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#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol

Dommer, Abigail and Casalino, Lorenzo and Kearns, Fiona and Rosenfeld, Mia and Wauer, Nicholas and Ahn, Surl-Hee and Russo, John and Oliveira, Sofia and Morris, Clare and Bogetti, Anthony and Trifan, Anda and Brace, Alexander and Sztain, Terra and Clyde, Austin and Ma, Heng and Chennubhotla, Chakra and Lee, Hyungro and Turilli, Matteo and Khalid, Syma and Tamayo-Mendoza, Teresa and Welborn, Matthew and Christensen, Anders and Smith, Daniel G. A. and Qiao, Zhuoran and Sirumalla, Sai Krishna and O’Connor, Michael and Manby, Frederick and Anandkumar, Anima and Hardy, David and Phillips, James and Stern, Abraham and Romero, Josh and Clark, David and Dorrell, Mitchell and Maiden, Tom and Huang, Lei and McCalpin, John and Woods, Christopher and Gray, Alan and Williams, Matt and Barker, Bryan and Rajapaksha, Harinda and Pitts, Richard and Gibbs, Tom and Stone, John and Zuckerman, Daniel and Mulholland, Adrian and Miller, Thomas, III and Jha, Shantenu and Ramanathan, Arvind and Chong, Lillian and Amaro, Rommie (2021) #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol. . (Unpublished)

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We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

Item Type:Report or Paper (Discussion Paper)
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URLURL TypeDescription Paper InCaltech News CentralDiscussion Paper ItemJournal Article
Dommer, Abigail0000-0003-4847-4136
Casalino, Lorenzo0000-0003-3581-1148
Kearns, Fiona0000-0002-5469-9035
Rosenfeld, Mia0000-0002-8961-8231
Wauer, Nicholas0000-0002-1230-9166
Russo, John0000-0002-2813-6554
Bogetti, Anthony0000-0003-0610-2879
Trifan, Anda0000-0003-4808-9502
Sztain, Terra0000-0002-1327-8541
Clyde, Austin0000-0002-3697-7070
Ma, Heng0000-0002-7667-922X
Chennubhotla, Chakra0000-0002-0024-1627
Lee, Hyungro0000-0002-4221-7094
Turilli, Matteo0000-0003-0527-1435
Khalid, Syma0000-0002-3694-5044
Qiao, Zhuoran0000-0002-5704-7331
Manby, Frederick0000-0001-7611-714X
Anandkumar, Anima0000-0002-6974-6797
Stone, John0000-0001-7215-762X
Zuckerman, Daniel0000-0001-7662-2031
Miller, Thomas, III0000-0002-1882-5380
Ramanathan, Arvind0000-0002-1622-5488
Chong, Lillian0000-0002-0590-483X
Amaro, Rommie0000-0002-9275-9553
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. We thank Prof. Kim Prather for inspiring and informative discussions about aerosols and for her commitment to convey the airborne nature of SARS-CoV-2. We thank D. Veesler for sharing the Delta spike NTD coordinates in advance of publication. We thank B. Messer, D. Maxwell, and the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory supported by the DOE under Contract DE-AC05-00OR22725. We thank the Texas Advanced Computing Center Frontera team, especially D. Stanzione and T. Cockerill, and for compute time made available through a Director’s Discretionary Allocation (NSF OAC-1818253). We thank the Argonne Leadership Computing Facility supported by the DOE under DE-AC02-06CH11357. We thank the Pittsburgh Supercomputer Center for providing priority queues on Bridges-2 through the XSEDE allocation NSF TG-CHE060063. We thank N. Kern and J. Lee of the CHARMM-GUI support team for help converting topologies between NAMD and GROMACS. We thank J. Copperman, G. Simpson, D. Aristoff, and J. Leung for valuable discussions and support from NIH grant GM115805. NAMD and VMD are funded by NIH P41-GM104601. This work was supported by the NSF Center for Aerosol Impacts on Chemistry of the Environment (CAICE), National Science Foundation Center for Chemical Innovation (NSF CHE-1801971), as well as NIH GM132826, NSF RAPID MCB-2032054, an award from the RCSA Research Corp., a UC San Diego Moore’s Cancer Center 2020 SARS-CoV-2 seed grant, to R.E.A. This work was also supported by Oracle Cloud credits and related resources provided by the Oracle for Research program. The authors have declared no competing interest.
Funding AgencyGrant Number
Department of Energy (DOE)DE-AC05-00OR22725
Department of Energy (DOE)DE-AC02-06CH11357
University of California, San DiegoUNSPECIFIED
Oracle for Research programUNSPECIFIED
Subject Keywords:molecular dynamics, deep learning, multiscale simulation, weighted ensemble, computational virology, SARS-CoV-2, aerosols, COVID-19, HPC, AI, GPU, Delta
PubMed Central ID:PMC8609898
Record Number:CaltechAUTHORS:20220208-947187000
Persistent URL:
Official Citation:#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol Abigail Dommer, Lorenzo Casalino, Fiona Kearns, Mia Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, Sofia Oliveira, Clare Morris, Anthony Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai Krishna Sirumalla, Michael O’Connor, Frederick Manby, Anima Anandkumar, David Hardy, James Phillips, Abraham Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John McCalpin, Christopher Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John Stone, Daniel Zuckerman, Adrian Mulholland, Thomas Miller III, Shantenu Jha, Arvind Ramanathan, Lillian Chong, Rommie Amaro bioRxiv 2021.11.12.468428; doi:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113328
Deposited By: George Porter
Deposited On:08 Feb 2022 21:00
Last Modified:18 Oct 2022 21:43

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