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Identification of ligand-specific G protein-coupled receptor states and prediction of downstream efficacy via data-driven modeling.

Oliver FleetwoodJens CarlssonLucie Delemotte
Published in: eLife (2021)
Ligand binding stabilizes different G protein-coupled receptor states via a complex allosteric process that is not completely understood. Here, we have derived free energy landscapes describing activation of the β2 adrenergic receptor bound to ligands with different efficacy profiles using enhanced sampling molecular dynamics simulations. These reveal shifts toward active-like states at the Gprotein-binding site for receptors bound to partial and full agonists, and that the ligands modulate the conformational ensemble of the receptor by tuning protein microswitches. We indeed find an excellent correlation between the conformation of the microswitches close to the ligand binding site and in the transmembrane region and experimentally reported cyclic adenosine monophosphate signaling responses. Dimensionality reduction further reveals the similarity between the unique conformational states induced by different ligands, and examining the output of classifiers highlights two distant hotspots governing agonism on transmembrane helices 5 and 7.
Keyphrases
  • molecular dynamics simulations
  • molecular docking
  • lymph node
  • binding protein
  • genome wide
  • small molecule
  • machine learning
  • amino acid
  • convolutional neural network