RT Journal Article
SR Electronic
T1 Identification of ligand-specific G-protein coupled receptor states and prediction of downstream efficacy via data-driven modeling
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.07.06.186601
DO 10.1101/2020.07.06.186601
A1 Oliver Fleetwood
A1 Jens Carlsson
A1 Lucie Delemotte
YR 2020
UL http://biorxiv.org/content/early/2020/12/21/2020.07.06.186601.abstract
AB G protein-coupled receptors (GPCRs) shift between inactive states and active signaling states, to which intracellular binding partners can bind. Extracellular binding of ligands stabilizes different receptor states and modulates the intracellular response via a complex allosteric process, which is not completely understood. Despite the recent advances in structure determination and spectroscopy techniques, a comprehensive view of the ligand-protein interplay remains a challenge. We derived free energy landscapes describing activation of the β2 adrenergic receptor (β2AR) bound to ligands with different efficacy profiles using enhanced sampling molecular dynamics (MD) simulations. The resulting free energy landscapes reveal clear shifts towards active-like states at the G protein binding site for receptors bound to partial and full agonists compared to antagonists and inverse agonists. Not only do the ligands control the population of states, they also modulate the conformational ensemble of the receptor by tuning allosteric protein microswitches. We find an excellent correlation between the conformation of the microswitches close to the ligand binding site and in the transmembrane region and experimentally reported cAMP signaling responses, highlighting the predictive power of our approach. Using dimensionality reduction techniques, we could further assess the similarity between the unique conformational states induced by different ligands. Two distant hotspots governing agonism on transmembrane helices 5 and 7, including the conserved NPxxY motif, formed the endpoints of an allosteric pathway between the binding sites. Our results demonstrate how molecular dynamics simulations can further provide insights into the mechanism of GPCR regulation by ligands, which may contribute to the design of drugs with specific efficacy profiles.Competing Interest StatementThe authors have declared no competing interest.GPCRsG protein-coupled receptorsMDMolecular dynamicsβ2ARβ2 adrenergic receptorTM1-7Transmembrane helix 1-7H8Helix 8cAMPcyclic adenosine monophosphateCVCollective variablePCAPrincipal component analysisPCprincipal componentMDSMulti-dimensional scalingt-SNET-distributed stochastic neighbor embeddingRMSDRoot-mean-square deviationKL divergenceKullback–Leibler (KL) divergence