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Homology Modeling and Molecular Dynamics Simulations of the Mu Opioid Receptor in a Membrane–Aqueous System
Author(s) -
Zhang Yan,
Sham Yuk Y.,
Rajamani Ramkumar,
Gao Jiali,
Portoghese Philip S.
Publication year - 2005
Publication title -
chembiochem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.05
H-Index - 126
eISSN - 1439-7633
pISSN - 1439-4227
DOI - 10.1002/cbic.200400207
Subject(s) - rhodopsin , homology modeling , g protein coupled receptor , chemistry , molecular dynamics , lipid bilayer , transmembrane domain , stereochemistry , opioid receptor , molecular model , receptor , crystallography , biophysics , membrane , biochemistry , opioid , biology , computational chemistry , retinal , enzyme
Three types of opioid receptors—mu, delta, and kappa—belong to the rhodopsin subfamily in the G protein‐coupled receptor superfamily. With the recent characterization of the high‐resolution X‐ray crystal structure of bovine rhodopsin, considerable attention has been focused on molecular modeling of these transmembrane proteins. In this study, a homology model of the mu opioid receptor was constructed based on the X‐ray crystal structure of bovine rhodopsin. A phospholipid bilayer was built around the receptor, and two water layers were placed on both surfaces of the lipid bilayer. Molecular‐dynamics simulations were carried out by using CHARMM for the entire system, which consisted of 316 amino acid residues, 92 phospholipid molecules, 8327 water molecules, and 11 chloride counter ions—40 931 atoms altogether. The whole system was equilibrated for 250 ps followed by another 2 ns dynamic simulation. The opioid ligand naltrexone was docked into the optimized model, and the critical amino acid residues for binding were identified. The mu opioid receptor homology model optimized in a complete membrane–aqueous system should provide a good starting point for further characterization of the binding modes for opioid ligands. Furthermore, the method developed herein will be applicable to molecular model building to other opioid receptors as well as other GPCRs.