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Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D-2 receptor

Journal article
Authors Marcus Malo
Ronnie Persson
Peder Svensson
Kristina Luthman
Lars Brive
Published in Journal of Computer-Aided Molecular Design
Volume 27
Issue 3
Pages 277-291
ISSN 0920-654X
Publication year 2013
Published at Department of Chemistry and Molecular Biology
Institute of Biomedicine, Department of Medical Biochemistry and Cell Biology
Pages 277-291
Language en
Links dx.doi.org/10.1007/s10822-013-9640-...
Keywords GPCR, 7TM, Membrane protein, Dopamine D-2 receptor, Structure prediction, Receptor modeling, protein-coupled receptor, 2nd extracellular loop, angstrom, crystal-structure, a(2a) adenosine receptor, predicted 3d structure, binding-site, beta-2-adrenergic receptor, conformational-changes, beta(2) adrenoceptor, structural insights
Subject categories Cell and Molecular Biology

Abstract

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

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