3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor β

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor β (TRβ), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q² (cross-validated) values 0.600 and 0.616 and non-cross-validated r² values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (r_pred²) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRβ. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor β but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.