AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics

Casalino, Lorenzo; Dommer, Abigail C.; Gaieb, Zied; Barros, Emília P.; Sztain, Terra; Ahn, Surl-Hee; Trifan, Anda; Brace, Alexander; Bogetti, Anthony T.; Clyde, Austin; Ma, Huadóng; Lee, Hyungro; Turilli, Matteo; Khalid, Syma; Chong, Lillian T.; Simmerling, Carlos; Hardy, David J.; Maia, Julio D.C.; Phillips, J. C.; Kurth, Thorsten; Stern, Abraham C.; Huang, Lei; McCalpin, John D.; Tatineni, Mahidhar; Gibbs, Tom; Stone, John E.; Jha, Shantenu; Ramanathan, Arvind; Amaro, Rommie E.

doi:10.1177/10943420211006452

Cited by 111 publications

(100 citation statements)

References 78 publications

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“…Our analysis also motivates several directions for future simulations. While researchers have explored the free energy surface of single RBD open-close transitions (29,30), the thermodynamics of secondary and tertiary RBD opening, as well as the role of multivalent ACE2 binding, should be thoroughly investigated. We note that our current CG model will also likely require additional features to holistically probe SARS-CoV-2 virion binding, fusion, and entry.…”

Section: Discussionmentioning

confidence: 99%

Cooperative multivalent receptor binding promotes exposure of the SARS-CoV-2 fusion machinery core

Pak

et al. 2021

Preprint

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The molecular events that permit the spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to bind, fuse, and enter cells are important to understand for both fundamental and therapeutic reasons. Spike proteins consist of S1 and S2 domains, which recognize angiotensin-converting enzyme 2 (ACE2) receptors and contain the viral fusion machinery, respectively. Ostensibly, the binding of spike trimers to ACE2 receptors promotes the preparation of the fusion machinery by dissociation of the S1 domains. We report the development and use of coarse-grained models and simulations to investigate the dynamical mechanisms involved in viral binding and exposure of the S2 trimeric core. We show that spike trimers cooperatively bind to multiple ACE2 dimers. The multivalent interaction cyclically and processively induces S1 dissociation, thereby exposing the S2 core containing the fusion machinery. Our simulations thus reveal an important concerted interaction between spike trimers and ACE2 dimers that primes the virus for membrane fusion and entry.

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Section: Discussionmentioning

confidence: 99%

Cooperative multivalent receptor binding promotes exposure of the SARS-CoV-2 fusion machinery core

Pak

et al. 2021

Preprint

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“…The integration of AI techniques with WE can further enhance the efficiency of sampling rare events (Brace et al, 2021b, Noé, 2020. One frontier area couples unsupervised linear and non-linear dimensionality reduction methods to identify collective variables/progress coordinates in high-dimensional molecular systems (Bhowmik et al, 2018, Clyde et al, 2021. Such methods may be well suited for analyzing the aerosolized virus.…”

Section: Ai-enhanced We Simulationsmentioning

confidence: 99%

“…We also leveraged a simple, yet powerful unsupervised deep learning method called Anharmonic Conformational Analysis enabled Autoencoders (ANCA-AE) (Clyde et al, 2021) to extract conformational states from our long-timescale WE simulations of Delta spike opening (Fig. 5A,D).…”

Section: Ai-we Simulations Of Delta Spike Openingmentioning

confidence: 99%

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

Dommer¹,

Casalino²,

Kearns³

et al. 2021

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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.ACM Reference FormatAbigail Dommer1†, Lorenzo Casalino1†, Fiona Kearns1†, Mia Rosenfeld1, Nicholas Wauer1, Surl-Hee Ahn1, John Russo,2 Sofia Oliveira3, Clare Morris1, AnthonyBogetti4, AndaTrifan5,6, Alexander Brace5,7, TerraSztain1,8, Austin Clyde5,7, Heng Ma5, Chakra Chennubhotla4, Hyungro Lee9, Matteo Turilli9, Syma Khalid10, Teresa Tamayo-Mendoza11, Matthew Welborn11, Anders Christensen11, Daniel G. A. Smith11, Zhuoran Qiao12, Sai Krishna Sirumalla11, Michael O’Connor11, Frederick Manby11, Anima Anandkumar12,13, David Hardy6, James Phillips6, Abraham Stern13, Josh Romero13, David Clark13, Mitchell Dorrell14, Tom Maiden14, Lei Huang15, John McCalpin15, Christo- pherWoods3, Alan Gray13, MattWilliams3, Bryan Barker16, HarindaRajapaksha16, Richard Pitts16, Tom Gibbs13, John Stone6, Daniel Zuckerman2*, Adrian Mulholland3*, Thomas MillerIII11,12*, ShantenuJha9*, Arvind Ramanathan5*, Lillian Chong4*, Rommie Amaro1*. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing ‘21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI

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“…examining non-linear correlations, we can obtain a succinct description of how global conformational changes are embodied in a simulation. This method, titled ANCA-AE (Clyde et al, 2021), can eciently handle large dimensions (e.g., in the case of the mRTC, the 6,650 C U -atoms lead to approximately 20,000 dimensions) and can eciently run on CPUs. We have shown that ANCA-AE can identify conformational states that share structural and energetic similarities, while characterizing transitional points in the high dimensional landscape.…”

Section: Capturing Global Conformational Transitions With Anharmonic Conformational Analysis Enabled Autoencoders (Anca-ae)mentioning

confidence: 99%

“…The AI inference constantly observes the simulation runs, prunes stagnant ones that are trapped in local energy minima, and spawns new ones from less sampled conformations. We have shown that this approach can accelerate sampling of rare events (for example, in the SARS-CoV-2 Spike opening simulations (Casalino et al, 2021), protein folding (Lee et al, 2019)) by at least an order of magnitude. When integrated with specialized AI-hardware to accelerate the learning, it can provide nearly 4 orders of magnitude speedup (Brace et al, 2021).…”

Section: Current State Of the Artmentioning

confidence: 99%

Intelligent Resolution: Integrating Cryo-EM with AI-driven Multi-resolution Simulations to Observe the SARS-CoV-2 Replication-Transcription Machinery in Action

Trifan

Gorgun

et al. 2021

Preprint

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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

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AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics

Cited by 111 publications

References 78 publications

Cooperative multivalent receptor binding promotes exposure of the SARS-CoV-2 fusion machinery core

Cooperative multivalent receptor binding promotes exposure of the SARS-CoV-2 fusion machinery core

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

Intelligent Resolution: Integrating Cryo-EM with AI-driven Multi-resolution Simulations to Observe the SARS-CoV-2 Replication-Transcription Machinery in Action

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