GoToCloud optimization of cloud computing environment for accelerating cryo-EM structure-based drug design.
Journal
Communications biology
ISSN: 2399-3642
Titre abrégé: Commun Biol
Pays: England
ID NLM: 101719179
Informations de publication
Date de publication:
14 Oct 2024
14 Oct 2024
Historique:
received:
18
04
2024
accepted:
07
10
2024
medline:
15
10
2024
pubmed:
15
10
2024
entrez:
14
10
2024
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 39402335
doi: 10.1038/s42003-024-07031-6
pii: 10.1038/s42003-024-07031-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1320Subventions
Organisme : Japan Agency for Medical Research and Development (AMED)
ID : JP23ama121001
Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : JP20K15735
Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : JP23H02427
Informations de copyright
© 2024. The Author(s).
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