Extending proteochemometric modeling for unraveling the sorption behavior of compound-soil interaction

Contamination of ground water by industrial chemicals presents a major environmental and health problem. Soil sorption plays an important role in the transport and movement of such pollutant chemicals. In this study, proteochemometric (PCM) modeling was used to unravel the origins of interactions of 17 phthalic acid esters (PAEs) against 3 soil types by predicting the organic carbon content normalized sorption coefficient (log K_oc) values as a function of fingerprint descriptors of 17 PAEs and physical and textural properties of 3 soils. The results showed that PCM models provided excellent predictivity (R²=0.94, Q²=0.89,Q_Ext²=0.85). In further validation of the model, our proposed PCM model was assessed by leave-one-compound-out (Q_LOCO²=0.86) and leave-one-soil-out (Q_LOSO²=0.86) cross-validations. The transparency of the PCM model allowed interpretation of the underlying importance of descriptors, which potentially contributes to a better understanding on the outcome of PAEs in the environment. A thorough analysis of descriptor importance revealed the contribution of secondary carbon atoms on the hydrophobicity and flexibility of PAEs as significant properties in influencing the soil sorption capacity.