4.5 Article

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

期刊

BIOPHYSICAL JOURNAL
卷 120, 期 6, 页码 1097-1104

出版社

CELL PRESS
DOI: 10.1016/j.bpj.2020.10.048

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资金

  1. NSF through NSF RAPID [CHE-2029092]
  2. National Institute of General Medical Sciences of the National Institutes of Health [R01 GM063796]
  3. National Institutes of Health
  4. NSF RAPID [MCB-2032054]
  5. RCSA Research, and a UC San Diego Moore's Cancer Center 2020 SARS-COV-2 seed grant
  6. National Institute of Allergy and Infectious Diseases of the National Institutes of Health [F32 AI150208, F32 AI150477]
  7. NSF [OAC-1818253]
  8. National Institutes of Health [R01GM116961]
  9. [PSCA17046P]

向作者/读者索取更多资源

This article presents the current status and ongoing development of a largely bottom-up coarse-grained (CG) model of the SARS-CoV-2 virion. The CG model was constructed using data from cryo-electron microscopy, x-ray crystallography, and computational predictions to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into the complete virion model. The CG model allows for capturing viral behavior that is difficult to observe in atomistic simulations and can be iteratively improved with new data.
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 are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and ongoing development of a largely bottom-up'' coarse-grained (CG) model of the SARS-CoV-2 virion. 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 become 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.

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