WikiSysop: Created page with "== Citation == T. Moriya, Y. Yamada, M. Yamamoto, and T. Senda, “GoToCloud optimization of cloud computing environment for accelerating cryo-EM structure-based drug design,” Communications Biology, vol. 7, no. 1, p. 1320, 2024. == Abstract == Cryogenic electron microscopy (Cryo-EM) is a widely used technique for visualizing the 3D structures of many drug design targets, including membrane proteins, at atomic resolution. However, the necessary throughput for struct..."

2024-11-08T10:00:26Z

Created page with "== Citation == T. Moriya, Y. Yamada, M. Yamamoto, and T. Senda, “GoToCloud optimization of cloud computing environment for accelerating cryo-EM structure-based drug design,” Communications Biology, vol. 7, no. 1, p. 1320, 2024. == Abstract == Cryogenic electron microscopy (Cryo-EM) is a widely used technique for visualizing the 3D structures of many drug design targets, including membrane proteins, at atomic resolution. However, the necessary throughput for struct..."

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== Citation ==

T. Moriya, Y. Yamada, M. Yamamoto, and T. Senda, “GoToCloud optimization of cloud computing environment for accelerating cryo-EM structure-based drug design,” Communications Biology, vol. 7, no. 1, p. 1320, 2024.

== Abstract ==

Cryogenic electron microscopy (Cryo-EM) is a widely used technique for visualizing the 3D structures
of many drug design targets, including membrane proteins, at atomic resolution. However, the
necessary throughput for structure-based drug design (SBDD) is not yet achieved. Currently, data
analysis is a major bottleneck due to the rapid advancements in detector technology and image
acquisition methods. Here we show “GoToCloud”, a cloud-computing-based platform for advanced
data analysis and data management in Cryo-EM. With GoToCloud, it is possible to optimize
computing resources and reduce costs by selecting the most appropriate parallel processing settings
for each processing step. Our benchmark tests on GoToCloud demonstrate that parallel computing
settings, including the choice of computational hardware, as well as a required target resolution have
significant impacts on the processing time and cost performance. Through this optimization of a cloud
computing environment, GoToCloud emerges as a promising platform for the acceleration of Cryo-
EM SBDD.

== Keywords ==

== Links ==

https://www.nature.com/articles/s42003-024-07031-6

== Related software ==

== Related methods ==

== Comments ==

2024Moriya GoToCloud - Revision history