Prediction of Fate of Organic Chemicals Using In-Silico Methods

The number of chemicals used in commerce is continuously increasing. The task of identifying chemical properties and fate of many chemicals along with their impacts on the environment becomes challenging. In-silico (computational) methods offer simple, affordable, and safe quantitative chemical evaluation by prediction of physicochemical properties and degradation half-lives. On the other hand, multimedia mass balance (MMB) models help in understanding environmental distribution of chemicals via indices such as overall persistence (Pov), and long-range atmospheric transport (LRAT) ability of the chemicals. In addition to these metrics, an evaluative MMB model, namely, Equilibrium Criterion (EQC) model can also predict environmental concentrations. Deficiency in experiment-based chemical properties for inputs of MMB models can be solved by integrating in-silico estimation tools, such as linear free energy relationships (LFERs) and quantitative structure activity/property relationship (QSAR/QSPR) models. LFERs consist of multiple linear regression between a partitioning coefficient and multiplication of phase and solute descriptors. On the other hand, QSAR/QSPR models can predict various physicochemical properties by dividing the molecular structure into fragments. This study aims to investigate the comparative fate of priority chemicals and their abiotic/biotic transformation products by combining in-silico estimation tools with the EQC model. Hence, potential impact of priority pollutants can be more comprehensively taken into account.

By: Nezahat Gülücük Barlas

Date & Time: November 27th, 2019 at 15:40 in CZ-14