De Koning, G.H.P.

Derijks, H.J.

Egberts, A.C.G.

Heerdink, E.R.

Janknegt, R.

Loonen, A.J.M.

Olivier, B.

Objective: To construct a model for classification of antidepressants on the basis of their binding properties to six common transporter and receptor sites. Design and methods: Receptor binding was quantified by calculating receptor/ transporter occupancy (hereafter: receptor occupancy) for the serotonin (5HT) transporter, norepinephrine (NE) transporter, 5HT2Creceptor, M3receptor, H1receptor and a, receptor. Receptor occupancy has been proven to be an appropriate measure to estimate the pharmacological effects among drugs with the same mechanism of action. To identify groups of antidepressants showing similar patterns of receptor occupancy for different receptors, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were performed. To visualize (a)symmetry between binding profiles of antidepressants, radar plots were used. Results: On the basis of HCA, PCA and the radar plots, four clusters of antidepressants with similar pharmacological properties were identified. The first cluster (sertraline, fluvoxamine, escitalopram, paroxetine, venlafaxine, fluoxetine, Citalopram, duloxetine and clomipramine) included antidepressants with specific affinity for the 5HT transporter. The second cluster (amitriptyline, doxepin and Imipramine) included antidepressants with high affinity for all receptors Investigated. The third cluster (maprotiline, nortriptyline, mianserin and mirtazapine) included antidepressants with high affinity for the NE transporter, H1receptor and 5HT2Creceptor. The fourth cluster (trazodone, nefazodone, reboxetine and bupropion) was identified as group with no specific similarities. Conclusions: The use of the receptor occupancy theory combined with HCA, PCA and radar plots is a useful method to visualize (a)symmetry in binding profiles of antidepressants. It could be a helpful tool in evidence-based practice, selecting the right antidepressant for the right patient, and may be used in pharmacovigilance as a prediction model for adverse effects of novel drugs entering the market

Visualizing pharmacological activities of antidepressants

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