Identifying Novel Adenosine Receptor Ligands by Simultaneous Proteochemometric Modeling of Rat and Human Bioactivity Data

The four subtypes of adenosine receptors form relevant
drug targets
in the treatment of, e.g., diabetes and Parkinson’s disease.
In the present study, we aimed at finding novel small molecule ligands
for these receptors using virtual screening approaches based on proteochemometric
(PCM) modeling. We combined bioactivity data from all human and rat
receptors in order to widen available chemical space. After training
and validating a proteochemometric model on this combined data set
(Q2 of 0.73, RMSE of 0.61), we virtually
screened a vendor database of 100910 compounds. Of 54 compounds purchased,
six novel high affinity adenosine receptor ligands were confirmed
experimentally, one of which displayed an affinity of 7 nM on the
human adenosine A1 receptor. We conclude that the combination
of rat and human data performs better than human data only. Furthermore,
we conclude that proteochemometric modeling is an efficient method
to quickly screen for novel bioactive compounds.