Producing 13C NMR, infrared absorption, and electron ionization mass spectrometric data models of the monodechlorination of chlorobenzenes, chlorophenols, and chloroanilines

We have developed four spectroscopic data-activity relationship (SDAR) models of monodechlorination of 32 chlorinated benzene compounds-in anaerobic estuarine sediment. The SDAR models were based on combinations-of C-13 nuclear magnetic resonance (NMR),infrared-absorption (IR), and electron ionization mass spectrometric (EI:MS) data. The SDAR models segregated the 32 compounds into 17 readily monodechlorinated compounds and 15 not readily monodechlorinated compounds. The SDAR model-based on C-13 NMR, IR; and EI MS data gave a leave-one-out cross-validation of 93.8%. The SDAR model based on a composite of C-13 NMR and IR data gave a leave-one-out cross-validation of 90.6%. The SDAR model based on a composite of IR and Fl MS data gave a leave-one-out cross-validation of 84.4%. The SDAR model based on a composite of C-13 NMR and BI MS data gave a leave-one-out cross-validation of 84.4%. These reliable SDAR models provide a rapid and simple way to predict whether a chlorinated benzene compound will readily go through monodechlorination. The FDA has filed a patent application on methods of using any combination of spectral data (NMR, MS, W-vis, IR, and fluorescence; phosphorescence) to model a chemical, physical, or biological endpoint.