Faculty Opinions recommendation of Uncoupling the Structure-Activity Relationships of β2 Adrenergic Receptor Ligands from Membrane Binding.

2016 ◽  
Author(s):  
John Lowe
Keyword(s):  
Adrenergic Receptor ◽  
Membrane Binding ◽  
Receptor Ligands ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Β2 Adrenergic Receptor ◽  
Adrenergic Receptor Ligands

Uncoupling the Structure–Activity Relationships of β2 Adrenergic Receptor Ligands from Membrane Binding

2016 ◽  
Vol 59 (12) ◽  
pp. 5780-5789 ◽  
Author(s):  
Callum J. Dickson ◽  
Viktor Hornak ◽  
Camilo Velez-Vega ◽  
Daniel J. J. McKay ◽  
John Reilly ◽  
...  
Keyword(s):  
Adrenergic Receptor ◽  
Membrane Binding ◽  
Receptor Ligands ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Β2 Adrenergic Receptor ◽  
Adrenergic Receptor Ligands

β 3 -Adrenergic receptor ligands: insight into structure–activity relationships using Monte-Carlo conformational analysis in water

Tetrahedron ◽  
2001 ◽  
Vol 57 (9) ◽  
pp. 1849-1855 ◽  
Author(s):  
Marco De Amici ◽  
Carlo De Micheli ◽  
Laurent Kassi ◽  
Giacomo Carrea ◽  
Gianluca Ottolina ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Conformational Analysis ◽  
Adrenergic Receptor ◽  
Receptor Ligands ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Adrenergic Receptor Ligands ◽  
Insight Into

Binding-Site Compatible Fragment Growing Applied to the Design of β2-Adrenergic Receptor Ligands

2018 ◽  
Vol 61 (3) ◽  
pp. 1118-1129 ◽  
Author(s):  
Florent Chevillard ◽  
Helena Rimmer ◽  
Cecilia Betti ◽  
Els Pardon ◽  
Steven Ballet ◽  
...  
Keyword(s):  
Binding Site ◽  
Adrenergic Receptor ◽  
Receptor Ligands ◽  
Β2 Adrenergic Receptor ◽  
Adrenergic Receptor Ligands

scholarly journals Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Besma Benredjem ◽  
Jonathan Gallion ◽  
Dennis Pelletier ◽  
Paul Dallaire ◽  
Johanie Charbonneau ◽  
...  
Keyword(s):  
Side Effects ◽  
Adrenergic Receptor ◽  
Unsupervised Clustering ◽  
Operational Parameters ◽  
Receptor Ligands ◽  
Clinical Responses ◽  
Β2 Adrenergic Receptor ◽  
Adrenergic Receptor Ligands ◽  
G Protein Coupled

Abstract Signaling diversity of G protein-coupled (GPCR) ligands provides novel opportunities to develop more effective, better-tolerated therapeutics. Taking advantage of these opportunities requires identifying which effectors should be specifically activated or avoided so as to promote desired clinical responses and avoid side effects. However, identifying signaling profiles that support desired clinical outcomes remains challenging. This study describes signaling diversity of mu opioid receptor (MOR) ligands in terms of logistic and operational parameters for ten different in vitro readouts. It then uses unsupervised clustering of curve parameters to: classify MOR ligands according to similarities in type and magnitude of response, associate resulting ligand categories with frequency of undesired events reported to the pharmacovigilance program of the Food and Drug Administration and associate signals to side effects. The ability of the classification method to associate specific in vitro signaling profiles to clinically relevant responses was corroborated using β2-adrenergic receptor ligands.

Quantification of Ligand Bias for Clinically Relevant β2-Adrenergic Receptor Ligands: Implications for Drug Taxonomy

2013 ◽  
Vol 85 (3) ◽  
pp. 492-509 ◽  
Author(s):  
Emma T. van der Westhuizen ◽  
Billy Breton ◽  
Arthur Christopoulos ◽  
Michel Bouvier
Keyword(s):  
Adrenergic Receptor ◽  
Receptor Ligands ◽  
Β2 Adrenergic Receptor ◽  
Adrenergic Receptor Ligands ◽  
Ligand Bias
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