网格上蛋白质的量子化学

T. Ikegami, J. Maki, T. Takami, Yoshio Tanaka, M. Yokokawa, S. Sekiguchi, M. Aoyagi
{"title":"网格上蛋白质的量子化学","authors":"T. Ikegami, J. Maki, T. Takami, Yoshio Tanaka, M. Yokokawa, S. Sekiguchi, M. Aoyagi","doi":"10.1109/GRID.2007.4354128","DOIUrl":null,"url":null,"abstract":"A GridFMO application was developed by recoining the fragment molecular orbital (FMO) method of GAMESS with grid technology. With the GridFMO, quantum calculations of macro molecules become possible by using large amount of computational resources collected from many moderate-sized cluster computers. A new middleware suite was developed based on Ninf-G, whose fault tolerance and flexible resource management were found to be indispensable for long-term calculations. The GridFMO was used to draw ab initio potential energy curves of a protein motor system with 16,664 atoms. For the calculations, 10 cluster computers over the pacific rim were used, sharing the resources with other users via butch queue systems on each machine. A series of 14 GridFMO calculations were conducted for 70 days, coping with more than 100 problems cropping up. The FMO curves were compared against the molecular mechanics (MM), and it was confirmed that (1) the FMO method is capable of drawing smooth curves despite several cut-off approximations, and that (2) the MM method is reliable enough for molecular modeling.","PeriodicalId":304508,"journal":{"name":"2007 8th IEEE/ACM International Conference on Grid Computing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"GridFMO — Quantum chemistry of proteins on the grid\",\"authors\":\"T. Ikegami, J. Maki, T. Takami, Yoshio Tanaka, M. Yokokawa, S. Sekiguchi, M. Aoyagi\",\"doi\":\"10.1109/GRID.2007.4354128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A GridFMO application was developed by recoining the fragment molecular orbital (FMO) method of GAMESS with grid technology. With the GridFMO, quantum calculations of macro molecules become possible by using large amount of computational resources collected from many moderate-sized cluster computers. A new middleware suite was developed based on Ninf-G, whose fault tolerance and flexible resource management were found to be indispensable for long-term calculations. The GridFMO was used to draw ab initio potential energy curves of a protein motor system with 16,664 atoms. For the calculations, 10 cluster computers over the pacific rim were used, sharing the resources with other users via butch queue systems on each machine. A series of 14 GridFMO calculations were conducted for 70 days, coping with more than 100 problems cropping up. The FMO curves were compared against the molecular mechanics (MM), and it was confirmed that (1) the FMO method is capable of drawing smooth curves despite several cut-off approximations, and that (2) the MM method is reliable enough for molecular modeling.\",\"PeriodicalId\":304508,\"journal\":{\"name\":\"2007 8th IEEE/ACM International Conference on Grid Computing\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 8th IEEE/ACM International Conference on Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GRID.2007.4354128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 8th IEEE/ACM International Conference on Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRID.2007.4354128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

利用网格技术对GAMESS的片段分子轨道(FMO)方法进行重构,开发了GridFMO应用程序。有了GridFMO,利用从许多中等规模的集群计算机收集的大量计算资源,大分子的量子计算成为可能。基于Ninf-G开发了一套新的中间件,发现其容错能力和灵活的资源管理是长期计算不可缺少的。利用GridFMO绘制了包含16664个原子的蛋白质马达系统的从头算势能曲线。为了进行计算,使用了太平洋沿岸的10台集群计算机,通过每台机器上的队列系统与其他用户共享资源。在70天内,共进行了14次GridFMO计算,处理了100多个突然出现的问题。将FMO曲线与分子力学(MM)曲线进行了比较,证实了(1)FMO方法能够绘制出光滑的曲线,尽管有几个截止近似;(2)MM方法对于分子建模是足够可靠的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GridFMO — Quantum chemistry of proteins on the grid
A GridFMO application was developed by recoining the fragment molecular orbital (FMO) method of GAMESS with grid technology. With the GridFMO, quantum calculations of macro molecules become possible by using large amount of computational resources collected from many moderate-sized cluster computers. A new middleware suite was developed based on Ninf-G, whose fault tolerance and flexible resource management were found to be indispensable for long-term calculations. The GridFMO was used to draw ab initio potential energy curves of a protein motor system with 16,664 atoms. For the calculations, 10 cluster computers over the pacific rim were used, sharing the resources with other users via butch queue systems on each machine. A series of 14 GridFMO calculations were conducted for 70 days, coping with more than 100 problems cropping up. The FMO curves were compared against the molecular mechanics (MM), and it was confirmed that (1) the FMO method is capable of drawing smooth curves despite several cut-off approximations, and that (2) the MM method is reliable enough for molecular modeling.
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
自引率
0.00%
发文量
0
×
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