http://www.cnr.it/ontology/cnr/individuo/prodotto/ID167408
Homology modeling in tandem with 3D-QSAR analyses: a computational approach to depict the agonist binding site of the human CB2 receptor (Articolo in rivista)
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- Homology modeling in tandem with 3D-QSAR analyses: a computational approach to depict the agonist binding site of the human CB2 receptor (Articolo in rivista) (literal)
- Anno
- 2011-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.ejmech.2011.07.023 (literal)
- Alternative label
Cichero E, Ligresti A, Allarà M, di Marzo V, Lazzati Z, D'Ursi P, Marabotti A, Milanesi L, Spallarossa A, Ranise A, Fossa P. (2011)
Homology modeling in tandem with 3D-QSAR analyses: a computational approach to depict the agonist binding site of the human CB2 receptor
in European journal of medicinal chemistry
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Cichero E, Ligresti A, Allarà M, di Marzo V, Lazzati Z, D'Ursi P, Marabotti A, Milanesi L, Spallarossa A, Ranise A, Fossa P. (literal)
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- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Dipartimento di Scienze Farmaceutiche, Università di Genova, Viale Benedetto XV n. 3, 16132 Genova, Italy
Endocannabinoid Research Group, Istituto di Chimica Biomolecolare, CNR, Via Campi Flegrei 34, 80078 Pozzuoli Napoli, Italy
Institute for Biomedical Technologies National Research Council (ITB-CNR), Via Fratelli Cervi 93, 20090 Segrate (MI), Italy
Institute of Genetics and Biophysics A. Buzzati Traverso National Research Council (IGB-CNR), Via P. Castellino 111, 80131 Naples, Italy (literal)
- Titolo
- Homology modeling in tandem with 3D-QSAR analyses: a computational approach to depict the agonist binding site of the human CB2 receptor (literal)
- 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 b2 adrenoreceptor and its high sequence similarity with human CB2 receptor (hCB2) prompted us to compute a theoretical model of hCB2 based also on b2 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 r2ncv = 0.96, r2cv =0.713, SEE = 0.193, F = 125.223, and r2pred = 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. (literal)
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