利用 NAMD 原子埋藏技术实现并行蛋白质折叠的自适应补丁网格策略

IF 3.4 3区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Emerson A. Macedo, Alba C.M.A. Melo
{"title":"利用 NAMD 原子埋藏技术实现并行蛋白质折叠的自适应补丁网格策略","authors":"Emerson A. Macedo,&nbsp;Alba C.M.A. Melo","doi":"10.1016/j.jpdc.2024.104868","DOIUrl":null,"url":null,"abstract":"<div><p>The definition of protein structures is an important research topic in molecular biology currently, since there is a direct relationship between the function of the protein in the organism and the 3D geometric configuration it adopts. The transformations that occur in the protein structure from the 1D configuration to the 3D form are called protein folding. <em>Ab initio</em> protein folding methods use physical forces to model the interactions among the atoms that compose the protein. In order to accelerate those methods, parallel tools such as NAMD were proposed. In this paper, we propose two contributions for parallel protein folding simulations: (a) adaptive patch grid (APG) and (b) the addition of atomic burials (AB) to the traditional forces used in the simulation. With APG, we are able to adapt the simulation box (patch grid) to the current shape of the protein during the folding process. AB forces relate the 3D protein structure to its geometric center and are adequate for modeling globular proteins. Thus, adding AB to the forces used in parallel protein folding potentially increases the quality of the result for this class of proteins. APG and AB were implemented in NAMD and tested in supercomputer environments. Our results show that, with APG, we are able to reduce the execution time of the folding simulation of protein 4LNZ (5,714 atoms, 15 million time steps) from 12 hours and 36 minutes to 11 hours and 8 minutes, using 16 nodes (256 CPU cores). We also show that our APG+AB strategy was successfully used in a realistic protein folding simulation (1.7 billion time steps).</p></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive patch grid strategy for parallel protein folding using atomic burials with NAMD\",\"authors\":\"Emerson A. Macedo,&nbsp;Alba C.M.A. Melo\",\"doi\":\"10.1016/j.jpdc.2024.104868\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The definition of protein structures is an important research topic in molecular biology currently, since there is a direct relationship between the function of the protein in the organism and the 3D geometric configuration it adopts. The transformations that occur in the protein structure from the 1D configuration to the 3D form are called protein folding. <em>Ab initio</em> protein folding methods use physical forces to model the interactions among the atoms that compose the protein. In order to accelerate those methods, parallel tools such as NAMD were proposed. In this paper, we propose two contributions for parallel protein folding simulations: (a) adaptive patch grid (APG) and (b) the addition of atomic burials (AB) to the traditional forces used in the simulation. With APG, we are able to adapt the simulation box (patch grid) to the current shape of the protein during the folding process. AB forces relate the 3D protein structure to its geometric center and are adequate for modeling globular proteins. Thus, adding AB to the forces used in parallel protein folding potentially increases the quality of the result for this class of proteins. APG and AB were implemented in NAMD and tested in supercomputer environments. Our results show that, with APG, we are able to reduce the execution time of the folding simulation of protein 4LNZ (5,714 atoms, 15 million time steps) from 12 hours and 36 minutes to 11 hours and 8 minutes, using 16 nodes (256 CPU cores). We also show that our APG+AB strategy was successfully used in a realistic protein folding simulation (1.7 billion time steps).</p></div>\",\"PeriodicalId\":54775,\"journal\":{\"name\":\"Journal of Parallel and Distributed Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Parallel and Distributed Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0743731524000327\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Parallel and Distributed Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0743731524000327","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

摘要

蛋白质结构的定义是当前分子生物学的一个重要研究课题,因为蛋白质在生物体内的功能与它所采用的三维几何构型有直接关系。蛋白质结构从一维构型到三维形式的转变称为蛋白质折叠。蛋白质折叠方法使用物理力来模拟组成蛋白质的原子之间的相互作用。为了加速这些方法,人们提出了 NAMD 等并行工具。在本文中,我们提出了并行蛋白质折叠模拟的两个贡献:(a) 自适应补丁网格 (APG) 和 (b) 在模拟中使用的传统力之外添加原子埋藏 (AB)。有了 APG,我们就能在折叠过程中根据蛋白质的当前形状调整模拟框(补丁网格)。AB 力将三维蛋白质结构与其几何中心相关联,适用于球状蛋白质建模。因此,将 AB 力添加到并行蛋白质折叠中可能会提高这类蛋白质的结果质量。在 NAMD 中实现了 APG 和 AB,并在超级计算机环境中进行了测试。结果表明,使用 APG,我们能够将 4LNZ 蛋白质(5714 个原子,1500 万个时间步)折叠模拟的执行时间从 12 小时 36 分钟减少到 11 小时 8 分钟,使用 16 个节点(256 个 CPU 内核)。我们还展示了 APG+AB 策略在实际蛋白质折叠模拟(17 亿时间步)中的成功应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive patch grid strategy for parallel protein folding using atomic burials with NAMD

The definition of protein structures is an important research topic in molecular biology currently, since there is a direct relationship between the function of the protein in the organism and the 3D geometric configuration it adopts. The transformations that occur in the protein structure from the 1D configuration to the 3D form are called protein folding. Ab initio protein folding methods use physical forces to model the interactions among the atoms that compose the protein. In order to accelerate those methods, parallel tools such as NAMD were proposed. In this paper, we propose two contributions for parallel protein folding simulations: (a) adaptive patch grid (APG) and (b) the addition of atomic burials (AB) to the traditional forces used in the simulation. With APG, we are able to adapt the simulation box (patch grid) to the current shape of the protein during the folding process. AB forces relate the 3D protein structure to its geometric center and are adequate for modeling globular proteins. Thus, adding AB to the forces used in parallel protein folding potentially increases the quality of the result for this class of proteins. APG and AB were implemented in NAMD and tested in supercomputer environments. Our results show that, with APG, we are able to reduce the execution time of the folding simulation of protein 4LNZ (5,714 atoms, 15 million time steps) from 12 hours and 36 minutes to 11 hours and 8 minutes, using 16 nodes (256 CPU cores). We also show that our APG+AB strategy was successfully used in a realistic protein folding simulation (1.7 billion time steps).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing 工程技术-计算机:理论方法
CiteScore
10.30
自引率
2.60%
发文量
172
审稿时长
12 months
期刊介绍: This international journal is directed to researchers, engineers, educators, managers, programmers, and users of computers who have particular interests in parallel processing and/or distributed computing. The Journal of Parallel and Distributed Computing publishes original research papers and timely review articles on the theory, design, evaluation, and use of parallel and/or distributed computing systems. The journal also features special issues on these topics; again covering the full range from the design to the use of our targeted systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信