Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways
| Autor: | Diwakar Shukla, Dan Belov, Vijay S. Pande, David E. Konerding, Russ B. Altman, Kai Kohlhoff, Gregory R. Bowman, Morgan Lawrenz |
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| Rok vydání: | 2013 |
| Předmět: |
State model
Internet Millisecond Markov chain Chemistry business.industry General Chemical Engineering Statistical model Nanotechnology Cloud computing General Chemistry Ligands Ligand (biochemistry) Article Markov Chains Receptors G-Protein-Coupled Modulation Biological system business G protein-coupled receptor |
| Zdroj: | Nature chemistry |
| ISSN: | 1755-4349 1755-4330 |
| DOI: | 10.1038/nchem.1821 |
| Popis: | 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 β2AR. 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. |
| Databáze: | OpenAIRE |
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