TY - JOUR
T1 - Ligand and structure based models for the identification of beta 2 adrenergic receptor antagonists
AU - Joshi, Jayadev
AU - Dimri, Manali
AU - Ghosh, Subhajit
AU - Shrivastava, Nitisha
AU - Chakraborti, Rina
AU - Sehgal, Neeta
AU - Ray, Jharna
AU - Prem Kumar, Indracanti
N1 - Publisher Copyright:
© 2015 Bentham Science Publishers
PY - 2015/12/1
Y1 - 2015/12/1
N2 - Ligand bound beta 2 adrenergic receptor (β2AR) 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 β2AR antagonist is still a major hurdle. Docking of known antagonists and agonists into activated and ground state β2AR 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.
AB - Ligand bound beta 2 adrenergic receptor (β2AR) 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 β2AR antagonist is still a major hurdle. Docking of known antagonists and agonists into activated and ground state β2AR 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.
KW - Beta blocker
KW - Cluster analysis
KW - Docking
KW - GPCR. SAR
KW - Screening
KW - β2AR
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U2 - 10.2174/1573409911666150812130420
DO - 10.2174/1573409911666150812130420
M3 - Article
C2 - 26265253
AN - SCOPUS:84959454631
SN - 1573-4099
VL - 11
SP - 222
EP - 236
JO - Current Computer-Aided Drug Design
JF - Current Computer-Aided Drug Design
IS - 3
ER -