Prediction of subcooled vapor pressures (log PL) of 399 polychlorinated trans-azoxybenzenes by using the QSPR and ANN approach.
Environmentally relevant partitioning properties such as the sub-cooled vapor pressures (log PL) have been predicted for 399 congeners of chloro-trans-azoxybenzene (C-t-AOBs) by two computational methods. The quantitative structure-property relationship (QSPR), an approach which is based on geometry optimalization and quantum-chemical structural descriptors in RM1 and DFT methods and artificial neural networks (ANNs), an approach that predicts abilities that give similar results of estimated log P(L) and the accuracy of the methods was also similar. The RM1 method was less time consuming and less costly compared to calculations by the DFT method. Estimated from the RM1 and DFT methods of log P(L) values of 399 Ct-AOBs varied between -1.98 to -0.93 and -1.83 to -0.79 for Mono-, 3.12 to -1.46 and -3.00 to -1.46 for Di-, -4.03 to -1.39 and -3.53 to -1.67 for Tri-, -4.75 to -2.33 and -4.59 to -1.91 for Tetra-, -5.37 to -2.59 and -5.42 to -2.09 for Penta-, -5.82 to -2.88 and -5.66 to -2.58 for Hexa-, -5.88 to -3.24 and -5.60 to -2.93 for Hepta-, -6.28 to -4.33 and -5.60 to -4.29 for Octa-, -6.54 to -5.28 and -5.66 to -4.93 for NonaCt-AOBs, and -6.59 and -5.61 for DecaCt-AOB. According to a common classification of environmental contaminants and by sub-cooled vapor pressure values, MonoCt-AOBs and a few of the Di- and TriCt-AOBs (log P(L)from -2 to 0) fall into the group of compounds that are relatively well mobile in the ambient environment, while most of the Di- to HeptaCt-AOBs (log P(L) < -4 to -2) mobility is relatively weak. Octa- and NonaCt-AOBs and DecaCt-AOB (log P(L) < -4) are also weak mobile contaminants.
Research Group of Environmental Chemistry, Ecotoxicology & Food Toxicology, Institute of Environmental Sciences & Public Health, University of Gdańsk, Gdańsk, Poland.
Sławomir
S
Piliszek
Agata J
AJ
Wilczyńska-Piliszek
Jerzy
J
Falandysz
D001391:Azo Compounds / Q000737:chemistry*; D004785:Environmental Pollutants / Q000737:chemistry*; D006843:Hydrocarbons, Chlorinated / Q000737:chemistry*; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D055548:Vapor Pressure
D001391:Azo Compounds; D004785:Environmental Pollutants; D006843:Hydrocarbons, Chlorinated