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A multiscale coarse-grained model of the SARS-CoV-2 virion

Authors :
Lorenzo Casalino
Zied Gaieb
Peng He
Alexander J. Pak
Alvin Yu
Rommie E. Amaro
Abigail C. Dommer
Viviana Monje-Galvan
Gregory A. Voth
Source :
Biophysical journal, vol 120, iss 6, Biophysical Journal, bioRxiv
Publication Year :
2021
Publisher :
eScholarship, University of California, 2021.

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations, however, are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and on-going development of a largely “bottom-up” coarse-grained (CG) model of the SARS-CoV-2 virion. Structural data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data becomes publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.Significance StatementThis study reports the construction of a molecular model for the SARS-CoV-2 virion and details our multiscale approach towards model refinement. The resulting model and methods can be applied to and enable the simulation of SARS-CoV-2 virions.

Details

Database :
OpenAIRE
Journal :
Biophysical journal, vol 120, iss 6, Biophysical Journal, bioRxiv
Accession number :
edsair.doi.dedup.....e24abaaf8f4e0bf3a253b37e256e0d3a