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

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 使用分布式计算算法和一个由100,000个CPU组成的网络(“Folding@Home”项目)，我们研究了小蛋白质在十微秒到毫秒时间尺度上的动力学。特别是，我们第一次能够从蛋白质的序列开始，模拟所有原子细节的小蛋白质的折叠。此外，我们已经能够预测这些小蛋白的结构和折叠速度，这些预测与实验定量地一致。PSC是Folding@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，供社区其他人研究和数据挖掘。这将进一步利用这100,000个CPU的工作，也有利于其他几个小组的研究。由于这个数据集非常大(TB)，这就需要PSC的数据基础设施和备份系统。

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.