Editors Choice: Removal of Targeted Pharmaceuticals and Personal Care Products from Wastewater Treatment Plants using QSAR Model


Background: Because of their intrinsic ability to induce physiological effects in humans at low doses, pharmaceuticals and personal care products (PPCPs) are a unique group of emerging environmental pollutants. A number of studies have confirmed the occurrence of different PPCPs in the environment, which raises concerns about possible adverse effects on humans and wildlife. The removal of PPCPs from wastewaters has become a major activity to reduce pollution due to their adverse effects on humans and aquatic ecosystems.

Methods: This study aimed to design a Quantitative Structure Activity Relationship (QSAR) model for the removal of 57 PPCPs from wastewater treatment plants (WWTPs) of historical data obtained from plants located in South Korea. The target compounds of PPCPs were optimised geometrically using a Forcite-Geometry code, assembled in Material Studio 2016.

Results: The removal efficiency of PPCPs is dependent on several preliminary molecular descriptors including rotatable bonds (RBs), hydrogen bond donor (HBD), total molecular mass (TMM), binding energy (BE), atom count (AC), element count (EC), total energy (TE), total dipole (TD), highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). A Genetic Function Approximation (GFA) method was adopted to perform regression analysis and create correlation between experimental data (literature) and measured data (QSAR model).

Conclusion: A QSAR model equation was established and used to predict removal efficiency of 57 PPCPs; the results obtained showed goodness of fit, R2 greater than 0.90 indicating that the internal and external validations were also performed on the model. Read more here: https://www.eurekaselect.com/179207/article

Author: Bentham Science Publishers

A major STM journal publisher of more than 100 online and print journals and related print/online book series, Bentham Science answers the information needs of scientists in the fields of pharmaceutical, biomedical, medical, engineering, technology, computer and social sciences.

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