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Simmerling, C.

Publications and source records attributed to Simmerling, C..

2 recordsLinked to original sources

Receptor binding may directly activate the fusion machinery in coronavirus spike glycoproteins

SARS-CoV-2, the causative agent of the COVID-19 pandemic, is an enveloped RNA virus. Trimeric spike glycoproteins extend outward from the virion; these class I viral membrane fusion proteins mediate entry of the virus into a host cell and are the dominant antigen for immune response. Cryo-EM studies have generated a large number of structures for the spike either alone, or bound to the cognate receptor ACE2 or antibodies, with the three receptor binding domains (RBDs) seen closed, open, or in various combinations. Binding to ACE2 requires an open RBD, and is believed to trigger the series of dramatic conformational changes in the spike that lead to the shedding of the S1 subunit and transition of the spring-loaded S2 subunit to the experimentally observed post-fusion structure. The steps following ACE2 binding are poorly understood despite extensive characterization of the spike through X-ray, cryo-EM, and computation. Here, we use all-atom simulations, guided by analysis of 81 existing experimental structures, to develop a model for the structural and energetic coupling that connects receptor binding to activation of the membrane fusion machinery.

molecular biology

AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spikes full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems. ACM Reference FormatLorenzo Casalino1{dagger}, Abigail Dommer1{dagger}, Zied Gaieb1{dagger}, Emilia P. Barros1, Terra Sztain1, Surl-Hee Ahn1, Anda Trifan2,3, Alexander Brace2, Anthony Bogetti4, Heng Ma2, Hyungro Lee5, Matteo Turilli5, Syma Khalid6, Lillian Chong4, Carlos Simmerling7, David J. Hardy3, Julio D. C. Maia3, James C. Phillips3, Thorsten Kurth8, Abraham Stern8, Lei Huang9, John McCalpin9, Mahidhar Tatineni10, Tom Gibbs8, John E. Stone3, Shantenu Jha5, Arvind Ramanathan2*, Rommie E. Amaro1*. 2020. AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics. In Supercomputing 20: International Conference for High Performance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI

biophysics