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. 2021 Oct 19;6(43):29166–29170. doi: 10.1021/acsomega.1c04592

Computational Analysis of the Binding Mechanism of GenX and HSA

Jeannette Delva-Wiley †,§, Israt Jahan ‡, Robert H Newman §, Lifeng Zhang ‡,*, Ming Dong †,*
PMCID: PMC8567346  PMID: 34746605

Abstract

graphic file with name ao1c04592_0005.jpg

One PFOS alternative, ammonium 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy) propanoate, known as GenX, was created to replace one of the original PFAS. This small and tough molecule has been found in surface water, groundwater, drinking water, rainwater, and air emissions in some areas in the United States. Recently, GenX has been shown to have an impact on several disease-related proteins in humans, and just like PFOS, it binds to human protein human serum albumin (HSA). In this paper, we reported four binding sites of GenX on HSA protein via docking and molecular dynamics simulation.

Introduction

Per- and polyfluoroalkyl substances (PFAS) are a group of manmade chemicals that includes perfluorooctanoic acid (PFOA), PFOS, GenX, and many other chemicals (Figure 1). PFAS chemicals have been manufactured and used in a variety of industries around the globe. For example, they have been widely used in products such as food packaging, cookware, and items commonly found in offices, households, cars, and firefighting and related training activities because they are highly effective against hydrocarbon fuel fires. Among PFAS chemicals, PFOA and PFOS have been the most extensively produced and well studied. The carbon–fluorine bond in PFAS molecules is extremely stable under environmental conditions, and thus PFASs are not appreciably degraded in our daily life, which means that they are very persistent in the environment and they can accumulate in the human body over time. Accumulated evidence showed that exposure to PFAS can lead to adverse human health effects.1−6 International concerns regarding human health from PFAS exposure started in the early 2000s, and perfluorooctanoic acid (PFOA) is found in the blood of approximately 98% of Americans.7 More specifically, it was previously found that the PFAS molecules were mostly found in the blood and liver, where it is bound with human serum albumin (HSA) and human liver fatty acid-binding proteins, respectively.4,8−11 Therefore, regulations and restrictions have been imposed on the use of PFOS and PFOA.

Figure 1.

Figure 1

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Structures of PFOA, PFSO, and GenX.

The recent regulations and restrictions on the use of long-chain PFASs have resulted in a significant shift toward short-chain alternatives.12 One known PFOS alternative, ammonium 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy) propanoate (CAS no. 62037-80-3), has been produced since 2010 with the trade name “GenX”13,14 (Figure 1). GenX, which was created to replace one of the original PFAS, has been found in surface water, groundwater, drinking water, rainwater, and air emissions in some areas in the United States. GenX is also persistent in the environment. Despite a significant shift in the industry toward short-chain alternatives, there are very limited studies on these short-chain PFAS.15 Moreover, emerging evidence from animal experiments suggests that these alternative short-chain PFASs can be equally or even more hazardous to humans due to less steric hindrance of these molecules than their longer-chain counterparts and consequently higher potential to interact with biomolecules. Meanwhile, the technical performance of short-chain PFASs is lower than that of long-chain counterparts and thus larger quantities of short-chain PFASs are utilized in commercial production to obtain similar performance to long-chain PFASs, which further exacerbates the situation.12 Recently, GenX has been shown to have an impact on several disease-related proteins in humans, e.g., breast cancer resistance protein (BCRP), multidrug resistance-associated protein 2 at the blood–brain barrier, the transport activity of the human breast cancer resistance protein (BCRP), and P-glycoprotein (P-gp).16 Like PFOS, in this paper, we report that GenX also binds to the HSA protein.

