Transmembrane signaling mechanisms of plexin - Supplement

这个应用是为购买高端计算和数据存储而申请资金 冷冻电子显微镜(CRYO-EM)工作系统在重点关注的父项目下进行 关于跨膜受体丛蛋白的冷冻-EM结构和机理分析。在 在过去的几年里，母项目已经产生了许多具有高冲击性的低温电磁结构 丛蛋白和相关的跨膜受体，这大大促进了人们对 它们的信号机制。在此期间，计算和数据的基础设施 存储已经成为一个主要的瓶颈。CRYO-EM数据收集的吞吐量一直在 以非常快的速度增长，导致海量数据，从而能够确定 蛋白质的高分辨率结构，这在以前是不可能的。相应地，快速 需要计算机来处理这些数据并利用新的方法 每天都在改进，但也需要更多的资源。需要大型存储服务器 用于安全存储和轻松访问数据。该实验室一直依赖于一台工作站 配备12 TB硬盘。数据收集率为每天约2 TB，每次试验约5 TB 蛋白质，可用的磁盘空间严重限制了项目的进展。计算 对于疑难病例，在GPU工作站上对每个结构进行测试需要数天或数周的时间，这导致 延迟，因为数据集在队列中等待。此外，目前的GPU具有12 GB内存， 限制可加工的蛋白质复合体结构的大小。这项建议 因此，请求提供资金，以购买为Cryo-EM建造的具有16个GPU的计算系统 具有48 GB内存和1 PB RAID硬盘单元。这项投资将极大地惠及 母项目和未来几年的研究领域。

This application is to request fund for purchasing of a high-end computation and data storage system for the cryo-electron microscopic (cryo-EM) work under the parent project that is focused on cryo-EM structural and mechanistic analyses of the transmembrane receptor plexin. In the past few years, the parent project has generated a number of high-impact cryo-EM structures of plexin and related transmembrane receptors, which substantially advanced the understanding of their signaling mechanisms. During this period, the infrastructure for computation and data storage have become a major bottleneck. The throughput of cryo-EM data collection has been increasing at a very fast rate, leading to vast amounts of data that enable the determination of high-resolution structures of proteins that was previously not possible. Accordingly, fast computers are required for processing these data and take advantage of new methods that are improving on a daily basis but also more resource demanding. Large storage servers are needed for secure storage and easy access of the data. The lab has been relying on a single workstation with a 12-TB hard-disk. With the data collection rate at ~2 TB per day and ~5 TB per trial of a protein, the available disk space is severely limiting the progress of the project. The calculation of each structure on the GPU workstation takes days or weeks for difficult cases, which leads to delays as datasets waiting in the queue. In addition, the current GPUs have 12 GB memory, limiting the size of the protein complex structures that could be processed. This proposal therefore requests for fund to purchase a computational system built for cryo-EM, with 16 GPUs with 48 GB memory and 1 PB RAID hard-disk unit. This is an invest that will greatly benefit the parent project and the research field for years to come.