Transmembrane signaling mechanisms of plexin - Supplement

此申请是为了申请购买高端计算和数据存储的资金 系统的低温电子显微镜（cryo-EM）工作的母项目，重点是 跨膜受体丛蛋白的冷冻电镜结构和机制分析。在 在过去的几年里，母项目已经产生了一些高影响力的低温电磁结构， 丛蛋白和相关的跨膜受体，这大大推进了理解 他们的信号机制。在此期间，计算和数据的基础设施 存储已成为一个主要瓶颈。低温EM数据收集的吞吐量已经 以非常快的速度增加，导致大量的数据，使确定 蛋白质的高分辨率结构，这在以前是不可能的。因此，快速 需要计算机来处理这些数据，并利用新的方法， 每天都在改善，但也需要更多的资源。需要大型存储服务器 安全存储和轻松访问数据。实验室一直依赖于一个工作站 12 TB硬盘的数据收集速率为每天约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 在GPU工作站上对每个结构进行测试需要几天或几周的时间， 延迟作为数据集在队列中等待。此外，目前的GPU有12 GB内存， 限制了可加工的蛋白质复合物结构的尺寸。这项建议 因此，要求资金购买一个为冷冻EM建造的计算系统，有16个GPU 配备48 GB内存和1 PB RAID硬盘单元。这是一项投资，将大大有利于 在未来的几年里，我们的研究领域和研究领域。

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.