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Simulations of graphene nanoflake as a nanovector to improve ZnPc phototherapy toxicity; from vacuum to cell membrane Eric Duverger, Fabien Picaud, Louise Stauffer, and Philippe Sonnet ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b09054 • Publication Date (Web): 12 Oct 2017 Downloaded from http://pubs.acs.org on October 17, 2017

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ACS Applied Materials & Interfaces

Simulations of graphene nanoflake as a nanovector to improve ZnPc phototherapy toxicity; from vacuum to cell membrane Eric Duverger1, Fabien Picaud2, Louise Stauffer3 and Philippe Sonnet*,3

[1] FEMTO-ST Institute, Université Bourgogne Franche-Comté, CNRS, 15B avenue des Montboucons, F-25030 Besancon CEDEX, France. [2] Laboratoire de Nanomédecine Imagerie et Thérapeutique (NIT), EA4662, Université de Bourgogne Franche-Comté, UFR ST & CHU Médecine, 25000, Besançon, France. [3] Institut de Science des Matériaux de Mulhouse IS2M UMR 7361 CNRS, Université de Haute Alsace, 3 bis rue Alfred Werner, 68093 Mulhouse, France.

KEYWORDS : graphene nanoflake, ZnPc, biological environment, photodynamic therapy, DFT, molecular dynamics.

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ABSTRACT We propose a new approach to improve photodynamic therapy by transporting ZnPhthalocyanine (ZnPc) in biological systems via a graphene nanoflake, to increase its targeting. Indeed, by means of time dependent density functional theory simulations, we show that the ZnPc molecule in interaction with a graphene nanoflake preserves its optical properties not only in the vacuum but also in the water. Moreover, molecular dynamic simulations demonstrate that the graphene nanoflake-ZnPc association, as a carrier, permits to stabilize the ZnPc/graphene nanoflake system on the cellular membrane, which was not possible when using ZnPc alone. We finally conclude that the graphene nanoflake is a good candidate to transport and stabilize the ZnPc molecule near the cell membrane for a longer time than the isolated ZnPc molecule. In this way, the choice of the graphene nanoflake as a nanovector paves the way to ZnPc photodynamic therapy improvement.

1. INTRODUCTION In the field of health, photodynamic therapy (PDT) is currently one of the main applications of light-living organisms interaction as an alternative or complementary method in the conventional anti-cancer treatments (surgery, radiation therapy, chemotherapy) and also in non-malignant disorders

1,2

. This promising therapy effectively allows for the selective destruction of diseased

tissue providing the potential for minimal morbidity and large therapeutic indices. PDT combines a light-activated drug, namely the photosensitizer, with light of the appropriate wavelength that is consistent with the adsorption spectrum of the given photosensitizer. Neither


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the photosensitizer, nor the light are harmful by themselves. They only produce cytotoxic species when combined, in PDT, with the presence of molecular oxygen3. Due to its photophysical and photochemical properties, the Zinc-Phthalocyanine (i.e. ZnPc) molecule is a good candidate as a photosensitizer in PDT4-6. This molecule exhibits in ultra violet-visible spectra (i.e. UV-Vis) two strong and wide adsorption peaks: one of them, noted Bband, is centered between 300 nm and 400 nm, while the other, noted Q-band, is located between 650 and 750 nm. It is the most usable for PDT applications. The lifetime associated to these excited states is more than 200 ms, permitting to generate high yield oxygen singlet7-9. Despite drastic problem due to the natural self-aggregation of the ZnPc molecules induced by their poor solubility in a bodily fluid10,11, PDT has yet undergone clinical trials, for instance against squamous cell carcinomas of the upper aerodigestive tract12, and in vitro trials against non neoplastic cell models (peritoneal macrophages from Swiss mice)13. In order to improve water solubility and thus the drug delivery of anticancer molecules, molecules of interest can be modified chemically with functional groups as described by Li et al. in the case of ZnPc molecules14-17 or associated with nanosized carriers18-24. On the other hand, many works concerning the development of carbon nanovectors able to target only the disease cells and destroy them are also realized25. These carbon nanostructures present a great interest due to their diversity of forms (nanotube (CNT), fullerene, nanoflake). Most of them present a very large surface area that can be modified using functional groups to give them specific properties. Their hydrophobic core allows to enhance the cellular internalization of poorly permeable drugs, compared to the free ones and increases the drug action near the diseased cells. Recently, nanovectors made of functionalized CNT have proved their efficiency to vectorize anticancer ligand specifically without any damage for healthy cell26. Among all the


