# Structural prediction of chimeric immunogen candidates to elicit targeted antibodies against betacoronaviruses

## TL;DR

This paper introduces a method to design stable chimeric spike proteins that can help elicit broad antibody responses against betacoronaviruses.

## Contribution

A new design approach using AlphaFold to predict and validate stable chimeric spike proteins for immunogen development.

## Key findings

- A new metric based on AlphaFold outputs was developed to score chimera stability.
- Top chimeras showed good stability in molecular dynamics simulations.
- Experimental testing confirmed 5 out of 7 predicted-stable chimeras.

## Abstract

Betacoronaviruses pose an ongoing pandemic threat. Antigenic evolution of the SARS-CoV-2 virus has shown that much of the spontaneous antibody response is narrowly focused rather than broadly neutralizing against even SARS-CoV-2 variants, let alone future threats. One way to overcome this is by focusing the antibody response against better-conserved regions of the viral spike protein. This has been demonstrated empirically in prior work, but we posit that systematic design tools will further potentiate antigenic focusing approaches. Here, we present a design approach to predict stable chimeras between SARS-CoV-2 and other coronaviruses, creating synthetic spike proteins that display a desired conserved region, in this case S2, and vary other regions. We leverage AlphaFold to predict chimeric structures and create a new metric for scoring chimera stability based on AlphaFold outputs. We evaluated 114 candidate spike chimeras using this approach. Top chimeras were further evaluated using molecular dynamics simulation as an intermediate validation technique, showing good stability compared to low-scoring controls. Experimental testing of five predicted-stable and two predicted-unstable chimeras confirmed 5/7 predictions, with one intermediate result. This demonstrates the feasibility of the underlying approach, which can be used to design custom immunogens to focus the immune response against a desired viral glycoprotein epitope.

Viral spike glycoproteins often show great antigenic variability in the most immunogenic regions, while broadly neutralizing antibodies frequently recognize secondary sites. This raises the question of how to elicit antibodies against less immunogenic but more conserved antigenic regions. Prior proof-of-concept studies have shown that a series of chimeric antigens can elicit such responses if the highly immunogenic regions are varied and the desired antigenic regions are held fixed. This introduces a protein design question: how to select viral spike chimeras that have comparable or increased stability compared to wild-type parent sequences. This study leverages structural modeling with AlphaFold to predict the stability of chimeric coronavirus spike proteins, selecting a set of low-homology but high-stability chimeras. These chimeras were then computationally validated using molecular dynamics simulation and experimentally tested. The resulting chimeric spike proteins represent a starting point for further chimeric immunization strategies, and the underlying tools provide a general means to design chimeric proteins to assist future immunization strategies aimed at generating antigenically focused and potentially more broadly neutralizing immune responses.