Soil Sorption Estimator (SSE): Read-Across-Based Predictions of Soil Organic Carbon Partition Coefficient (Log K_oc) and Validation Using Multiple External Sets

Among various properties, the soil organic carbon-water partition coefficient (<i>K</i>_oc) is a key parameter that governs the environmental fate of these organic chemicals. Experimental values of soil sorption potential are available for only a limited number of chemicals due to the high cost and labor required for experiments.

In the present study, we have developed both quantitative structure–property relationship (QSPR) and quantitative read-across structure–property relationship (<i>q</i>-RASPR) models for the fast and efficient prediction of Log <i>K</i>_OC values of new or untested chemicals. The statistical and predictive qualities of our models (<i>R</i>² > 0.84, <i>Q</i>_LOO² > 0.84, <i>Q</i>_F1² > 0.87, MAE_tr < 0.34, MAE_test < 0.44) depict their efficiency in predicting Log <i>K</i>_OC values for new organic chemicals.