Identification of ligand-specific G-protein coupled receptor states and prediction of downstream efficacy via data-driven modeling
Abstract
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 (MD) simulations. These reveal shifts towards active-like states at the G protein 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 cAMP 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.
Data availability
The data necessary to reproduce the findings presented in this paper can be found on OSF (DOI 10.17605/OSF.IO/B5RAV). The code used to run and analyze simulations has been deposited on GitHub (https://github.com/delemottelab/demystifying, https://github.com/delemottelab/gpcr-string-method-2019 and https://github.com/delemottelab/state-sampling).
Article and author information
Author details
Funding
Göran Gustafssons Stiftelse
- Jens Carlsson
- Lucie Delemotte
Science for Life Laboratory
- Jens Carlsson
- Lucie Delemotte
Vetenskapsrådet (2017-4676)
- Jens Carlsson
Swedish strategic research program eSSENCE
- Jens Carlsson
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Fleetwood et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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