Structure-based approach for the study of thyroid hormone receptor binding affinity and subtype selectivity |
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Authors: | Fang-Fang Wang Wei Yang Yong-Hui Shi Xiang-Rong Cheng |
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Affiliation: | 1. The State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122, China;2. Faculty of Medicine, Department of Microbiology, Monash University, Melbourne, Victoria 3800, Australia |
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Abstract: | Thyroid hormone (TH) possesses the ability to lower cholesterol and improve cardiac performance, which have prompted the efforts to design analogs that can utilize the cholesterol-lowering property without adversely affecting heart function. In order to gain insights into the interaction mechanism for agonists at the active site of thyroid hormone receptor β (TRβ), quantitative structure–activity relationship (QSAR) models have been developed on TRβ agonists, significant statistical coefficients were obtained (CoMFA, R2cv, .732), (CoMSIA, R2cv, .853), indicating the internal consistency of the models, the obtained models were further validated using the test set, the acquired R2pred values .7054 and .7129 were in good agreement with the experimental results. The key amino acids affecting ligand binding were identified by molecular docking, and the detailed binding modes of the compounds with different activities were also determined. Furthermore, molecular dynamics (MD) simulations were conducted to assess the reliability of the derived models and the docking results. Moreover, TH exerts significant physiological effects through modulation of the two human thyroid hormone receptor subtypes. Because TRβ and TRα locate in different target cells, selective TR ligands would target specific tissues regulated by one receptor without affecting the other. Thus, the 3D information was analyzed to reveal the most relevant structural features involved in selectivity. The findings serve as the basis for further investigation into selective TRβ/TRα agonists. |
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Keywords: | TRβ TRα CoMFA CoMSIA molecular docking |
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