Ligand and structure based models for the identification of beta 2 adrenergic receptor antagonists

Jayadev Joshi, Manali Dimri, Subhajit Ghosh, Nitisha Shrivastava, Rina Chakraborti, Neeta Sehgal, Jharna Ray, Indracanti Prem Kumar

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)222-236
Number of pages15
JournalCurrent Computer-Aided Drug Design
Volume11
Issue number3
DOIs
StatePublished - Dec 1 2015
Externally publishedYes

Keywords

  • Beta blocker
  • Cluster analysis
  • Docking
  • GPCR. SAR
  • Screening
  • β2AR

ASJC Scopus subject areas

  • Molecular Medicine
  • Drug Discovery

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