FOLDING@HOME: SIMULATING PROTEIN FOLDING WITH MASSIVELY PARALLEL DISTRIBUTED CO

FOLDING@HOME：使用大规模并行分布式 CO 模拟蛋白质折叠

• 批准号: 7956078
• 负责人: VIJAY S PANDE
• 金额: $ 0.08万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7956078
• 关键词: Algorithms; Amino Acid Sequence; Biomedical Research; Communities; Computer Retrieval of Information on Scientific Projects Database; Data; Data Set; Databases; Funding; Grant; High Performance Computing; Institution; Peptide Sequence Determination; Proteins; Research; Research Infrastructure; Research Personnel; Resources; Rest; Simulate; Source; Structure; System; Time; United States National Institutes of Health; Work; cluster computing; data mining; millisecond; protein folding; research study; Algorithms; Amino Acid Sequence; Biomedical Research; Communities; Computer Retrieval of Information on Scientific Projects Database; Data; Data Set; Databases; Funding; Grant; High Performance Computing; Institution; Peptide Sequence Determination; Proteins; Research; Research Infrastructure; Research Personnel; Resources; Rest; Simulate; Source; Structure; System; Time; United States National Institutes of Health; Work; cluster computing; data mining; millisecond; protein folding; research study

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Using distributed computing algorithms and a network of 100,000 CPUs (the "Folding@Home" project), we have studied dynamics of small proteins on the ten of microseconds to millisecond timescale. In particular, we have been able to, for the first time, simulate the folding of small proteins in all atom detail starting purely from the protein`s sequence. Moreover, we have been able to predict the structure of these small proteins as well as the folding rate, and these predictions have quantitatively agreed with experiment. PSC is the main data repository for Folding@Home data. We are working with PSC to eventually host this data for the rest of the community to study and data mine. This woul further leverage the work of these 100,000 CPUs, benefiting the research of several other groups as well. Since this data set is very large (terabytes), this is something which requires PSC`s data infrastructure and backup systems.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 使用分布式计算算法和100,000个CPU（“折叠@home”项目）的网络，我们研究了小蛋白在微秒十毫秒到毫秒的时间表上的小蛋白的动力学。特别是，我们首次能够模拟所有原子细节中小蛋白的折叠，这纯粹是从蛋白质序列开始的。此外，我们已经能够预测这些小蛋白质的结构以及折叠率，并且这些预测已与实验定量达成一致。 PSC是用于折叠@HOME数据的主要数据存储库。我们正在与PSC合作，最终托管这些数据供社区其他成员研究和数据矿山。这将进一步利用这10万CPU的工作，从而使其他几个小组的研究受益。由于此数据集非常大（Terabytes），因此需要PSC的数据基础架构和备份系统。