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3D-QSAR modeling of binding affinities and functional activities for the set of β2 adrenergic receptor agonists.

Anita Płazińska 1Lucita Jimenez 2Lawrence Toll 2Irving W. Wainer 3Krzysztof Jóźwiak 1

1. Medical University of Lublin (AM), Staszica 6, Lubin 20-081, Poland
2. SRI International (SRI), 333 Ravenswood Ave, Menlo Park 94025, United States
3. National Institute on Aging (NIA), 5600 Nathan Shock Dr, Baltimore, MD 21222, United States

Abstract

β2 adrenergic receptor system is one of the best characterized among G-protein coupled receptors. Our group carries a long term project aimed at development of new selective agonists of the receptor based on the scaffold of fenoterol molecule. Previous results showed that binding affinities strongly depend on the stereochemistry of the molecule. Generally the (R,R)-stereoconfiguration of a derivative is the most effective in binding. In the present study the Comparative Molecular Field Analysis was applied to develop models of binding affinity data generated using two different assays: 1) with [3H]CGP-12177 and 2) with [3H]4-methoxyfenoterol as a marker in radioligand displacement measurements. Two further models were developed for 3) AC50 values determined for tested compounds in agonist induced cAMP accumulation data and 4) IC50 values determined in agonist induced mitogenesis inhibition of astrocytoma 1321N1 cells.

Although these different sets of data are related to one phenomenon (the interactions of an agonist with β2 adrenergic receptor) the are not well correlated with each other. Different molecules appear to be the most effective in different assays. This is consistent with the current understanding of activation mechanisms in GPCRs according to which different agonists may induce different receptor activation state and, thus, different downstream signaling pathways in the cell. These diverse modes of interaction within the receptor binding site were characterized using CoMFA approach and significant differences in generated molecular fields were observed depending on the data modeled. The results may be useful in further steps of designing of new derivatives targeted at particular process/therapy.

 

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Submitted: 2010-02-25 15:24
Revised:   2010-03-17 13:40