Polychlorinated biphenyls(PCBs) can antagonize human pregnane X receptor(hPXR) activation.Such chemicals could pose a serious threat to the reproductive and developmental ability of humans.The quantitative structure a...Polychlorinated biphenyls(PCBs) can antagonize human pregnane X receptor(hPXR) activation.Such chemicals could pose a serious threat to the reproductive and developmental ability of humans.The quantitative structure activity relationship(QSAR) provides a promising method for the estimation of PCBs' antagonistic activity.In this investigation,a QSAR model was developed by using heuristic method and best subset modeling(r2 = 0.873,q2LOO=0.742).The built model was validated externally by splitting the original data set into training and prediction sets.The results of the model derived are as follows:r2 = 0.907,q2LOO=0.709,r2pred=0.676,suggesting developed QSAR model had good robustness and predictive ability.The applicability domain(AD) of the model was assessed by Williams plot.The antagonistic activity(?logKi) of 108 PCBs,which are unavailable by experiment at present,was predicted within the applicability domain of the model.The critical structural features related to the activity of PCBs were identified.展开更多
The human pregnane X receptor（hPXR） plays a critical role in the metabolism, transport and clearance of xenobiotics in the liver and intestine. The hPXR can be activated by a structurally diverse of drugs to initiat...The human pregnane X receptor（hPXR） plays a critical role in the metabolism, transport and clearance of xenobiotics in the liver and intestine. The hPXR can be activated by a structurally diverse of drugs to initiate clinically relevant drug-drug interactions. In this article, in silico investigation was performed on a structurally diverse set of drugs to identify critical structural features greatly related to their agonist activity towards h PXR. Heuristic method（HM）-Best Subset Modeling（BSM） and HM-Polynomial Neural Networks（PNN） were utilized to develop the linear and non-linear quantitative structure-activity relationship models. The applicability domain（AD） of the models was assessed by Williams plot. Statistically reliable models with good predictive power and explain were achieved（for HM-BSM, r^2=0.881, q^2_（LOO）=0.797, q^2_（EXT）=0.674; for HM-PNN, r^2=0.882, q^2_（LOO）=0.856, q^2_（EXT）=0.655）. The developed models indicated that molecular aromatic and electric property, molecular weight and complexity may govern agonist activity of a structurally diverse set of drugs to h PXR.展开更多
基金supported by the Science and Technology Development Foundation Key Project of Nanjing Medical University (09NJMUZ16)Natural Science Research Project of Institution of Higher Education of Jiangsu Province (11KJB180006)
文摘Polychlorinated biphenyls(PCBs) can antagonize human pregnane X receptor(hPXR) activation.Such chemicals could pose a serious threat to the reproductive and developmental ability of humans.The quantitative structure activity relationship(QSAR) provides a promising method for the estimation of PCBs' antagonistic activity.In this investigation,a QSAR model was developed by using heuristic method and best subset modeling(r2 = 0.873,q2LOO=0.742).The built model was validated externally by splitting the original data set into training and prediction sets.The results of the model derived are as follows:r2 = 0.907,q2LOO=0.709,r2pred=0.676,suggesting developed QSAR model had good robustness and predictive ability.The applicability domain(AD) of the model was assessed by Williams plot.The antagonistic activity(?logKi) of 108 PCBs,which are unavailable by experiment at present,was predicted within the applicability domain of the model.The critical structural features related to the activity of PCBs were identified.
基金supported by grants from the Natural Science Research Project of Institution of Higher Education of Jiangsu Province(No.11KJB180006)National Natural Science Foundation of China(No.21277074 and No.81302458)
文摘The human pregnane X receptor（hPXR） plays a critical role in the metabolism, transport and clearance of xenobiotics in the liver and intestine. The hPXR can be activated by a structurally diverse of drugs to initiate clinically relevant drug-drug interactions. In this article, in silico investigation was performed on a structurally diverse set of drugs to identify critical structural features greatly related to their agonist activity towards h PXR. Heuristic method（HM）-Best Subset Modeling（BSM） and HM-Polynomial Neural Networks（PNN） were utilized to develop the linear and non-linear quantitative structure-activity relationship models. The applicability domain（AD） of the models was assessed by Williams plot. Statistically reliable models with good predictive power and explain were achieved（for HM-BSM, r^2=0.881, q^2_（LOO）=0.797, q^2_（EXT）=0.674; for HM-PNN, r^2=0.882, q^2_（LOO）=0.856, q^2_（EXT）=0.655）. The developed models indicated that molecular aromatic and electric property, molecular weight and complexity may govern agonist activity of a structurally diverse set of drugs to h PXR.
