Abstract
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.
Keywords: β2AR, beta blocker, cluster analysis, docking, GPCR. SAR, screening.
Current Computer-Aided Drug Design
Title:Ligand and Structure Based Models for the Identification of Beta 2 Adrenergic Receptor Antagonists
Volume: 11 Issue: 3
Author(s): Jayadev Joshi, Manali Dimri, Subhajit Ghosh, Nitisha Shrivastava, Rina Chakraborti, Neeta Sehgal, Jharna Ray and Indracanti Prem Kumar
Affiliation:
Keywords: β2AR, beta blocker, cluster analysis, docking, GPCR. SAR, screening.
Abstract: 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.
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Joshi Jayadev, Dimri Manali, Ghosh Subhajit, Shrivastava Nitisha, Chakraborti Rina, Sehgal Neeta, Ray Jharna and Kumar Prem Indracanti, Ligand and Structure Based Models for the Identification of Beta 2 Adrenergic Receptor Antagonists, Current Computer-Aided Drug Design 2015; 11 (3) . https://dx.doi.org/10.2174/1573409911666150812130420
DOI https://dx.doi.org/10.2174/1573409911666150812130420 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |

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