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 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.