title: Atom-based 3D-QSAR, molecular docking and molecular dynamics simulation assessment of inhibitors for thyroid hormone receptor α and β.
abstract: The three-dimensional quantitative structure-activity relationship (3D-QSAR) for inhibitors of thyroid hormone receptors (TR) α and (TR) β was studied. The training set of the TRα model generated a correlation coefficient (R(2)) =  0.9535, with standard deviation (SD) =  0.3016. From the test set of the TRα model, a Q(2) value for the predicted activities (= 0.4303), squared correlation (random selection R(2)-CV  =  0.6929), Pearson-R (= 0.7294) and root mean square error (RMSE  =  0.6342) were calculated. The P-value for TRα (= 1.411e-96) and TRβ (= 2.108e-165) models indicate a high degree of self-reliance. For the TRβ model, the training set yielded R(2) = 0.9424 with SD = 0.3719. From the test set of TRβ, Q(2) value (= 0.5336), the squared correlation (R(2)-CV  =  0.7201), the Pearson-R (= 0.7852) and RMSE for test set predictions (= 0.8630) all strengthen the good predictive competence of the QSAR model derived. Examination of internal as well as external validation supports the rationality and good predictive ability of the best model. Molecular docking explained the conformations of molecules and important amino acid residues at the docking pocket, and a molecular dynamics simulation study further uncovered the binding process and validated the rationality of docking results. The findings not only lead to a better understanding of interactions between these antagonists and thyroid hormone receptors α and β, but also provide valuable information about the impact of structure on activity that will be very beneficial in the design of novel antagonists with preferred activity.
authors.affiliation: Department of Bioinformatics, University Institute of Engineering and Technology, Chhatrapati Shahu Ji Maharaj University, Kanpur, 208024, Uttar Pradesh, India, manish.kumar.gupta@gmail.com.
authors.forename: Manish Kumar
authors.initials: MK
authors.lastname: Gupta
authors.forename: Krishna
authors.initials: K
authors.lastname: Misra
mesh_terms: D013956:Antithyroid Agents / Q000737:chemistry / Q000378:metabolism / Q000494:pharmacology*; D001665:Binding Sites; D017076:Computer-Aided Design; D030562:Databases, Protein; D015195:Drug Design; D006860:Hydrogen Bonding; D057927:Hydrophobic and Hydrophilic Interactions; D008024:Ligands; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D015394:Molecular Structure; D058990:Molecular Targeted Therapy; D011485:Protein Binding; D011487:Protein Conformation; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results; D037021:Thyroid Hormone Receptors alpha / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism; D037042:Thyroid Hormone Receptors beta / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism
chemical_list: D013956:Antithyroid Agents; D008024:Ligands; D037021:Thyroid Hormone Receptors alpha; D037042:Thyroid Hormone Receptors beta