Cracking the Capsid Code: A Computationally-Feasible Approach for Investigating Virus-Excipient Interactions in Biologics Design

Abstract

The efficacy and equitable distribution of viral biologics, including vaccines and virus-like particles, is hindered due to their inherently low shelf life. To increase the longevity of such products, formulations are typically developed with small molecule additives known as excipients. Finding the correct excipients for a biological formulation is a costly and time-consuming process due to the large excipient design space and unknown mechanisms underlying excipient-virus interactions. Molecular dynamics simulations are, in theory, well-equipped to efficiently investigate these mechanisms. However, the massive size of fully assembled viral capsids, the protein shell that encapsulates the viral genome, demands computational resources well beyond the requirements of conventional simulations. There exists a need for a novel method that enables high-throughput investigations of virus-excipient interactions at the molecular level and at atomistic resolution. Here, we introduce CapSACIN -- a computational framework for Capsid Surface Abstraction and Computationally-Induced Nanofragmentation. We demonstrate the applicability of this workflow to a model non-enveloped virus, porcine parvovirus (PPV). Through simulations of PPV surface models, we observe that the 2-fold axis of symmetry is significantly weaker at the molecular level than the 3- or 5-fold axes of symmetry. Further, we present results demonstrating excellent agreement with experimentally determined excipient effects on PPV thermal stability.