CDS&E: Adaptive Biomolecular Free Energy Simulations on Massive Computational Grids

CDS

• 批准号: 1665032
• 负责人: Ronald Levy
• 金额: $ 52.43万
• 依托单位: Temple University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1665032&HistoricalAwards=false
• 关键词: CDS& Adaptive; Biomolecular; Free; Energy

Ron Levy of Temple University is supported by an award from the Chemical Theory, Models and Computational Methods Program in the Chemistry Division for the development of powerful computational and statistical tools to provide a fundamental understanding of how proteins function in controlling cellular processes. This project is co-funded by the Computational and Data-Enabled Science and Engineering in Mathematical and Statistical Sciences Program in the Division of Mathematical Sciences, and contributes to the National Strategic Computing Initiative. Understanding how proteins function requires extensive surveys of the molecular landscapes that control which structural states are functional, and knowing the free energy costs associated with transitions between states, including "active" and "inactive" protein states. The adaptive computational techniques based on stochastic reweighting that are being developed in this project make it possible to perform more reliable and accurate simulations of protein-ligand binding and conformational free energy changes of proteins, and to do so at extreme scale, on large computing grids consisting of hundreds of thousands of processors. This capability has important applications in the pharmaceutical industry and for biotechnology. The research is being carried out in an academic environment, where students are trained in state-of-the-art simulation techniques. A key aspect of the research is the creation and dissemination of the new theoretical and computational approaches, implemented as computer scripts and programs made freely available to the community.The focus of this research is on developing new sampling protocols for performing biomolecular simulations on massive but minimally communicating computational grids. The algorithms are designed to scale from campus grids with ~5K processors to the IBM World Community grid with ~500K processors. New free energy reweighting techniques based on stochastic solutions to the unbinned weighted histogram analysis equations are being formulated which can be used to estimate free energies from multi-state biomolecular simulations, when the simulations are locally equilibrated but not close to globally equilibrated at some of the states. Professor Levy is developing an adaptive version of asynchronous replica exchange that incorporates stochastic solutions to the free energy reweighting equations directly into the algorithms used to propagate the trajectories. This project addresses the significant computational and statistical challenges associated with performing and analyzing biomolecular simulations using multi-canonical sampling schemes designed specifically for use on computational grids, and which span sizes from thousands of processors (campus grids) to hundreds of thousands of processors (the IBM World Community Grid (WCG)). Two applications are used to illustrate the new approach and its implementation on the WCG: designing inhibitors of HIV-1 integrase, and exploring the effect of sequence on functional transitions in kinases. Professor Levy provides lectures and hands-on experience with the new codes and techniques through summer schools and workshops in the U.S. and Europe. Codes and scripts are freely disseminated for use by the simulation community, and can be interfaced to widely-used open source molecular dynamics codes such as GROMACS and OpenMM.

天普大学的罗恩·利维 (Ron Levy) 获得了化学部化学理论、模型和计算方法项目的奖项，以表彰其开发强大的计算和统计工具，以提供对蛋白质如何在控制细胞过程中发挥作用的基本了解。该项目由数学科学部数学和统计科学项目中的计算和数据支持的科学与工程共同资助，并为国家战略计算计划做出贡献。 了解蛋白质如何发挥作用需要对控制哪些结构状态发挥作用的分子景观进行广泛的调查，并了解与状态之间转换相关的自由能量成本，包括“活性”和“非活性”蛋白质状态。该项目正在开发的基于随机重新加权的自适应计算技术使得对蛋白质-配体结合和蛋白质构象自由能变化进行更可靠和更准确的模拟成为可能，并且可以在由数十万个处理器组成的大型计算网格上以极端的规模进行模拟。这种能力在制药工业和生物技术中具有重要的应用。该研究是在学术环境中进行的，学生接受最先进的模拟技术培训。该研究的一个关键方面是创建和传播新的理论和计算方法，以计算机脚本和程序的形式免费提供给社区。这项研究的重点是开发新的采样协议，用于在大规模但通信程度最低的计算网格上执行生物分子模拟。这些算法旨在从具有约 5K 处理器的校园网格扩展到具有约 500K 处理器的 IBM World Community 网格。 正在制定基于无分箱加权直方图分析方程的随机解的新自由能重加权技术，当模拟在某些状态下局部平衡但不接近全局平衡时，该技术可用于估计多状态生物分子模拟的自由能。 Levy 教授正在开发异步副本交换的自适应版本，它将自由能重新加权方程的随机解直接纳入用于传播轨迹的算法中。该项目解决了与使用专为计算网格而设计的多规范采样方案执行和分析生物分子模拟相关的重大计算和统计挑战，其规模从数千个处理器（校园网格）到数十万个处理器（IBM World Community Grid (WCG)）。通过两个应用来说明新方法及其在 WCG 上的实施：设计 HIV-1 整合酶抑制剂，并探索序列对激酶功能转换的影响。 Levy 教授通过美国和欧洲的暑期学校和研讨会提供有关新代码和技术的讲座和实践经验。 代码和脚本可以免费传播以供模拟社区使用，并且可以与广泛使用的开源分子动力学代码（例如 GROMACS 和 OpenMM）连接。

项目成果

The UWHAM and SWHAM Software Package

UWHAM 和 SWHAM 软件包

• DOI: 10.1038/s41598-019-39420-x
• 发表时间: 2019
• 期刊: Scientific Reports
• 影响因子: 4.6
• 作者: Zhang, Bin W.;Arasteh, Shima;Levy, Ronald M.
• 通讯作者: Levy, Ronald M.

Absolute Protein Binding Free Energy Simulations for Ligands with Multiple Poses, a Thermodynamic Path That Avoids Exhaustive Enumeration of the Poses

• DOI: 10.1002/jcc.26078
• 发表时间: 2019-10
• 期刊: Journal of Computational Chemistry
• 影响因子: 3
• 作者: Y. Sakae;Bin W. Zhang;R. Levy;N. Deng

Spatially-Decomposed Free Energy of Solvation Based on the Endpoint Density-Functional Method

• DOI: 10.1021/acs.jctc.8b01309
• 发表时间: 2019-05-01
• 期刊: JOURNAL OF CHEMICAL THEORY AND COMPUTATION
• 影响因子: 5.5
• 作者: Ishii, Yoshiki;Yamamoto, Naoki;Levy, Ronald M.
• 通讯作者: Levy, Ronald M.

Massive-Scale Binding Free Energy Simulations of HIV Integrase Complexes Using Asynchronous Replica Exchange Framework Implemented on the IBM WCG Distributed Network

• DOI: 10.1021/acs.jcim.8b00817
• 发表时间: 2019-04-01
• 期刊: JOURNAL OF CHEMICAL INFORMATION AND MODELING
• 影响因子: 5.6
• 作者: Xia，Junchao;Flynn，William;Levy，Ronald M.
• 通讯作者: Levy，Ronald M.

Ligand Binding Thermodynamic Cycles: Hysteresis, the Locally Weighted Histogram Analysis Method, and the Overlapping States Matrix

• DOI: 10.1021/acs.jctc.9b00740
• 发表时间: 2020-01-01
• 期刊: JOURNAL OF CHEMICAL THEORY AND COMPUTATION
• 影响因子: 5.5
• 作者: Cui, Di;Zhang, Bin W.;Levy, Ronald M.
• 通讯作者: Levy, Ronald M.