Multiscale modeling of SARS-COV-2 variants

Recent months have seen surges of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing COVID-19 pandemic due to the emergence of several new variants. Since the first emergence of SARS-CoV-2 from Wuhan, China, in December 2019, the variants with D614G mutation have dominated worldwide. In Autumn 2020, the SARS-CoV-2 variant of concern (VOC) B.1.1.7 (alpha) became dominant in the United Kingdom and subsequently spread to the other parts of the globe. After the emergence of B.1.1.7, numerous other VOCs have been identified including B.1.351 (beta) in South Africa, P.1 (gamma) in Brazil, and B.1.617.2 (delta) in India. These VOCs are associated with extensive transmissivity and infectivity. In particular, the delta variant spread to over 98 countries within a matter of months and became the dominant variant in those countries including India, the USA, and the UK (https://cov-lineages.org/lineage.html?lineage=B.1.617.2). These VOCs are characterized by different mutations in the spike (S) protein and are believed to escape from the host immune responses induced by currently available vaccines. In the current situation, the enormous social and health impacts indicate a clear and urgent need to understand the effect of these mutations on the virus during viral pathogenesis in order to modify the existing vaccines and treatments. Our proposal focuses on these variants of SARS-CoV-2 that have raised concerns about the effectiveness of current SARS-COV-2 vaccine platforms. We will use accurate coarse-grained (CG) models of these variants as simplified representations of complex biomolecules to study the cooperative dynamical processes involved in viral pathogenesis. To build CG models, reference data from microsecond long all-atom (AA) molecular dynamics (MD) simulations will be used as a training set to systematically generate and refine viral protein CG models. In addition, the atomic-level data will help to unravel the interactions and impact of mutations on the virus. On top of that, we will perform AA-MD simulations of the membrane (M) and nucleocapsid (N) structural proteins in different realistic membrane models to understand the process of viral assembly and budding during viral pathogenesis.