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allotrope carbon structures, graphene materials consisting of pure carbon are known to have weak π−π stacking between the interlayer sheets and play a pivotal role in binding of biomolecules and small aromatic molecules onto their surface27,28. This remarkable property has generated many studies from a biomedical perspective. For instance, Mensing et al.29 have presented an electrochemical method to produce a stable aqueous dispersion of graphene-metal phthalocyanine hybrid material by means of electrolytic exfoliation of graphite in an electrolyte containing functionalized metal (i.e. Cu) phthalocyanine molecules. This hybrid material obtained was formed by non-covalent π−π interactions between the graphene sheets and metal phthalocyanine. Jiang et al. have proposed an one step experimental method for the fabrication of a water-soluble graphene-metal-phthalocyanine hybrid material by sonication. Their in vitro cell experiments have shown that the effect of the graphene-metal phthalocyanine PDT is higher than that of the free metal phthalocyanine30. We can therefore assume that these methods of preparation should produce the same results for Zn metal phthalocyanine molecules on graphene. Moreover, graphene nanomaterials are currently studied in gene therapy and delivery31,32, drug delivery33-36, biomolecular sensors37,38, cellular imagery39 and also tumor heat therapy40 due to its optical absorption sensitivity in the near infrared region stronger than CNTs41,42. In this domain, graphene oxide could also be of interest. However, the graphene oxide exhibits more structural defects and many possible concentrations of oxygen, alcohol, carboxylic acid or methyl groups depending on the oxidation conditions43-45. The better yield of PDT would necessarily needs a specific localization of the photosensitizer on the cancer cell. Improving the localization and stabilization of the photosensitizer is thus of crucial importance to erase only malignant cells. On the other part, ZnPc and graphene nanoflake present interesting characteristics to treat cancer and arise very relevant questions, for instance:


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how can the ZnPc photodynamic therapy be modified in presence of a graphene nanoflake? Another points concern the ZnPc/graphene system behavior in a biological environment as well as the preservation of the intrinsic electronic properties of the ZnPc molecule with respect to the light-molecule interaction. To address these questions, we intend by means of theoretical simulations, to study the ZnPc molecule on a graphene nanoflake (GN), not only in vacuum but also in presence of water. In the first part of this paper, we investigate, within density functional theory (DFT) calculations and Bader charge analysis, the ZnPc/graphene nanoflake system in vacuum and determine its energetic stability and electronic charge transfer. Further information about the photodynamic properties of this system will then be obtained by time dependent density functional theory (TDDFT) calculations in vacuum as well as in water. In a second part, molecular dynamics (MD) simulations performed in a full biological environment will provide a complete insight of the stability of the ZnPc/graphene nanoflake system in presence of the cell membrane.

2. THEORETICAL CALCULATIONS Calculations in vacuum environment were carried out based on density functional theory (DFT) by using the projector augmented wave (PAW) method46,47 as implemented in the Vienna Ab initio Simulation Package (VASP)48,49. The generalized gradient approximation (GGA) calculations were performed with Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential50. Due to the large unit cells used in our calculations (40 Å x 40 Å x 30 Å), the Brillouin zone integration was reduced to the Γ k-point. The graphene nanoflake was constructed with 198 C and 38 H with a lateral size equal to 24 Å x 24 Å. The ZnPc molecule (C32H16Zn1N8)


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was constructed around the Zn atom (Figure 1).

