bioRxivBiophysicsPreprint
End-to-end automation of repeat-target cryo-EM structure determination in CryoSPARC
CryoSPARC Team, Kelly Barber, Hannah R. BridgesiD, Suhail Dawood, Katherine Elder, Nick Frasser, Fiona Hu, Serena Liu, M. McLean, Ryan Narine, Telisha Ng, Valentin PeretroukhiniD, Ali PunjaniiD, Harris Snyder, Kye StachowskiiD, W. TempeliD, Saara Virani, Rich Waldo, Christina Wang, Nicholas Wong
Abstract
Single particle cryo-EM is a valuable and growing technique for life science and drug discovery. Currently, obtaining state-of-the-art results from cryo-EM data analysis requires a human in the loop to analyze intermediate results and make image processing decisions. This bottleneck limits the achievable throughput of structure determination, especially in high-throughput settings such as structure-based drug design. In this work, we develop an end-to-end automation strategy for repeat-target structure determination using new tools in CryoSPARC. We demonstrate completely hands-off processing of 21 challenging G protein-coupled receptor (GPCR) datasets. In 17 of 21 cases, automated processing meets or exceeds published resolution and map quality and, in several cases, provides significant improvement in receptor and ligand density that allows improved model building. Our results on both active and inactive state GPCRs show that our automation strategy generalizes easily to new target classes, and that complete automation of data processing is straightforward to achieve in CryoSPARC. We provide downloadable CryoSPARC Workflow files so that users can import, replicate, adapt and extend our automated workflow for their own targets, enabling cryo-EM to be applied at larger scales and to answer larger biological questions.
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