Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models
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...
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| Format: | Article |
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American Chemical Society
2015
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| Online Access: | https://eprints.nottingham.ac.uk/34664/ |
| _version_ | 1848794906057768960 |
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| author | Ranganathan, Anirudh Stoddart, Leigh A. Hill, Stephen J. Carlsson, Jens |
| author_facet | Ranganathan, Anirudh Stoddart, Leigh A. Hill, Stephen J. Carlsson, Jens |
| author_sort | Ranganathan, Anirudh |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:23:38Z |
| format | Article |
| id | nottingham-34664 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:23:38Z |
| publishDate | 2015 |
| publisher | American Chemical Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-346642020-05-04T17:25:53Z https://eprints.nottingham.ac.uk/34664/ Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models Ranganathan, Anirudh Stoddart, Leigh A. Hill, Stephen J. Carlsson, Jens 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. American Chemical Society 2015-12-24 Article PeerReviewed Ranganathan, Anirudh, Stoddart, Leigh A., 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 1520-4804 http://dx.doi.org/10.1021/acs.jmedchem.5b01120 10.1021/acs.jmedchem.5b01120 10.1021/acs.jmedchem.5b01120 10.1021/acs.jmedchem.5b01120 |
| spellingShingle | Ranganathan, Anirudh Stoddart, Leigh A. Hill, Stephen J. Carlsson, Jens Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| title | Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| title_full | Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| title_fullStr | Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| title_full_unstemmed | Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| title_short | Fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| title_sort | fragment-based discovery of subtype-selective adenosine receptor ligands from homology models |
| url | https://eprints.nottingham.ac.uk/34664/ https://eprints.nottingham.ac.uk/34664/ https://eprints.nottingham.ac.uk/34664/ |