(a)

(b)

Figure 1. Top views of the ZnPc molecule (a) and the graphene nanoflake (b). White, turquoise, dark blue and grey balls correspond to hydrogen, carbon, nitrogen and zinc atoms respectively.

The cut-off energy for plane-wave was equal to 400 eV. Besides, in order to obtain the optimized ground state geometries, the conjugate gradient algorithm was used until the residual force was within 0.02 eV/Å. In order to consider the dispersive interactions, we added the energetic correction term proposed by Grimme in the total energy calculations (i.e. DFT-D3 approximation)51-53. In order to understand the nanoflake/molecule interactions, the adsorption energy (Eads) of the adsorbed molecules (ZnPc) is defined as: Eads =E(ZnPc + nanoflake) E(nanoflake) - E(ZnPc). A negative Eads value denotes a more favorable interaction between the drug and the nanoflake surface. The charge transfer occurring between the molecule and the surface were analyzed through a partial charges approach (i.e. valence electrons) in the Bader scheme54,55. In order to highlight the interaction between the ZnPc molecule and the graphene nanoflake, electron localization function (ELF) representation was used. This function produces informative


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patterns and describes chemical bonding in molecules and solids. It measures the probability of finding an electron near another electron with the same spin related to the Pauli exclusion principle56,57. Then for the best conformation of ZnPc on graphene nanoflake, we determined the absorption spectra in vacuum and in water by using the time dependent DFT code developed in the Octopus package58-60. To calculate the different absorption response spectra in the linear-response regime for singlet mode, we excited the system with the same infinitesimal electric-field pulse, and then propagated the time-dependent Kohn-Sham equations for the same time giving 4500 time steps (i.e. total time equal to 10.00 hbar/eV or 6.58 fs). In order to propagate these wave functions, we let converging the energy to 10-7 eV and the density to 10-6 respectively. Spectra of the graphene nanoflake, ZnPc molecule and ZnPc/graphene nanoflake system were calculated by using the Approximately Enforced Time-Reversal Symmetry (AETRS) for the TDDFT simulation in gas phase (i.e. vacuum) as well as during Polarizable Continuum Model (PCM) simulations. Indeed, the PCM method permits to define a solvent (in our case water) as a continuous dielectric medium polarized by the solute molecule. Molecular dynamics simulations were conducted by building the ZnPc molecular force field thanks to the Force Field Toolkit package of the Visual Molecular Dynamics program61. The systems were solvated in a water box large enough to prevent graphene nanoflake and ZnPc molecules from interacting with their neighbors in the adjacent cell when periodic boundary conditions were used. NaCl ions were placed at a concentration of 0.1 M in the water to reproduce a correct biological environment. The membrane cell was formed by 656 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (denoted as POPC) lipid molecules in our simulations. This membrane was built by using the


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protocol described in the CHARMM-GUI website62 and then was progressively equilibrated using MD simulations for 30 ns. MD simulations were performed using the NAMD 2.9b2 package. The CHARMM36 force field parameters were used in all simulations63. During the simulations, the temperature and pressure of the system were kept constant at 310 K (Langevin dynamics) and 1 atm (Langevin piston), respectively. The long-range electrostatic forces were evaluated by using the classical Particle Mesh Ewald (PME) method with a grid spacing of 1.2 Å and a fourth-order spline interpolation. The integration time step was equal to 1 fs. Each simulation employed periodic boundary conditions in the three directions of space. During MD simulations, all atoms were allowed to relax and water molecules could move freely in the simulation box.

3. RESULTS 3.1.The ZnPc/graphene nanoflake system: DFT and TDDFT results 3.1.1. Energetic and structural study To model the adsorption of phthalocyanine on graphene Gao et al. tested three adsorption sites64. In the ZnPc on graphene nanoflake case, we also envisioned the same sites: 1) center: at the center of one carbon ring, 2) bridge: between two carbon atoms of the same ring, 3) top: at the top of one carbon atom. The calculated adsorption energies and the molecule-graphene nanoflake distances are reported in Table 1.


