Considering ionic state in modelling sorption of pharmaceuticals to sewage sludge
(English)Manuscript (preprint) (Other academic)
Partitioning of chemicals between particular matter and water in sewage treatment plants provide essential information on fate of chemicals and is particularly challenging for pharmaceuticals that frequently are present in ionized form. The aim of this study was to investigate how ionization state affects partitioning to sludge of active pharmaceutical ingredients (APIs). In addition, we investigated the use of chemical descriptors based on ionized structures to improve our understanding of the underlying mechanisms of sludge sorption and for use in quantitative structure-property relationship (QSPR) models. We collected KD values for 110 APIs, which were classified as neutral, positive, or negative at pH 7. The models with the highest performance exceeded 0.75 R2Y and 0.65 Q2. We found that neutral and positively charged APIs share dominant intermolecular forces with sludge, i.e., hydrophobic, Pi-Pi and dipole-dipole interactions. In contrast, hydrophobicity driven interactions for negatively charged APIs was of little importance and sorption was mainly driven by covalent bonding, and ion-ion, ion-dipole, and dipole-dipole interactions. The performance of the models increased by 5-10% by adding charge-related descriptors, implying importance of electrostatic interactions. Using descriptors calculated for ionized structures did not improve model statistics for positive and negative APIs, however, the model statistics of the neutral APIs increased. We believe that this increase resulted from a better description of neutral zwitterions present in the dataset.
QSAR, in silico, sorption, sludge, pharmaceuticals, charge
Chemical Sciences Computer Science Environmental Sciences
IdentifiersURN: urn:nbn:se:umu:diva-120257OAI: oai:DiVA.org:umu-120257DiVA: diva2:927612