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Cloud-based simulations on Google Exacycle reveal ligand-modulation of GPCR activation pathways

Simulations can provide tremendous insight into atomistic details of biological mechanisms, but micro- to milliseconds timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative, bringing long-timescale processes within reach...

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Detalles Bibliográficos
Autores principales: Kohlhoff, Kai J., Shukla, Diwakar, Lawrenz, Morgan, Bowman, Gregory R., Konerding, David E., Belov, Dan, Altman, Russ B., Pande, Vijay S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3923464/
https://www.ncbi.nlm.nih.gov/pubmed/24345941
http://dx.doi.org/10.1038/nchem.1821
Descripción
Sumario:Simulations can provide tremendous insight into atomistic details of biological mechanisms, but micro- to milliseconds timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative, bringing long-timescale processes within reach of a broader community. We used Google's Exacycle cloud computing platform to simulate 2 milliseconds of dynamics of the β2 adrenergic receptor — a major drug target G protein-coupled receptor (GPCR). Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a GPCR, revealing multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design