Title |
Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways
|
---|---|
Published in |
Nature Chemistry, December 2013
|
DOI | 10.1038/nchem.1821 |
Pubmed ID | |
Authors |
Kai J. Kohlhoff, Diwakar Shukla, Morgan Lawrenz, Gregory R. Bowman, David E. Konerding, Dan Belov, Russ B. Altman, Vijay S. Pande |
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 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 19 | 29% |
Japan | 5 | 8% |
United Kingdom | 4 | 6% |
France | 3 | 5% |
Spain | 3 | 5% |
Sweden | 1 | 2% |
Vietnam | 1 | 2% |
Egypt | 1 | 2% |
Cuba | 1 | 2% |
Other | 3 | 5% |
Unknown | 25 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 39 | 59% |
Scientists | 25 | 38% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 14 | 3% |
Germany | 4 | <1% |
United Kingdom | 4 | <1% |
China | 3 | <1% |
Italy | 2 | <1% |
Canada | 2 | <1% |
Switzerland | 1 | <1% |
Finland | 1 | <1% |
Japan | 1 | <1% |
Other | 1 | <1% |
Unknown | 368 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 124 | 31% |
Researcher | 105 | 26% |
Student > Bachelor | 38 | 9% |
Student > Master | 28 | 7% |
Professor | 17 | 4% |
Other | 47 | 12% |
Unknown | 42 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 95 | 24% |
Agricultural and Biological Sciences | 84 | 21% |
Biochemistry, Genetics and Molecular Biology | 55 | 14% |
Physics and Astronomy | 35 | 9% |
Computer Science | 19 | 5% |
Other | 63 | 16% |
Unknown | 50 | 12% |