In-Vitro and In-Silico Assessment of Per- and Polyfluoroalkyl Substances (PFAS) in Aqueous Film-Forming Foam (AFFF) Binding to Human Serum Albumin

Abstract

Drinking water contaminated by fluorosurfactant-based aqueous film-forming foams (AFFF) is a source of human exposure to poly- and perfluoroalkyl substances (PFAS). However, assessment of bioaccumulation potentials of diverse PFAS in commercial products such as AFFF have been insufficient and challenging, especially due to a lack of analytical standards. Here we explore the value of suspect screening, equilibrium dialysis, and molecular-docking simulations to identify potentially bioaccumulative PFAS. We exposed human serum albumin (HSA) protein to dilutions of a legacy AFFF produced by 3M in 1999 using equilibrium dialysis and screened in-vitro protein-binding affinities using high-resolution mass spectrometry (HRMS). Through suspect screening, we identified 32 PFAS and 18 hydrocarbon surfactants in the AFFF that bound to HSA. Quantification of noncovalent association constants for 26 PFAS standards confirmed that many PFAS, including the short-chain perfluoropropane sulfonic acid (log K_a= 4.1 ± 0.2 M^-1), exhibit strong binding affinities with HSA. At least five PFAS in AFFF (including three PFAS with less than five perfluorocarbons) remained bound to the precipitated HSA pellet after extensive solvent washing-an indication of high PFAS binding potential. Three PFAS (PFBS, PFOS, and PFOA) were confirmed in the protein pellet with analytical standards and quantified after acid digestion-this sample fraction accounted for 5 to 20% of each compound mass in the sample. We calculated pseudo-bioconcentration factors (BCF_pseudo) for PFAS that suspect screening flagged as noncovalently bound or potentially covalently bound. Most PFAS exhibiting high BCF_pseudo, especially those with seven perfluorocarbons, contained a carboxylic acid or a sulfonic acid. Finally, we used molecular docking to simulate HSA binding affinities for 62 ligands (26 PFAS targets, 18 PFAS qualified in AFFF, and 18 hydrocarbon surfactants qualified in AFFF). We found that molecular docking can effectively separate HSA-binding and -nonbinding compounds in AFFF. In-vitro and in-silico approaches described in this study provide replicable, high-throughput workflows for assessing bioaccumulation potentials of diverse PFAS in commercial products.

Keywords: PFAS; bioconcentration; docking; equilibrium dialysis; suspect screening.

Figure 1

Equilibrium dialysis set-up and observed mass balance for three PFAS with initial dosages of 40–80 ng. PFAS that were free in aqueous solution PFAS, noncovalently bound PFAS, and residual PFAS in the precipitated protein pellet were measured independently. The time required to reach equilibrium (T_eq) was previously determined using 26 PFAS standards in Figure S1.2. Detailed mass balance data are available in Table S1.1.

Figure 2

Experimentally determined noncovalent association constants (K_A) of 26 PFAS targets with human serum albumin (has) in equilibrium dialysis. Three C₈ precursor compounds, Perfluoro-1-octanesulfonamide (FOSA), N-methylperfluoro-1-octanesulfonamidoacetic acid (MeFOSAA), and N-ethylperfluoro-1-octanesulfonamidoacetic acid (EtFOSAA) are presented in a separate plot. The error bars represent one standard deviation.

Figure 3

Comparison of experimental log K_A with results from molecular simulations with the HSA crystal structure 1E7G. Solid black lines represent the 1:1 line; dotted lines represent one log unit higher or lower. Error bars reflect one geometric standard deviation (GSD).

Figure 4

Residual PFAS quantified in digested HSA pellets, precipitated from equilibrium dialysis experiment.

Figure 5

Pseudo-bioconcentration factors (BCF_i,pseudo ) of PFAS in aqueous film-forming foams (AFFF) that were bound noncovalently (yellow) or potentially covalently (red) to HSA. Bubble size represents the natural logarithm of the BCF_pseudo (legend BCF_pseudo = 1). For 12 qualified PFAS with multiple functional groups, a separate bubble of the same size is displayed for each functional group (e.g., noncovalently bound Cl-PFOS contained chloride and sulfonic acid groups and is represented as two bubbles with seven perfluorocarbons).

Figure 6

Violin plots of molecular docking simulated 1E7G docking scores for (a) PFAS with greater than 10 perfluorocarbons and (b) hydrocarbon surfactants identified in AFFF that have greater than 10 carbons. The shape of each violin represents a rotated kernel density plot of 5400 HSA–PFAS binding conformations generated from simulations for six binding pockets. Blue and red colors are used to distinguish experimental results. The compounds with significantly greater peak area (after correction with ISTD peak area) in the noncovalently bound fraction of the protein chamber relative to the chemical chamber are shown in blue. The compounds identified experimentally in the protein chamber that were not significantly greater in peak area relative to the chemical chamber are shown were red. Distributions in red were significantly different than distributions in blue Kruskal–Wallis (p < 0.05) except for those distributions marked with a black X.