CB2 receptor belongs to the large family of G-protein coupled receptors (GPCRs) controlling a wide variety of signal transduction. The recent crystallographic determination of human beta 2 adrenoreceptor and its high sequence similarity with human CB2 receptor (hCB2) prompted us to compute a theoretical model of hCB2 based also on beta 2 adrenoreceptor coordinates. This model has been employed to perform docking and molecular dynamic simulations on WIN-55,212-2 (CB2 agonist commonly used in binding experiments), in order to identify the putative CB2 receptor agonist binding site, followed by molecular docking studies on a series of indol-3-yl-tetramethylcyclopropyl ketone derivatives, a novel class of potent CB2 agonists. Successively, docking-based Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were also performed. The CoMSIA model resulted to be the more predictive, showing r(ncv)(2) = 0.96, r(cv)(2) = 0.713, SEE = 0.193, F = 125.223, and r(pred)(2) = 0.78. The obtained 3D-QSAR models allowed us to derive more complete guidelines for the design of new analogues with improved potency so as to synthesize new indoles showing high CB2 affinity.
Homology modeling in tandem with 3D-QSAR analyses: a computational approach to depict the agonist binding site of the human CB2 receptor.
CICHERO, ELENA;SPALLAROSSA, ANDREA;RANISE, ANGELO;FOSSA, PAOLA
2011-01-01
Abstract
CB2 receptor belongs to the large family of G-protein coupled receptors (GPCRs) controlling a wide variety of signal transduction. The recent crystallographic determination of human beta 2 adrenoreceptor and its high sequence similarity with human CB2 receptor (hCB2) prompted us to compute a theoretical model of hCB2 based also on beta 2 adrenoreceptor coordinates. This model has been employed to perform docking and molecular dynamic simulations on WIN-55,212-2 (CB2 agonist commonly used in binding experiments), in order to identify the putative CB2 receptor agonist binding site, followed by molecular docking studies on a series of indol-3-yl-tetramethylcyclopropyl ketone derivatives, a novel class of potent CB2 agonists. Successively, docking-based Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were also performed. The CoMSIA model resulted to be the more predictive, showing r(ncv)(2) = 0.96, r(cv)(2) = 0.713, SEE = 0.193, F = 125.223, and r(pred)(2) = 0.78. The obtained 3D-QSAR models allowed us to derive more complete guidelines for the design of new analogues with improved potency so as to synthesize new indoles showing high CB2 affinity.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.