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.