Yeast is ubiquitous and may act as a solid phase in natural aquatic systems, which may affect the distribution of organic micropollutants (OMs). Therefore, it is important to understand the adsorption of OMs on yeast. Therefore, in this study, a predictive model for the adsorption values of OMs on the yeast was developed. For that, an isotherm experiment was performed to estimate the adsorption affinity of OMs on yeast (i.e., Saccharomyces cerevisiae). Afterwards, quantitative structure-activity relationship (QSAR) modeling was performed for the purpose of developing a prediction model and explaining the adsorption mechanism. For the modeling, empirical and in silico linear free energy relationship (LFER) descriptors were applied. The isotherm results showed that yeast adsorbs a wide range of OMs, but the magnitude of Kd strongly depends on the types of OMs. The measured log Kd values of the tested OMs ranged from -1.91 to 1.1. Additionally, it was confirmed that the Kd measured in distilled water is comparable to that measured in real anaerobic or aerobic wastewater (R2 = 0.79). In QSAR modeling, the Kd value could be predicted by the LFER concept with an R2 of 0.867 by empirical descriptors and an R2 of 0.796 by in silico descriptors. The adsorption mechanisms of yeast for OMs were identified in individual correlations between log Kd and each descriptor: Dispersive interaction, hydrophobicity, hydrogen-bond donor, and cationic Coulombic interaction of OMs attract the adsorption, while the hydrogen-bond acceptor and anionic Coulombic interaction of OMs act as repulsive forces. The developed model can be used as an efficient method to estimate OM adsorption to yeast at a low level of concentration.
Keywords: Ions; LFER; Micropollutants; Prediction; QSAR; Toxicant-carrier.
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