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

IF 2.5 3区计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

International Journal of High Performance Computing Applications Pub Date : 2021-09-01 DOI:10.1177/10943420211006452

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

{"title":"AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics.","authors":"Lorenzo Casalino, Abigail C Dommer, Zied Gaieb, Emilia P Barros, Terra Sztain, Surl-Hee Ahn, Anda Trifan, Alexander Brace, Anthony T Bogetti, Austin Clyde, Heng Ma, Hyungro Lee, Matteo Turilli, Syma Khalid, Lillian T Chong, Carlos Simmerling, David J Hardy, Julio Dc Maia, James C Phillips, Thorsten Kurth, Abraham C Stern, Lei Huang, John D McCalpin, Mahidhar Tatineni, Tom Gibbs, John E Stone, Shantenu Jha, Arvind Ramanathan, Rommie E Amaro","doi":"10.1177/10943420211006452","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":54957,"journal":{"name":"International Journal of High Performance Computing Applications","volume":"35 5","pages":"432-451"},"PeriodicalIF":2.5000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064023/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of High Performance Computing Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1177/10943420211006452","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}

引用次数: 0

Abstract

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.

Abstract Image

查看原文本刊更多论文

人工智能驱动的多尺度模拟揭示了 SARS-CoV-2 穗状动态的机制。

我们开发了一种可通用的人工智能驱动工作流，利用异构高性能计算资源来探索分子系统随时间变化的动力学。我们利用该工作流研究了 SARS-CoV-2 穗状病毒的感染机制，它是主要的病毒感染机制。我们的工作流能够在各种复杂环境中更有效地研究尖峰动态，包括在完整的 SARS-CoV-2 病毒包膜模拟中，该模拟包含 3.05 亿个原子，并在使用 NAMD 的 ORNL Summit 上显示出很强的扩展性。我们介绍了几项新的科学发现，包括阐明尖峰的完整聚糖屏蔽、尖峰聚糖在调节病毒传染性中的作用以及尖峰与人类 ACE2 受体之间灵活相互作用的特征。我们还展示了人工智能如何加速不同系统的构象取样，并为将来将这种方法应用于 SARS-CoV-2 和其他分子系统的其他研究铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of High Performance Computing Applications 工程技术-计算机：跨学科应用

CiteScore

6.10

自引率

6.50%

发文量

审稿时长

>12 weeks

期刊介绍： With ever increasing pressure for health services in all countries to meet rising demands, improve their quality and efficiency, and to be more accountable; the need for rigorous research and policy analysis has never been greater. The Journal of Health Services Research & Policy presents the latest scientific research, insightful overviews and reflections on underlying issues, and innovative, thought provoking contributions from leading academics and policy-makers. It provides ideas and hope for solving dilemmas that confront all countries.