Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods.
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abstract
The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure-Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THR was assembled to generate both continuous and classification QSAR models with an external accuracy of R(2)=0.55 and CCR=0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THR (R(2)=0.70). Furthermore, molecular docking studies were performed for a set of THR ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THR structures retrieved from the Protein Data Bank. We found that two agonist-bound THR conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THR-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THR. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern.
