QSAR approach to POPs screening for atmospheric persistence.

Area of Science:

• Environmental Chemistry
• Computational Chemistry
• Toxicology

Background:

• Environmental behavior of Persistent Organic Pollutants (POPs) is governed by persistence, long-range transport (LRT), and physicochemical properties.
• Atmospheric half-life is a key metric for evaluating air persistence and LRT potential of POPs.

Purpose of the Study:

• To model mean and maximum atmospheric half-life estimations for 12 UNEP POPs and 48 potential POPs.
• To develop quantitative structure-activity relationship (QSAR) models for predicting POPs' persistence and LRT potential using molecular descriptors.
• To screen and rank POPs based on their atmospheric persistence and mobility, creating specific indices.

Main Methods:

• Quantitative Structure-Activity Relationship (QSAR) regression models were developed using molecular structure descriptors (atom counts, fragment counts, topological, WHIM descriptors).
• Genetic Algorithm was employed for descriptor selection in QSAR modeling.
• Principal Component Analysis (PCA) was utilized to explore half-life data and relevant physicochemical properties for atmospheric mobility.

Main Results:

• Validated QSAR models were established to predict atmospheric half-life, providing both average and precautionary estimates for ranking and screening purposes.
• The study generated a persistence index in air and a long-range transport (LRT) index for POPs.
• These indices were successfully modeled using molecular descriptors, facilitating preliminary screening of novel compounds.

Conclusions:

• The developed models accurately predict atmospheric persistence and LRT potential of POPs, offering valuable tools for environmental risk assessment.
• The persistence and LRT indices derived from molecular descriptors enable efficient screening and ranking of existing and new POP candidates.
• This approach supports informed decision-making in managing and regulating POPs to mitigate environmental risks.