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Published March 2015 | Published + Supplemental Material
Journal Article Open

Predicted Structures for Kappa Opioid G‑Protein Coupled Receptor Bound to Selective Agonists

Abstract

Human kappa opioid receptor (κ-OR), a G protein-coupled receptor (GPCR), has been identified as a drug target for treatment of such human disorders as pain perception, neuroendocrine physiology, affective behavior, and cognition. In order to find more selective and active agonists, one would like to do structure based drug design. Indeed, there is an X-ray structure for an antagonist bound to κ-OR, but structures for activated GPCRs are quite different from those for the inactive GPCRs. Here we predict the ensemble of 24 low-energy structures of human kappa opioid receptor (κ-OR), obtained by application of the GEnSeMBLE (GPCR Ensemble of Structures in Membrane Bilayer Environment) complete sampling method, which evaluates 13 trillion combinations of tilt and rotation angles for κ-OR to select the best 24. To validate these structures, we used the DarwinDock complete sampling method to predict the binding sites for five known agonists (ethylketocyclazocine, bremazocine, pentazocine, nalorphine, and morphine) bound to all 24 κ-OR conformations. We find that some agonists bind selectively to receptor conformations that lack the salt bridge between transmembrane domains 3 and 6 as expected for active conformations. These 3D structures for κ-OR provide a structural basis for understanding ligand binding and activation of κ-OR, which should be useful for guiding subtype specific drug design.

Additional Information

© 2015 American Chemical Society. ACS AuthorChoice - This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes. Received: August 29, 2014; Published: February 2, 2015; Publication Date (Web): February 2, 2015. We thank Prof. Ravinder Abrol and Mr. Adam Griffith for many helpful discussions. This work was supported by grants from China Scholarship Council and by gifts to the Materials and Process Simulation Center. The computational resources were provided the NSF-CSEM grant to Caltech and the DURIP-ONR grant to W.A.G.

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