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Adsorption site

Eads (eV)

Distance (Å)

Center

-2.16

3.49

Bridge

-2.11

3.51

Top

-2.10

3.53

Table 1. Calculated adsorption energies and distances in the three adsorption sites of the ZnPc molecule on the graphene nanoflake. With an adsorption energy equal to -2.16 eV, the center site is slightly favored (Figure 2), but the adsorption energies and the molecule-graphene distances of the three sites are very close (the maximum energy and distance differences are 0.06 eV and 0.04 Å respectively). Let us notice that further simulations show that two ZnPc molecules, distributed on both sides of the graphene nanoflake, provide little energy gain (inferior to 0.03 eV/molecule compared to the isolated ZnPc adsorbed on graphene nanoflake). In this way, the adsorption of two ZnPc molecules on both sides of the graphene nanoflake is not of interest from an energy perspective. We have also investigated the case of two ZnPc molecules stacking on the same side of the graphene nanoflake. The energetic study leads to less favorable adsorption energy than in the case of one ZnPc per graphene nanoflake. In the following, these two cases are therefore not considered. Moreover, the competition between the hydrophobic character of graphene and the hydrophilic behavior of ZnPc is exalted when considering one to one ratio. In this case, the question raises to know which (graphene or ZnPc) will govern the system behavior. The ZnPc molecules being hydrophilic, when ZnPc molecules are adsorbed on both sides of the graphene nanoflake, the hydrophilic character of the ZnPc/graphene nanoflake/ZnPc system increases. We therefore expect that the ZnPc/graphene nanoflake/ZnPc system moves away from the hydrophobic membrane cell.


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(a)

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(b)

Figure 2. Top (a) and side (b) views of the model for the graphene nanoflake with one ZnPc molecule adsorbed at the carbon ring center site. White, turquoise, dark blue and grey balls correspond to hydrogen, carbon, nitrogen and zinc atoms respectively.

To visualize more precisely the physical interactions in the most favorable conformation (center position), we present in Figure 3 the electron localization function (ELF) representation of the system. The upper limit of the ELF representation corresponds to chemical bonding while the values lower than 0.5 correspond to electron-gas-like pair probability (i.e. no chemical bonding). We can notice the absence of any chemical bond between the ZnPc molecule and the graphene nanoflake.


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Figure 3. Side view of the electron localization function (ELF) for one ZnPc molecule adsorbed on the graphene nanoflake. On the right, the colour code of the ELF is as follows: ELF = 1.0 (in red) indicates an electron localized region, ELF = 0.5 (in blue) corresponds to a delocalized region.

Moreover, the Bader charge difference for the ZnPc molecule between the final state (one ZnPc molecule adsorbed on the substrate, in center position) and the initial state (one ZnPc molecule in the gas phase) is equal to 0.023 e- only. This weak charge transfer towards the molecule plays in favor of physical interactions. Beside, the densities of states (DOS) of the ZnPc molecule in the gas phase and in the case of one molecule adsorption show very slight discrepancies (Figure 4). All these data confirm the preservation of the ground state electronic properties of the ZnPc molecule when adsorbed on the graphene nanoflake and the ability to use a graphene nanoflake as a nanovector for ZnPc.


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(a)

(b)

Figure 4. Densities of states of the ZnPc molecule: (a) in gas phase and (b) adsorbed on graphene.

