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  4. Homology modelling of the human adenosine A(2B) receptor based on X-ray structures of bovine rhodopsin, the beta(2)-adrenergic receptor and the human adenosine A(2A) receptor
 
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2009
Journal Article
Title

Homology modelling of the human adenosine A(2B) receptor based on X-ray structures of bovine rhodopsin, the beta(2)-adrenergic receptor and the human adenosine A(2A) receptor

Abstract
A three-dimensional model of the human adenosine A(2B) receptor was generated by means of homology modelling, using the crystal structures of bovine rhodopsin, the beta(2)-adrenergic receptor, and the human adenosine A(2A) receptor as templates. In order to compare the three resulting models, the binding modes of the adenosine A(2B) receptor antagonists theophylline, ZM241385, MRS1706, and PSB601 were investigated. The A(2A)-based model was much better able to stabilize the ligands in the binding site than the other models reflecting the high degree of similarity between A(2A) and A(2B) receptors: while the A(2B) receptor shares about 21% of the residues with rhodopsin, and 31% with the beta(2)-adrenergic receptor, it is 56% identical to the adenosine A(2A) receptor. The A(2A)-based model was used for further studies. The model included the transmembrane domains, the extracellular and the intracellular hydrophilic loops as well as the terminal domains. In order to validate the usefulness of this model, a docking analysis of several selective and nonselective agonists and antagonists was carried out including a study of binding affinities and selectivities of these ligands with respect to the adenosine A(2A) and A(2B) receptors. A common binding site is proposed for antagonists and agonists based on homology modelling combined with site-directed mutagenesis and a comparison between experimental and calculated affinity data. The new, validated A(2B) receptor model may serve as a basis for developing more potent and selective drugs.
Author(s)
Sherbiny, F.F.
Schiedel, A.C.
Maaß, A.
Müller, C.E.
Journal
Journal of computer aided molecular design  
DOI
10.1007/s10822-009-9299-7
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
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