Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

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 THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R2=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 THRβ (R2=0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ 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 THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. 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.

Advances in high-throughput screening technology for toxicology

“…Chang et al (2015) at NICEATM conducted an in vitro-to-in vivo extrapolation (IVIVE) study of 230 potentially ER-active environmental chemicals tested in Tox21 10K screening, suggesting the need of compound pharmacokinetics in prioritising chemicals for further endocrine-related tests. Additionally, Politi et al (2014) demonstrated the usefulness of HTS data in confirming results generated from virtual screening for TR ligands. To supplement current toxicity assessment methods with computational modelling, NCATS launched a crowdsource challenge in 2014 that asked the participants to build computational models predictive of chemical toxicity .…”

CORAL: Prediction of binding affinity and efficacy of thyroid hormone receptor ligands

“…The chemical structures for 181 compounds able to bind at AF-2 domains taken in the literature: collected IC50 values falls into range from 0.310 mM to 100 mM for AF-2 domains [1]. The endpoint under consideration is the negative decimal logarithm of half maximal inhibitory concentration (pIC50) [1].…”

“…The endpoint under consideration is the negative decimal logarithm of half maximal inhibitory concentration (pIC50) [1]. The available data were three times randomly split into the training (z75%), calibration (z12.5%), and validation (z12.5%) sets.…”

“…Endocrine disrupting chemicals are natural or synthetic compounds that have the potential to interfere with the endocrine system, often through imitating or blocking endogenous hormones [1].…”

“…Several functional domains of thyroid hormone receptors have been identified. The important family of chemicals is a ligand-inducible co-activators binding domain termed activation function 2 or AF-2 [1].…”