Abstract
Quantitative structure–activity relationship (QSAR) has been applied to a set of thyroid hormone receptor β 1 (TRβ 1) antagonists, which are of special interest because of their potential role in safe therapies for nonthyroid disorders while avoiding the cardiac side effects. Using the calculated structural descriptors by CODESSA program, principal component analysis (PCA) was performed on the whole compounds to assist the separation of the data into the training set and the test set in QSAR analysis. Six molecular descriptors selected by genetic algorithm (GA) were used as inputs for a projection pursuit regression (PPR) study to develop a more accurate QSAR model. The PPR model performs well both in the fitting and prediction capacity. For the test set, it gave a predictive correlation coefficient ( R) of 0.9450, root mean square error (RMSE) of 0.4498, and absolute average relative deviation (AARD) of 4.19%, respectively, confirming the ability of PPR for the prediction of the binding affinities of compounds to β 1 isoform of human thyroid hormone receptor (TRβ 1).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.