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Virologie ; 26(2):181, 2022.
Article in English | EMBASE | ID: covidwho-1912989


Several COVID-19 vaccines have now been deployed to tackle the SARSCoV- 2 pandemic, most of them based on messenger RNA or adenovirus vectors. The duration of protection afforded by these vaccines is unknown, as well as their capacity to protect from emerging new variants. To provide sufficient coverage for the world population, additional strategies need to be tested. The live pediatric measles vaccine (MeV) is an attractive approach, given its extensive safety and efficacy history, along with its established large-scale manufacturing capacity. We develop an MeVbased SARS-CoV-2 vaccine expressing the prefusion-stabilized, membrane-anchored full-length S antigen, which proves to be efficient at eliciting strong Th1-dominant T-cell responses and high neutralizing antibody titers. In both mouse and golden Syrian hamster models, these responses protect the animals from intranasal infectious challenge. Additionally, the elicited antibodies efficiently neutralize in vitro the three currently circulating variants of SARS-CoV-2.

PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333613


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 spike's 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 FORMAT: Lorenzo Casalino 1 , Abigail Dommer 1 , Zied Gaieb 1 , Emilia P. Barros 1 , Terra Sztain 1 , Surl-Hee Ahn 1 , Anda Trifan 2,3 , Alexander Brace 2 , Anthony Bogetti 4 , Heng Ma 2 , Hyungro Lee 5 , Matteo Turilli 5 , Syma Khalid 6 , Lillian Chong 4 , Carlos Simmerling 7 , David J. Hardy 3 , Julio D. C. Maia 3 , James C. Phillips 3 , Thorsten Kurth 8 , Abraham Stern 8 , Lei Huang 9 , John McCalpin 9 , Mahidhar Tatineni 10 , Tom Gibbs 8 , John E. Stone 3 , Shantenu Jha 5 , Arvind Ramanathan 2* , Rommie E. Amaro 1* . 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.

3rd IEEE/ACM International Workshop on HPC for Urgent Decision Making, UrgentHPC 2021 ; : 1-10, 2021.
Article in English | Scopus | ID: covidwho-1705928


Over the past 18 months, the need to perform atomic detail molecular dynamics simulations of the SARS-CoV-2 virion, its spike protein, and other structures related to the viral infection cycle has led biomedical researchers worldwide to urgently seek out all available biomolecular structure information, appropriate molecular modeling and simulation software, and the necessary computing resources to conduct their work. We describe our experiences from several COVID-19 research collaborations and the challenges they presented in terms of our molecular modeling software development and support efforts, our laboratory's local computing environment, and our scientists' use of non-traditional HPC hardware platforms such as public clouds for large scale parallel molecular dynamics simulations. © 2021 IEEE.