Fragment-Based Discovery of Subtype-Selective Adenosine Receptor Ligands from Homology Models

Ranganathan, Anirudh and Stoddart, Leigh A. and Hill, Stephen J. and Carlsson, Jens (2015) Fragment-Based Discovery of Subtype-Selective Adenosine Receptor Ligands from Homology Models. Journal of Medicinal Chemistry, 58 (24). pp. 9578-9590. ISSN 0022-2623

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Fragment-based lead discovery (FBLD) holds great promise for drug discovery, but applications to G protein-coupled receptors (GPCRs) have been limited by a lack of sensitive screening techniques and scarce structural information. If virtual screening against homology models of GPCRs could be used to identify fragment ligands, FBLD could be extended to numerous important drug targets and contribute to efficient lead generation. Access to models of multiple receptors may further enable the discovery of fragments that bind specifically to the desired target. To investigate these questions, we used molecular docking to screen >500 000 fragments against homology models of the A3 and A1 adenosine receptors (ARs) with the goal to discover A3AR-selective ligands. Twenty-one fragments with predicted A3AR-specific binding were evaluated in live-cell fluorescence-based assays; of eight verified ligands, six displayed A3/A1 selectivity, and three of these had high affinities ranging from 0.1 to 1.3 μM. Subsequently, structure-guided fragment-to-lead optimization led to the identification of a >100-fold-selective antagonist with nanomolar affinity from commercial libraries. These results highlight that molecular docking screening can guide fragment-based discovery of selective ligands even if the structures of both the target and antitarget receptors are unknown. The same approach can be readily extended to a large number of pharmaceutically important targets.

Item Type: Article
Schools/Departments: University of Nottingham UK Campus > Faculty of Medicine and Health Sciences > School of Life Sciences
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Depositing User: Eprints, Support
Date Deposited: 18 Jul 2016 08:09
Last Modified: 14 Sep 2016 02:05

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