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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Deciphering the acute toxicity mechanisms of PFAS in algae: A molecular descriptor and binding energy hierarchy
Yanting Li1, Lin Zhao1, Lu Wang2
1School of Environmental Science and Engineering, China-Singapore Joint Center for Sustainable Water Management, Tianjin University, Tianjin 300072, PR China.
Abstract:
Per- and polyfluoroalkyl substances (PFASs) are globally persistent pollutants, yet their molecular mechanisms of toxicity in aquatic organisms remain unclear. To elucidate the molecular mechanisms of perfluorocarboxylic acid (PFCA) toxicity in algae, we combined protein-protein interaction (PPI) network analysis, molecular docking, and molecular dynamics simulations (MDS). Three photosystem II (PSII) core proteins-D1, CP47, and CP43-were identified as primary PFCA-binding targets. Molecular docking revealed a chain-length-dependent enhancement of binding affinity (-5.2 to -9.7 kcal·mol⁻1) following the hierarchy CP43 > CP47 > D1, driven by nonpolar residue density within protein hydrophobic cavities. MDS further showed that van der Waals (VDW) and nonpolar solvation forces accounted for 86 % and 28 % of the total binding free energy, respectively, with total ΔG ranging from -60.6 to -128.5 kJ·mol⁻1. These energies exhibited a strong correlation with experimentally derived algal EC50 values (r = 0. 88, p = 0.01), linking molecular-scale interactions to organism-level toxicity. Correlation analysis of molecular descriptors (e.g., log Kow, molecular weight, dipole moment, polarizability, and electrostatic potential) further identified hydrophobicity and polarity as the principal physicochemical drivers of VDW and nonpolar energetics, thereby mechanistically explaining chain-length-dependent toxicity. Extending this framework to broader PFAS subclasses confirmed consistent correlations (r = 0.85-0.99) between binding energy and toxicity. This integrative, multiscale framework quantitatively links molecular interactions, physicochemical properties, and ecological effects, providing a foundation for PFAS risk assessment and the development of environmentally safer alternatives.

