The use of carbon thirteen nuclear magnetic resonance spectra to predict dioxin and furan binding affinities to the aryl hydrocarbon receptor.
Four spectroscopic data-activity relationship (SDAR) models for polychlorinated dibenzofurans (PCDFs) and dibenzodioxins (PCDDs) binding to the aryl hydrocarbon receptor (AhR) have been developed based on simulated 13C nuclear magnetic resonance (NMR) data. Models were developed using discriminant function analysis of the compounds' spectral data. An SDAR model with two classifications for 26 PCDF compounds had a leave-one-out (LOO) cross-validation accuracy of 89%. A two-classification SDAR model for 14 PCDD compounds had LOO cross-validation accuracy of 95%. A two-classification SDAR model combining 14 PCDD and 26 PCDF compounds had LOO cross-validation accuracy of 88%, while a four-classification SDAR model based on the same 14 PCDD and 26 PCDF compounds had LOO cross-validation accuracy of 92%. We used each appropriate SDAR model to classify 41 PCDD and/or 121 PCDF compounds with unknown binding affinities to the AhR. The SDAR models provide a rapid, simple, and valid way to model the PCDF and PCDD binding activity in relation to the AhR.
Shade
Lindsay
L
Division of Chemistry, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA.
Beger
Richard D
RD
Wilkes
Jon G
JG
D001572:Benzofurans / Q000737:chemistry* / Q000378:metabolism; D002247:Carbon Isotopes; D003198:Computer Simulation; D000072338:Dibenzofurans, Polychlorinated; D004785:Environmental Pollutants; D005544:Forecasting; D009682:Magnetic Resonance Spectroscopy; D008954:Models, Biological; D000072317:Polychlorinated Dibenzodioxins / Q000031:analogs & derivatives* / Q000737:chemistry* / Q000378:metabolism; D018336:Receptors, Aryl Hydrocarbon / Q000378:metabolism*
D001572:Benzofurans; D002247:Carbon Isotopes; D000072338:Dibenzofurans, Polychlorinated; D004785:Environmental Pollutants; D000072317:Polychlorinated Dibenzodioxins; D018336:Receptors, Aryl Hydrocarbon