bioRxivPharmacology & Toxicology
Predicting the activation of the androgen receptor by mixtures of ligands using Generalized Concentration Addition
Abstract
Concentration/dose addition (CA) is widely used for compounds that act by similar mechanisms. But, CA cannot make predictions for mixtures of full and partial agonists for effect levels above that of the least efficacious component. As partial agonists are common, we developed Generalized Concentration Addition (GCA), which has been successfully applied to systems in which ligands compete for a single binding site. Here, we applied a pharmacodynamic model for a system with two binding sites, the androgen receptor (AR). AR acts according to the classic homodimer activation model: each cytoplasmic AR protein binds ligand, undergoes a conformational change that relieves inhibition of dimerization, and binds to DNA response elements as a dimer. We generated individual dose-response data for full (dihydroxytestosterone, BMS564929) and partial (TFM-4AS-1) agonists and a competitive antagonist (MDV3100) using reporter data generated in the MDA-kb2 cell line. We used the Schild method to estimate the binding affinity of AR for MDV3100. Data for individual compounds fit the AR pharmacodynamic model well. The partial agonist had agonistic effects at low effect levels and antagonistic effects at high levels, as predicted by pharmacological theory. The GCA model fit the empirical mixtures data--full/full agonist, full/partial agonist and full agonist/antagonist--as well or better than relative potency factors (a special case of CA) or effect summation. The ability of generalized concentration addition to predict the activity of mixtures of different types of androgen receptor ligands is important as a number of environmental compounds act as partial AR agonists or antagonists.
- organism: human
- assay: proteomics
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
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