fine-tune the order parameter of VLP-based vaccines to match the corresponding virus. Additionally, utilization of an Ising model plot reveals a clear relationship between case fatality rate and order parameter for distinct virus families.