title: Prediction of binding affinities of PCDDs, PCDFs and PCBs using docking-based Comparative Molecular Similarity Indices Analysis.
abstract: Polychlorinated Dibenzodioxins (PCDDs), Dibenzofurans (PCDFs) and Biphenyls (PCBs) are industrial compounds or byproducts that can cause toxic effects after binding to aryl hydrocarbon receptor (AhR). But the mechanism about PCDDs, PCDFs and PCBs binding to AhR is unclear. To study the interaction and significant amino acid residues in binding of PCDDs, PCDFs and PCBs to AhR, a docking-based Comparative Molecular Similarity Indices Analysis (CoMSIA) was performed on a set of structurally diverse PCDDs, PCDFs and PCBs with known binding affinities. The docking-based CoMSIA model (non-cross-validated regression coefficient of 0.942 and cross-validated regression coefficient of 0.768) was developed and compared with previous report, the presented docking-based CoMSIA model showed good robustness and predictive performance. The obtained docking conformations and predictive CoMSIA model could provide clues to understand key residues and interactions between receptor and compounds of interest.
authors.affiliation: Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China; School of Public Health, Zhengzhou University, Zhengzhou 450001, China.
authors.forename: Jintao
authors.initials: J
authors.lastname: Yuan
authors.affiliation: Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China. Electronic address: yppu@seu.edu.cn.
authors.forename: Yuepu
authors.initials: Y
authors.lastname: Pu
authors.affiliation: Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China.
authors.forename: Lihong
authors.initials: L
authors.lastname: Yin
mesh_terms: D020003:1-Octanol / Q000737:chemistry; D001572:Benzofurans / Q000737:chemistry / Q000378:metabolism*; D000072338:Dibenzofurans, Polychlorinated; D004785:Environmental Pollutants / Q000737:chemistry / Q000378:metabolism*; D008958:Models, Molecular; D011078:Polychlorinated Biphenyls / Q000737:chemistry / Q000378:metabolism*; D000072317:Polychlorinated Dibenzodioxins / Q000031:analogs & derivatives* / Q000737:chemistry / Q000378:metabolism; D018336:Receptors, Aryl Hydrocarbon / Q000378:metabolism*; D014867:Water / Q000737:chemistry
chemical_list: D001572:Benzofurans; D000072338:Dibenzofurans, Polychlorinated; D004785:Environmental Pollutants; D000072317:Polychlorinated Dibenzodioxins; D018336:Receptors, Aryl Hydrocarbon; D014867:Water; D011078:Polychlorinated Biphenyls; D020003:1-Octanol
keywords: Aryl hydrocarbon receptor; Binding affinity; CoMSIA; PCBs; PCDDs; PCDFs