Title :
Notice of Retraction
Theoretical Study of the Quantitative Structure-Activity Relationships for the Ah Receptor-Binding Affinities of Polybrominated Diphenyl Ethers
Author :
Yu Li ; Ting Wang ; Jing Xin ; Xianyuan Du
Author_Institution :
Res. Acad. of Energy & Environ. Studies, North China Electr. Power Univ., Beijing, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Polybrominated diphenyl ethers (PBDEs) are environmental contaminants that have been generating social concern. However, because of the large number of congeners for PBDEs, toxicology information of PBDEs based on test is incomplete. This paper aims to build a quantitative structure activity relationships (QSARs) focused on relative binding affinities (RBAs) with aryl hydro carbon receptor (AhR) and quantitative structure parameters of PBDEs. Hartree-Fock analysis was employed to calculate the quantitative parameters of PBDEs in this study. QSARs models were estimated through multiple linear regression analysis. Polarizabilities and hyperpolarizabilities explain most of variation in RBA to AhR of PBDEs based on principal component analysis. Quality of QSARs model using quantum descriptions is superior to the regression model estimated through principal components of quantum descriptions. The R2 and Aaj R2 of the final QSARs regression model were 0.957 and 0.939, respectively.
Keywords :
HF calculations; bonds (chemical); contamination; molecular biophysics; molecular configurations; organic compounds; polarisability; principal component analysis; proteins; regression analysis; toxicology; Hartree-Fock analysis; PBDE hyperpolarizability; PBDE polarizability; PBDE toxicology; QSAR; aryl hydrocarbon receptor binding affinity; environmental contaminants; multiple linear regression analysis; polybrominated diphenyl ethers; principal component analysis; quantitative structure-activity relationships; quantum descriptions; relative binding affinity; Analytical models; Biological system modeling; Compounds; Correlation; Linear regression; Predictive models; Principal component analysis;
Conference_Titel :
Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5088-6
DOI :
10.1109/icbbe.2011.5780774