Investigation on the relationship between bioconcentration factor and distribution coefficient based on class-based...

Area of Science:

• Environmental Chemistry
• Ecotoxicology
• Computational Chemistry

Background:

• Bioconcentration factor (BCF) is crucial for assessing aquatic ecosystem hazards of new compounds.
• Systematic investigation of factors influencing BCF estimation across diverse chemicals is lacking.

Purpose of the Study:

• To investigate the relationship between BCF and molecular descriptors for 1088 organic compounds.
• To evaluate nonlinear models for BCF prediction and compare them with existing methods.
• To identify factors causing prediction deviations for specific compound classes.

Main Methods:

• Utilized a large dataset of 1088 nonionic and ionic organic compounds.
• Performed step-by-step, class-based analysis to establish relationships between logBCF and distribution coefficient.
• Applied nonlinear Gaussian and Sigmoid equations for modeling.

Main Results:

• Nonlinear Gaussian and Sigmoid equations effectively described logBCF-distribution coefficient relationships for various compound classes.
• Nonlinear models demonstrated superior fit compared to the BCFBAF method for class-based compounds.
• Identified systemic prediction deviations for specific compound types, attributing them to factors like hydrophilicity, transformation, physical barriers, and measurement accuracy.

Conclusions:

• Nonlinear models provide a robust approach for BCF prediction in aquatic ecosystems.
• Understanding specific factors influencing BCF is essential for accurate hazard assessment.
• Future BCF prediction models should incorporate identified influencing factors for improved reliability.