人工智能驱动的多尺度模拟揭示了新冠病毒刺突蛋白动态变化的机制。

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

作者信息

Casalino Lorenzo, Dommer Abigail C, Gaieb Zied, Barros Emilia P, Sztain Terra, Ahn Surl-Hee, Trifan Anda, Brace Alexander, Bogetti Anthony T, Clyde Austin, Ma Heng, Lee Hyungro, Turilli Matteo, Khalid Syma, Chong Lillian T, Simmerling Carlos, Hardy David J, Maia Julio Dc, Phillips James 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

机构信息

University of California San Diego, La Jolla, CA, USA.

Authors with symbol indicate equal contribution.

出版信息

Int J High Perform Comput Appl. 2021 Sep;35(5):432-451. doi: 10.1177/10943420211006452.

DOI:10.1177/10943420211006452

PMID:38603008

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8064023/

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.

摘要

我们开发了一种可推广的人工智能驱动的工作流程，该流程利用异构高性能计算资源来探索分子系统的时间依赖性动力学。我们使用此工作流程来研究严重急性呼吸综合征冠状病毒2（SARS-CoV-2）刺突蛋白的感染机制，刺突蛋白是主要的病毒感染机制。我们的工作流程能够在各种复杂环境中更高效地研究刺突动力学，包括在完整的SARS-CoV-2病毒包膜模拟中，该模拟包含3亿5000万个原子，并且在橡树岭国家实验室的Summit超级计算机上使用NAMD软件显示出强大的扩展性。我们展示了几个新颖的科学发现，包括阐明刺突的完整聚糖屏蔽、刺突聚糖在调节病毒感染性中的作用，以及刺突与人类血管紧张素转换酶2（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采样，并为未来将此类方法应用于SARS-CoV-2和其他分子系统的更多研究铺平道路。