Quantitative structure-biodegradability relationships for biokinetic parameter of polycyclic aromatic hydrocarbons

Area of Science:

• Environmental Chemistry
• Computational Chemistry
• Molecular Modeling

Background:

• Estimating the environmental fate of chemicals is crucial for ecological and economic reasons.
• Biodegradability prediction of organic pollutants offers a feasible approach for environmental risk assessment.

Purpose of the Study:

• To establish a quantitative structure-biodegradability relationship (QSBR) for 20 polycyclic aromatic hydrocarbons (PAHs).
• To identify key molecular descriptors influencing the biodegradation activity index (qmax) of PAHs.

Main Methods:

• Stepwise multiple linear regression analysis was employed to develop the QSBR model.
• Quantum chemical calculations (B3LYP/6-311+G(2df,p)) were used to obtain molecular descriptors.
• Leave-one-out cross-validation was performed to evaluate the model's robustness and predictive ability.

Main Results:

• The major descriptors influencing biodegradation activity were identified as Freq, D, MR, EHOMO, and ToIE.
• The developed QSBR model demonstrated significant relationships, robustness, and good predictive ability.
• Computational analysis confirmed the stability of the studied PAH structures.

Conclusions:

• The established QSBR model provides a valuable tool for predicting PAH biodegradability.
• The findings enhance understanding of the molecular mechanisms governing biodegradation processes.
• This predictive approach supports environmental risk assessment and chemical management strategies.