Structural and Functional Analyses of the Full-length Insulin Receptor (IR) and Type 1 Insulin-like Growth Factor Receptor (IGF1R) in the Liganded Active State

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This application for supplemental grant is to request fund for purchasing a high performance GPU cluster for single particle cryo-EM data storage and processing, which is under the parent project that is focused on the understanding of the exact ligand induced activation mechanism of insulin receptor and IGF1R. In the last year, we have made tremendous progress toward finishing all the 3 aims of proposed project. Nevertheless, after I submitted the original proposal, our cryo-EM facility has been expanded significantly, currently housing 4 high-end electron microscopies, which is two times more than that one year ago. In addition, our cryo-EM facility has recently implemented a new data collection method with beam-image shift, which increases the throughput of data collection by another factor of 3. As a result, we can collect approximately 6 times more data in certain period, compared with one year ago. Thus, the current two old GPU servers in my lab would not allow us to process all newly generated cryo-EM data in a timely manner, which would lead to delay for the proposed project. Furthermore, with the improved data collection capability after our cryo-EM facility expands, we can generate 4-5 TB new cryo- EM data weekly. Such large amount of data cannot be stored in my old GPU servers for long term. By using an advanced GPU cluster that have 16 powerful GPU cards and 1000 TB storage space, I will be able to finish the processing of one full dataset in a few days. This will also allow me to try several recently developed 3D classification methods to distinguish the structures of full-length receptor/ligand complexes in different conformational states, which will be the key results in this proposed project. With the 1000 TB storage device, we could store more than 50 different datasets in the same time, meaning that each dataset can be stored in the GPU cluster for ~1 year before transferring to a permanent storage device. This would allow me to easily reprocess the data to improve our structures, as soon as a new method for image processing is developed.