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Integrating Pharmacophore into Membrane Molecular Dynamics Simulations to Improve Homology Modeling of G Protein‐coupled Receptors with Ligand Selectivity: A 2A Adenosine Receptor as an Example
Author(s) -
Zeng Lingxiao,
Guan Mengxin,
Jin Hongwei,
Liu Zhenming,
Zhang Liangren
Publication year - 2015
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.12607
Subject(s) - pharmacophore , homology modeling , molecular dynamics , g protein coupled receptor , receptor , chemistry , molecular model , biophysics , ligand (biochemistry) , molecular recognition , adenosine receptor , computational biology , stereochemistry , biochemistry , biology , molecule , computational chemistry , enzyme , agonist , organic chemistry
Homology modeling has been applied to fill in the gap in experimental G protein‐coupled receptors structure determination. However, achievement of G protein‐coupled receptors homology models with ligand selectivity remains challenging due to structural diversity of G protein‐coupled receptors. In this work, we propose a novel strategy by integrating pharmacophore and membrane molecular dynamics ( MD ) simulations to improve homology modeling of G protein‐coupled receptors with ligand selectivity. To validate this integrated strategy, the A 2A adenosine receptor (A 2A AR), whose structures in both active and inactive states have been established, has been chosen as an example. We performed blind predictions of the active‐state A 2A AR structure based on the inactive‐state structure and compared the performance of different refinement strategies. The blind prediction model combined with the integrated strategy identified ligand–receptor interactions and conformational changes of key structural elements related to the activation of A 2 A AR , including (i) the movements of intracellular ends of TM 3 and TM 5/ TM 6; (ii) the opening of ionic lock; (iii) the movements of binding site residues. The integrated strategy of pharmacophore with molecular dynamics simulations can aid in the optimization in the identification of side chain conformations in receptor models. This strategy can be further investigated in homology modeling and expand its applicability to other G protein‐coupled receptor modeling, which should aid in the discovery of more effective and selective G protein‐coupled receptor ligands.