Data Management for Molecule Simulation : A Throughput-Oriented Approach

分子模拟的数据管理：一种面向吞吐量的方法

• 批准号: 10299289
• 负责人: Yicheng Tu
• 金额: $ 28.77万
• 依托单位: UNIVERSITY OF SOUTH FLORIDA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-22 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10299289
• 关键词: ACE2; Algorithms; Biological; Biological Models; Biological Process; Biomimetic Materials; Collaborations; Communities; Computer Simulation; Computer software; Data; Data Analyses; Data Analytics; Data Management Resources; Data Set; Databases; Development; Distributed Systems; Docking; Genetic Diseases; Human; Individual; Knowledge Discovery; Letters; Location; Medical Research; Medicine; Methodology; Methods; Modeling; Modernization; Molecular; Motion; Names; Online Systems; Outcome; Output; Pathology; Performance; Pharmaceutical Preparations; Play; Process; Publishing; Research; Research Personnel; Resources; Role; SARS-CoV-2 infection; SARS-CoV-2 spike protein; Sampling; Stream; Structural Models; Structure; Structure-Activity Relationship; Supercomputing; System; Systems Analysis; Techniques; Testing; Thermodynamics; Time; Validation; Work; active control; analytical tool; base; big data management; cloud based; computerized data processing; computing resources; cost; data management; design; distributed data; falls; genetic disorder diagnosis; improved; large datasets; molecular dynamics; molecular scale; nano; novel; parallel computer; programs; query optimization; receptor; simulation; simulation software; software systems; task analysis; tool; tool development; wide area network

Project Summary We will design and develop a molecular simulation data management system, we call P2DMS, to analyze large dis- tributed molecular dynamics (MD) simulation data. The salient features of the system include: (1) a push-based local query engine design that handles data in a batch processing manner and processes many queries at the same time; (2) optimized MD analytics tools using modern many-core hardware such as GPUs; and (3) efficient management and access to distributed data over wide area networks, which is quite common for large scale MD simulations. This will be done by building a data analysis layer on top of state-of-the-art distributed big data management systems. The out- come of this project will not only improve the efficiency of MD data processing, but also enable new knowledge discov- ery that is currently regarded difficult or infeasible. In particular, we will integrate the P2DMS program into existing MD simulation packages, and validate the new design with important real-world biological and MD methodological prob- lems. In particular, we will (1) model the structure-function relationships of how the spike protein of SARS-CoV-2 inter- acts with the human angiotensin converting enzyme 2 (ACE2) receptor; and (2) enhance the performance of a recently developed parameter optimization software for active control of MD simulations.

项目摘要 我们将设计和开发一个分子模拟数据管理系统，我们称之为P2DMS，用于分析大样本数据。 分配的分子动力学(MD)模拟数据。该系统的显著特点包括：(1)基于推送的本地 查询引擎设计，以批处理的方式处理数据，同时处理多个查询； (2)使用现代多核硬件(如fi)优化的MD分析工具；以及(3)EF GPU有效的管理和 通过广域网络访问分布式数据，这在大规模MD模拟中是很常见的。这将是 通过在最先进的分布式大数据管理系统上构建数据分析层来实现这一点。外面的- 该项目的实施不仅将提高MD数据处理的效率，而且还将使新的知识发现成为可能。 目前被认为是不受fi崇拜或不可行的每一个。特别是，我们将把P2DMS计划整合到现有的MD中 仿真包，并用重要的真实世界生物学和MD方法学问题来验证新设计。 柠檬。特别是，我们将(1)模拟SARS-CoV-2刺突蛋白如何相互作用的结构-功能关系 与人血管紧张素转换酶2(ACE2)受体作用；以及(2)增强最近一种 开发了用于MD仿真主动控制的参数优化软件。