Ligand and Structure Based Models for the Identification of Beta 2 Adrenergic Receptor Antagonists

被引:1
|
作者
Joshi, Jayadev [1 ,2 ]
Dimri, Manali [1 ]
Ghosh, Subhajit [1 ,2 ]
Shrivastava, Nitisha [1 ]
Chakraborti, Rina [3 ]
Sehgal, Neeta [3 ]
Ray, Jharna [2 ]
Kumar, Indracanti Prem [1 ]
机构
[1] Inst Nucl Med & Allied Sci, Radiat Biosci Div, Delhi 110054, India
[2] Univ Calcutta, SN Pradhan Ctr Neurosci, Kolkata, India
[3] Univ Delhi, Dept Zool, Delhi 110007, India
关键词
beta; 2AR; beta blocker; cluster analysis; docking; GPCR; SAR; screening; MOLECULAR DOCKING; PREDICTION; AGONISTS; DESIGN; STATE;
D O I
10.2174/1573409911666150812130420
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Ligand bound beta 2 adrenergic receptor (beta 2AR) crystal structures are in use for screening of compound libraries for identifying inducers and blockers. However, in case of G protein coupled receptors (GPCR), docking and binding energy (BE) calculations are not enough to discriminate agonist and antagonists. Absence of a reliable model for discriminating beta 2AR antagonist is still a major hurdle. Docking of known antagonists and agonists into activated and ground state beta 2AR revealed several key intermolecular interactions and H-bonding patterns, which in combination, emerged as a model for prediction of antagonists. Present study identifies an alternative binding orientation, within the binding pocket, for blockers and a minimum grid size to lessen the false positive predictions. Cluster analysis revealed structural variability among the antagonists and a conserved pattern in case of agonists. A combination of docking and structure activity relationship (SAR) model reliably discriminated antagonists. Based on key intermolecular interactions, a set of agonists and antagonists useful to SAR, quantitative structure activity relationship (QSAR) and pharmacophore modeling, has also been proposed for identifying antagonists.
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页码:222 / 236
页数:15
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