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

Kai J. Kohlhoff, Diwakar Shukla, Morgan Lawrenz, Gregory R. Bowman, David E. Konerding, Dan Belov, Russ B. Altman, Vijay S. Pande

Research output: Contribution to journalArticle

245 Scopus citations

Abstract

Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β 2 AR. 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 G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.

Original languageEnglish
Pages (from-to)15-21
Number of pages7
JournalNature Chemistry
Volume6
Issue number1
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

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    Kohlhoff, K. J., Shukla, D., Lawrenz, M., Bowman, G. R., Konerding, D. E., Belov, D., Altman, R. B., & Pande, V. S. (2014). Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways. Nature Chemistry, 6(1), 15-21. https://doi.org/10.1038/nchem.1821