Quantitative prediction of selectivity between the A1 and A2A adenosine receptors

Journal of Cheminformatics, vol. 12, pp. 33

Abstract

Abstract The development of drugs is often hampered due to off-target interactions leading to adverse effects. Therefore, computational methods to assess the selectivity of ligands are of high interest. Currently, selectivity is often deduced from bioactivity predictions of a ligand for multiple targets (individual machine learning models). Here we show that modeling selectivity directly, by using the affinity difference between two drug targets as output value, leads to more accurate selectivity predictions. We test multiple approaches on a dataset consisting of ligands for the A1 and A2A adenosine receptors (among others classification, regression, and we define different selectivity classes). Finally, we present a regression model that predicts selectivity between these two drug targets by directly training on the difference in bioactivity, modeling the selectivity-window. The quality of this model was good as shown by the performances for fivefold cross-validation: ROC A1AR-selective 0.88 ± 0.04 and ROC A2AAR-selective 0.80 ± 0.07. To increase the accuracy of this selectivity model even further, inactive compounds were identified and removed prior to selectivity prediction by a combination of statistical models and structure-based docking. As a result, selectivity between the A1 and A2A adenosine receptors was predicted effectively using the selectivity-window model. The approach presented here can be readily applied to other selectivity cases.

Authors 4

1. Lindsey Burggraaff Aachen Division of Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

2. Herman van Vlijmen Aachen Division of Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University · Janssen (Belgium)

   Affiliation as printed

   Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

   Janssen Research & Development, Turnhoutseweg 30, Beerse, Belgium

3. Adriaan P. IJzerman Aachen Division of Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

4. Gerard J. P. van Westen corresponding Aachen Division of Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands. gerard@lacdr.leidenuniv.nl

   Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands