Abstract
A virtual ligand-based screening approach was designed and evaluated for the discovery of new A(2A) adenosine receptor (AR) ligands. For comparison and evaluation, the procedures from a recently published virtual screening study that used the A(2A) AR X-ray crystal structure for the target-based discovery of new A(2A) ligands were largely followed. Several screening models were constructed by deriving the distinguishing structural features from selected sets of A(2A) AR antagonists, so-called frequent substructure mining. The best model in statistical terms was subsequently applied to large-scale virtual screens of a commercial vendor library. This resulted in the selection of 36 candidates for acquisition and testing. Of the selected candidates, eight compounds significantly inhibited radioligand binding at A(2A) AR (>30%) at 10 μM, corresponding to a "hit rate" of 22%. This hit rate is quite similar to that of the referenced target-based virtual screening study, while both approaches yield new, non-overlapping sets of ligands.
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