David E. Konerding

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 of a broader community. We used Googles 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

Relaxation of backbone bond geometry improves protein energy landscape modeling

A key issue in macromolecular structure modeling is the granularity of the molecular representation. A fine‐grained representation can approximate the actual structure more accurately, but may require many more degrees of freedom than a coarse‐grained representation and hence make conformational search more challenging. We investigate this tradeoff between the accuracy and the size of protein conformational search space for two frequently used representations: one with fixed bond angles and lengths and one that has full flexibility. We performed large‐scale explorations of the energy landscapes of 82 protein domains under each model, and find that the introduction of bond angle flexibility significantly increases the average energy gap between native and non‐native structures. We also find that incorporating bonded geometry flexibility improves low resolution X‐ray crystallographic refinement. These results suggest that backbone bond angle relaxation makes an important contribution to native structure energetics, that current energy functions are sufficiently accurate to capture the energetic gain associated with subtle deformations from chain ideality, and more speculatively, that backbone geometry distortions occur late in protein folding to optimize packing in the native state.

Science in the Cloud: Accelerating Discovery in the 21st Century

Scientific discovery is transitioning from a focus on data collection to an emphasis on analysis and prediction using large-scale computation. With appropriate software support, scientists can do these computations with unused cycles in commercial clouds. Moving science into the cloud will promote data sharing and collaborations that will accelerate scientific discovery.

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

Nature Chemistry 6, 15–21 (2014); published online 15 December 2013; corrected after print 24 July 2015. In the version of this Article originally published, Figure 4 displayed incorrectly drawn chemical structures for five of the ligands. The correct structures were, however, used in the calculations.

Erratum: Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways (Nature Chemistry (2014) 6:15-21)

Nature Chemistry 6, 15–21 (2014); published online 15 December 2013; corrected after print 24 July 2015. In the version of this Article originally published, Figure 4 displayed incorrectly drawn chemical structures for five of the ligands. The correct structures were, however, used in the calculations.