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

该子项目是利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 使用分布式计算算法和100，000个CPU的网络（“Folding@Home”项目），我们研究了小蛋白质在10微秒到毫秒时间尺度上的动力学。特别是，我们已经能够，第一次，完全从蛋白质的序列开始，模拟小蛋白质的所有原子细节的折叠。此外，我们已经能够预测这些小蛋白质的结构以及折叠速率，这些预测与实验定量一致。PSC是Folding@Home数据的主要数据存储库。我们正在与PSC合作，最终将这些数据托管给社区的其他人进行研究和数据挖掘。这将进一步利用这10万个CPU的工作，也有利于其他几个小组的研究。由于该数据集非常大（TB），因此需要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.