Human serum albumin (HSA) is the most abundant protein of blood plasma, where HSA is the major plasma carrier protein in blood that binds a large number of ligands, e.g., amino acids, vitamins, fatty acids, drugs, and so on. HSA is also playing a role in both the oncotic pressure and pH of blood. HSA is an α-helical protein consisting of 585 amino acids with three homologous domains (I–III) (Figure 2A).17,18 The crystal structures of HSA complexed with fatty acids and other drugs have been determined previously, identifying seven sites (FAT1–FAT7) where the fatty acids bind19−22 (Figure 2A). Among the fatty acid-binding sites, there are two main drug-binding sites that were identified previously, a smaller and more rigid site known as “Sudlow site II” or the “indole-benzodiazepine-binding site”, which is the same as FAT3/4, located in the IIIA subdomain close to Tyr411 and Arg410.23 This site preferentially binds aromatic carboxylic acids, though it exhibits a high selectivity for anions of long-chain fatty acids (C8) as well. Likewise, there is “Sudlow site I”, same as the FAT7 site in the IIA domain of HSA, which is close to Trp21423 (Figure 2A). Both the experimental and computational analyses of the HSA–PFOS complex indicated that PFOS binds with HSA at FAT6 and FAT3/4, which were named as the PFOS6 and PFOS3 sites, respectively (Figure 2B).3,20,24 Site-specific fluorescence experiments showed that PFAS exhibits binding affinities with HSA of 2.2 × 104 and 7.6 × 106 M–1 at the Trp214 site (close to the FAT7 site) and FAT3/4,24 respectively. Because of this unique structure feature of HSA and its tight binding with PFOS and its derivatives, the HSA protein has been shown as one of the numerous proteins controlling the fate of these chemicals in organisms.2 However, currently, there is no study investigating the HSA and GenX binding mechanism, which inhibits us from evaluating the environmental and health impact of this binding mechanism as previously studied on PFOS.

Figure 2.

Figure 2

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(A) Ribbon model of HSA-Fat (Myr) complex (PDB: 1e7h), derived from X-ray crystallography. HSA is composed of three homologous domains I–III with each domain divided into two subdomains A and B. The seven FAT molecules are shown as surface representation. The numbering of the sites is labeled with FAT1–7 by following a previous numbering system (Bhattacharya et al.). Among these sites, Sudlow I site is at FAT7 and Sudlow II site is at FAT3/4. (B) Ribbon model of HSA–PFOS (PDB: 4e99). There were two PFOS binding sites identified, PFOS3 and PFOS6. (C) Ribbon model of the HSA–GenX from the docking results. There were four GenX binding sites identified and shown: GenX-1, GenX-2, GenX-8, and GenX-10 (PDB: 4e99).

In this study, we performed protein–ligand docking followed by molecular dynamics (MD) simulation. The docking and simulation results showed the GenX binding sites on HSA, which facilitates classifying them on the basis of their interaction energy. Four GenX binding sites with predicted binding energy with HSA were uncovered, which were named with GenX-1, GenX-2, GenX-8, and GenX-10 sites. Two sites, GenX-1 and GenX-8, are identical to the previously identified PFOS binding sites, PFOS3 and PFOS6, respectively. Site GenX-2 and GenX-10, which were not found binding with PFOS, are found to have high binding affinities with GenX.

Results and Discussion

Previously, the binding sites of fatty acids, the additional drug, and PFOS have been identified.19−22,25 However, there were no studies on the GenX binding with HSA. In this work, we did blind docking of GenX with HSA and used the highest-ranked poses from the docking results for the molecular dynamics simulation and obtained the estimated binding affinities. Our results showed four GenX binding poses, GenX-1, GenX-2, GenX-8, and GenX-10, with HSA protein (Figure 2C). Among these binding sites, GenX-1 corresponds to the previously identified FAT3/4/PFOS3 site, which is also named Sudlow II site, where Arg410 and Tyr411 contribute to the binding (Figure 3A). GenX-8 corresponds to the previously identified PFOS6/FAT6 site, which is close to the Sudlow I site (Figure 3C). Two other sites, GenX-2 and GenX-10 sites, were also identified, where the GenX-2 site is sandwiched by the IIIB and IIIA domains, and the GenX-10 site is sandwiched by the IIIA and IIA domains (Figure 3B,D). The RMSD of backbone had relatively higher values (Figure S1). We overlaid the averaged structures with the original HSA apo protein structure, and it showed that the IIIB domain has relatively large conformational shifting, which could be causing the higher RMSD values (Figure S2).

Figure 3.

