Prediction of environmental properties for chlorophenols with posetic quantitative super-structure/property relationships (QSSPR)
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abstract
Due to their widespread use in bactericides, insecticides, herbicides, and fungicides, chlorophenols represent an important source of soil contaminants. The environmental fate of these chemicals depends on their physico-chemical properties. In the absence of experimental values for these physico-chemical properties, one can use predicted values computed with quantitative structure-property relationships (QSPR). As an alternative to correlations to molecular structure we have studied the super-structure of a reaction network, thereby developing three new QSSPR models (poset-average, cluster-expansion, and splinoid poset) that can be applied to chemical compounds which can be hierarchically ordered into a reaction network. In the present work we illustrate these poset QSSPR models for the correlation of the octanol/water partition coefficient (log K ow) and the soil sorption coefficient (log K OC) of chlorophenols. Excellent results are obtained for all QSSPR poset models to yield: log K ow, r = 0.991, s = 0.107, with the cluster-expansion QSSPR; and log K OC, r = 0.938, s = 0.259, with the spline QSSPR. Thus, the poset QSSPR models predict environmentally important properties of chlorophenols. 2006 by MDPI.
