Molecular architecture of SARS-CoV-2 envelope by integrative modeling

Despite tremendous efforts by the research community during the COVID-19 pandemic, the exact structure of SARS-CoV-2 and related betacoronaviruses remains elusive. Being a key structural component of the SARS-CoV-2 virion, the envelope encapsulates viral RNA and is composed of three structural proteins, spike (S), membrane (M), and envelope (E), which interact with each other and with the lipids acquired from the host membranes. Here, we developed and applied an integrative multiscale computational approach to model the envelope structure of SARS-CoV-2 with near atomistic detail, focusing on studying the dynamic nature and molecular interactions of its most abundant, but largely understudied, M protein. The molecular dynamics simulations allowed us to test the envelope stability under different configurations and revealed that the M dimers agglomerated into large, filament-like, macromolecular assemblies with distinct molecular patterns formed by Ms transmembrane and intravirion (endo) domains. These results are in good agreement with current experimental data, demonstrating a generic and versatile integrative approach to model the structure of a virus de novo. We anticipate our work to provide insights into critical roles of structural proteins in the viral assembly and integration, proposing new targets for the antiviral therapies.

Structural genomics and interactomics of 2019 Wuhan novel coronavirus, 2019-nCoV, indicate evolutionary conserved functional regions of viral proteins

During its first month, the recently emerged 2019 Wuhan novel coronavirus (2019-nCoV) has already infected many thousands of people in mainland China and worldwide and took hundreds of lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge we leverage the data about the related coronaviruses that is readily available in public databases, and integrate these data into a single computational pipeline. As a result, we provide a comprehensive structural genomics and interactomics road-maps of 2019-nCoV and use these information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community at http://korkinlab.org/wuhan