Figure 3

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(Left) Predicted GenX binding sites on HSA. (A) GenX-1 site. (B) GenX-2 site. (C) GenX-8 site. (D) GenX-10 site. The binding sites were first predicted by docking, followed by energy minimization and simulation production. The GenX molecules are shown as surface representation. (Right) Close-up of the four GenX sites. (A) Close-up structure of GenX-1 site. residues LEU394, ASN391, ARG410, LEU407, TYR411, LYS414, PHE488, and LEU453 are in close contact with GenX, where R410 forms hydrogen bonds with the carbonyl oxygen of the GenX. (B) Close-up structure of the GenX-2 site. The residues Gln522, Arg521, Lys525, Lys190, and Glu425 are in close contact with GenX, where Arg186 forms hydrogen bonds with the carbonyl oxygen of the GenX. (C) Close-up structure of GenX-8 site. The residues LEU331, LEU327, ARG209, ALA213, ALA350, and ASP324 are in close contact with GenX, where ARG209 forms hydrogen bonds with the carbonyl oxygen with GenX. (D) Close-up structure of the GenX-10 site. The residues ARG218, TYR452, VAL455, CYS448, PRO447, and ARG222 are in close contact with GenX, where ARG218 forms hydrogen bonds with the carbonyl oxygen of GenX. HIS is protonated; ASP and GLU are deprotonated.

GenX-1 site is the same as the Sudlow II site26 or the PFOS3/FAT3/4 site (Figure 3A). For GenX-1, residues Leu394, Asn391, Leu407, Tyr411, Lys414, Phe488, and Leu453 are in close contact with GenX via hydrophobic interaction, where Arg410 forms hydrogen bonds with the carbonyl oxygen of the GenX. GenX-1 has a predicted binding energy of −6.14 ± 2.73 kJ/mol. This is much lower than the previously measured PFOS binding affinity at this site (−39.45 kJ/mol).24 Our results agree with the previous observation where same residues (Leu394 and Phe488) are interacting with PFOS. More specifically, Tyr411, Lys414, and Ser489 are interacting with the sulfonic group of PFOS via ionic interactions and hydrogen bonds.3 GenX-2, one site that previously was not shown to bind with PFOS, is sandwiched by IIIA and IIIB domains, which has the highest predicted binding affinity of −31.04±1.29 kJ/mol out of the four binding poses (Figure 3B). This is interesting because the IIIB domain was shown to be the most unstable domain from the RMSD charts (Figure S2) from all simulations. Moreover, this site was reported previously to be the binding site for another drug lidocaine, which was found to be bound at this GenX-2 site in the crystal structure22 with a binding affinity of −20.01 kJ/mol from isothermal titration calorimetry experiment. GenX-8 is the same as the previously identified FAT6/PFOS6 site, which is close to the Sudlow I site26 (Figure 3C). At the binding site of GenX-8, residues Leu331, Leu327, Ala213, Ala350, and Asp324 are in close contact with GenX via hydrophobic interaction and Arg209 forms hydrogen bonds with the carbonyl oxygen with the GenX (Figure 3C). GenX-8 has a predicted binding energy of −14.64±1.59 kJ/mol. Our result is in accordance with the same residues at this site (except Ala350) that are having interactions with PFOS via hydrophobic interactions.3 Unlike GenX, the PFOS mainly interacts with HSA via hydrophobic interactions and the sulfonic groups is not in close contact with groups that could form hydrogen bonds or ionic interactions.3 We are also reporting a previously unknown site GenX-10, which is sandwiched by IIIA and IIA domains (Figure 3D), where residues Tyr452, Val455, Cys448, Pro447, and Arg222 are in close contact with GenX via hydrophobic interaction, and Arg218 forms hydrogen bonds with carbonyl oxygen of GenX that gives a predicted binding energy of −27.5±0.715 kJ/mol (Figure 3D).

Conclusions

HSA mainly binds and transports the long-chain fatty acids in the blood plasma. It also binds with hormones and drugs. Just like PFOS, GenX also competes with other drugs at the HSA binding sites. Our results reported that from the MD simulation results, GenX binds with the HSA at four locations with various binding affinities, while not disturbing the secondary structure of HSA. Two of the GenX binding sites (GenX-1 and GenX-8) are the same as the previously identified sites for fatty acids and PFOS but with predicted relatively lower binding affinities. One site (GenX-2) is the same site for the binding of drug lidocaine, but with predicted higher binding affinity for GenX than lidocaine. Likely, the higher binding affinity of GenX at this site could inhibit the lidocaine from binding to HSA. One newly uncovered site (GenX-10) was not reported before, yet the binding affinity was predicted to be relatively high with a binding energy of −27.5±0.715 kJ/mol. For all four sites, Arg is shown to be the residue that interacts with the polar group of GenX. Since the displacement of endogenous chemicals bound to HSA by GenX will compete with the biological function of HSA, the interaction of GenX with HSA in this study indicated physiological impacts of GenX and contributed to the full spectrum knowledge of the binding sites of other chemicals which might be discovered in the future. This is the first time that the binding mechanism of HSA and GenX was explored. We performed this study with the goal of providing structural insights to further understand how the GenX could impact the function of HSA by occupying the hydrophobic binding pockets for other natural ligands or designed drugs, which could be used as a guide for future binding experiment design.

