Investigating Ligand-Modulation of GPCR Activation Pathways

Molecular dynamics 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 an unprecedented 2 milliseconds of dynamics of the β2 adrenergic receptor (β2AR)_a major drug target G protein-coupled receptor (GPCR). Markov state models aggregating these independent simulations into a single statistical model are validated by previous computational and experimental results and provide the first atomistic description of multiple GPCR activation pathways. We show that agonists and inverse agonists interact differentially with these pathways, creating an opportunity for developing drugs that interact more closely with diverse receptor states, for overall increased efficacy and specificity.