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 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.
| Errataetall: |
UpdateIn: This article has been published with doi: 10.1177/10943420211006452 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2020 |
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| Enthalten in: |
bioRxiv : the preprint server for biology - (2020) vom: 20. Nov. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Casalino, Lorenzo [VerfasserIn] |
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| Links: |
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| Themen: |
AI |
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| Anmerkungen: |
Date Revised 16.02.2024 published: Electronic UpdateIn: This article has been published with doi: 10.1177/10943420211006452 Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1101/2020.11.19.390187 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM318027097 |
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| 500 | |a UpdateIn: This article has been published with doi: 10.1177/10943420211006452 | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a 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 | ||
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| 700 | 1 | |a Dommer, Abigail |e verfasserin |4 aut | |
| 700 | 1 | |a Gaieb, Zied |e verfasserin |4 aut | |
| 700 | 1 | |a Barros, Emilia P |e verfasserin |4 aut | |
| 700 | 1 | |a Sztain, Terra |e verfasserin |4 aut | |
| 700 | 1 | |a Ahn, Surl-Hee |e verfasserin |4 aut | |
| 700 | 1 | |a Trifan, Anda |e verfasserin |4 aut | |
| 700 | 1 | |a Brace, Alexander |e verfasserin |4 aut | |
| 700 | 1 | |a Bogetti, Anthony |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Heng |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Hyungro |e verfasserin |4 aut | |
| 700 | 1 | |a Turilli, Matteo |e verfasserin |4 aut | |
| 700 | 1 | |a Khalid, Syma |e verfasserin |4 aut | |
| 700 | 1 | |a Chong, Lillian |e verfasserin |4 aut | |
| 700 | 1 | |a Simmerling, Carlos |e verfasserin |4 aut | |
| 700 | 1 | |a Hardy, David J |e verfasserin |4 aut | |
| 700 | 1 | |a Maia, Julio D C |e verfasserin |4 aut | |
| 700 | 1 | |a Phillips, James C |e verfasserin |4 aut | |
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| 700 | 1 | |a Stern, Abraham |e verfasserin |4 aut | |
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