Methods

Docking of the HSA–GenX Interaction

The interactions between GenX and HSA were investigated by employing the computational modeling method. We used AutoDock 4.2.6 and AutoDock Tools27 to screen GenX binding sites of HSA. AutoDock was run on a desktop computer and allowed rapid screening of complex structures. We used the ligand GenX and HSA apo protein (PDB code: 4e99.pdb) structures as input data for AutoDock. Grids that cover the entire protein were made to perform docking. Docking poses and estimated binding energies were predicted by AutoDock, which were ranked afterward. The top-ranked poses were used for the following molecular dynamics (MD) simulation.

More specifically, the pdbqt format files of both the GenX and HSA were prepared with AutoDock 4. A grid centering on the HSA molecule was made, and the size of the grid box was set to be 120, 120, 120 to cover the whole protein molecule. The ligand was placed at a random position within the grid. Then AutoGrid was performed first to create the gpf files before the AutoDock. Docking parameters were set as the generic algorithm, and the output was set as the Lamarckian genetic algorithm (LGA) with 50 runs. Random number generator and seeds were used as docking parameters. Finally, the AutoDock was performed and ligand with various poses with estimated binding energy ranking with pdbqt file was produced. The top-ranked poses were used for further MD simulation analysis.

Molecular Dynamics Simulation of HSA–GenX Binding Interaction

Molecular mechanics potential energy minimization and MD simulations were performed to use GROMACS v.4.5.5 with the top-ranked poses from AutoDock. A CHARMM36 all-atom force field was used for the simulation. The system was solvated with an explicit water box-shaped dodecahedron under periodic boundary conditions. The system was then neutralized using the genion tool by adding sodium or chlorine ions depending on the charge status of the molecule, followed by energy minimization, equilibration to room temperature, and MD production. More specifically, the equilibration was carried out before simulation to reduce unrestrained dynamics, where two steps of equilibration, NVT (isothermal–isochoric/canonical ensemble) and NPT (isothermal–isobaric ensemble), were performed. After the system was well equilibrated, the production run was then performed at a constant pressure (1 bar) and temperature (300 K) for 100 ns for the GenX–HSA complex. The particle-mesh Ewald (PME) method was used to treat long-range Coulombic interactions. The LINCS algorithm was used to constrain bond lengths. The van der Waals force and Coulombic interactions were maintained at 1.2 nm. Coordinates were clustered via the gmx_cluster with the method of RMS deviation to identify the largest clusters as representation. The root-mean-square deviation (RMSD) was calculated to determine the changes in the overall structure over time.

The trajectory files were analyzed through the gmx_energy and gmx_lie (Linear Interaction Energy)28,29 GROMACS utilities to compute the appropriate functions. The gmx_lie program calculated the ΔGbind including Lennard-Jones and electrostatic terms for ligand/protein or ligand/water interactions with scaling factors. After docking and simulation, the interface and residues involved in HSA–GenX interactions and the predicted binding energies were identified. The CHARMM General Force Field (CGenFF) program was used to prepare the simulation parameters of GenX.30

Acknowledgments

Computational facilities of the Computational Molecular Engineering Lab and the ViCAR Center at North Carolina A&T State University. This material is based upon work supported by the North Carolina Biotechnology Center (FLG-3841) and National Science Foundation (2100435).

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.1c04592.

  • Backbone RMSD timeline comparison of the HSA–GenX complex and the HSA apo protein and the overlay structures of the HSA–GenX complex and the HSA apo protein (PDF)

The authors declare no competing financial interest.

Supplementary Material

ao1c04592_si_001.pdf (1MB, pdf)

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Supplementary Materials

ao1c04592_si_001.pdf (1MB, pdf)

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