Mixed-model QSAR at the glucocorticoid receptor: Prediciting the binding mode and affinity of psychotropic drugsAuthors: Morena Spreafico, Beat Ernst, Markus A. Lill, Martin Smiesko and Angelo Vedani
Department of Pharmaceutical Sciences, University of Basel, CH-4056 Basel, Switzerland.
The glucocorticoid receptor (GR) is a member of the nuclear receptor superfamily that affects immune response, development, and metabolism in target tissues. Glucocorticoids are widely used to treat diverse pathophysiological conditions but their clinical applicability is limited by side effects. A prediction of the binding affinity towards the GR would be beneficial for identifying glucocorticoid-mediated adverse effects triggered by drugs or chemicals. By identifying the binding mode to the GR using flexible docking (software Yeti) and quantifying the binding affinity through multi-dimensional QSAR (software Quasar), we validated a model family based on 110 compounds, representing four different chemical classes. The correlation with the experimental data (cross-validated r2 = 0.702; predictive r2 = 0.719) suggests that our approach is suited for predicting the binding affinity of related compounds towards the GR. After challenging the model by a series of scramble tests, a consensus approach (software Raptor) and a prediction set, it was incorporated into our VirtualToxLab and used to simulate and quantify the interaction of 24 psychotropic drugs with the GR.
Left: Dexamethasone (space-filling model) binding to the glucocorticoid receptor (ribbon, sticks). Hydrogen bonds are indicated as dashed lines.
Right: Consensus scoring using the Quasar and Raptor technologies. The quantity is expressed as pKi, consensus = –log(Ki,Quasar/Ki,Raptor). Error bars indicate the cumulative standard deviation, esdcumulative = √ (esd2Quasar + esd2Raptor).