However, in order to use the ZnPc molecule in photodynamic therapy it is also crucial to determine the impact of the graphene nanoflake on the UV-Vis spectra of the ZnPc molecule. To address this potential bottleneck, we investigate, thanks to the Octopus code, the absorption spectra of the ZnPc molecule, the graphene nanoflake and the ZnPc/graphene nanoflake system,


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not only in vacuum but also in a solvent fluid mimicking the dielectric water properties within the polarizable continuum model (PCM). 3.1.2. Absorption spectra The absorption spectra in the UV-Vis of the ZnPc molecule and of the graphene nanoflake alone in vacuum or in PCM are reported in Figures 5(a) and 5(b) respectively. In order to highlight the absorption spectra of ZnPc on graphene nanoflake, Figure 5(c) depicts the difference between the absorption spectra of the molecule/graphene nanoflake system minus the spectra of the isolated nanoflake, in vacuum and PCM. The absorption spectrum of the molecule/graphene nanoflake system is not shown, the UV-Vis spectrum of the graphene nanoflake masking the ZnPc UV-Vis response. In all these spectra, we focus more accurately on the peaks between 650-750 nm which corresponds to the ZnPc Q-band zone responsible for the creation of oxygen singlet. We can see that the ZnPc spectra in vacuum and in water present the same general aspect while the peak of the Q-band was shifted of only 53 nm in the polarizable environment (Figure 5(a)). In the case of the graphene nanoflake (Figure 5(b)), we observe from 650 nm, in vacuum as well as in water, continuous absorption spectra. These latter should induce a diminution of the light intensity during PDT treatment without peak extinction for these wavelengths. Indeed, in Figure 5(c), the ZnPc onto graphene nanoflake absorption spectra show that the peak observed between 650 and 800 nm is shifted towards increasing wavelengths with respect to the vacuum phase. The redshift value, equal to 55 nm, is comparable to the red shift observed for ZnPc in Figure 5(a).


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(a)

(b)

(c)

Figure 5. UV-Vis absorption spectra (singlet states) obtained within the Octopus code in vacuum (blue line) and in polarizable continuum model (red line): (a) isolated ZnPc molecule; (b) isolated graphene nanoflake; (c) difference between ZnPc/graphene nanoflake system (not shown) and isolated nanoflake.


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All these results allow to conclude that the choice of the ZnPc molecule interacting with the graphene nanoflake might be a good candidate as a photosensitizer in photodynamic therapy. In the following section, we continue our study by investigating the stability and the behavior of the ZnPc/graphene nanoflake system in a biological environment by means of molecular dynamics (MD) simulations. 3.2. The ZnPc/graphene nanoflake system in biological environment: MD study 3.2.1 In normal water plus salt conditions Three systems were first stabilized and studied in biologic solvent alone, i.e. ZnPc, graphene nanoflake, ZnPc/graphene nanoflake system respectively. They have been equilibrated for 2 ns before a run production was performed for at most 12.5 ns. Each production run was launched as far as temperature and pressure were stabilized with time. The root mean square deviation (RMSD) for each system did not exceed 2 Å compared to their equilibrated structure in vacuum. The most important geometry modifications are observed for the ZnPc molecule (the RMSD is 2 Å in solvent and 1.8 Å when adsorbed on graphene in solvent). This can be explained by the deformation of the ZnPc carbon skeleton in presence of water. While the parameters to simulate the molecules are obtained in implicit solvent model, this is not sufficient to prevent such small skeleton deformation when explicit solvent is taken into account dynamically. Note also that during the adsorption of the ZnPc molecule on the graphene sheet, the molecule tends to desorb partially when the water fluctuates around it. This phenomenon, which could lead to the total ZnPc departure from its vector, never occurs during the simulation course. To interpret it, the interaction energies were extracted from the running simulations and averaged on the whole running time. Figure 6 depicts the different energy contributions.


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-1 (a)

(b)

Graphene/water ZnPc/water

-2

-2

-3

E (eV)

-4

E (eV)

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-6

-4

-5

-6 Graphene/water ZnPc/water Graphene/ZnPc

-8 -7

-10

-8 0

1

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0

2

t (ns)

4

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t (ns)

Figure 6. Fluctuations of the different interaction energy contributions as a function of time: (a) isolated systems in water; (b) interacting systems in water.

Note that the interactions with ions are not shown since they presented a too small value whatever the studied system. The main contribution when systems are isolated comes from water molecules. The small graphene nanoflake feels an interaction energy equal to -3.8+/-0.3 eV while ZnPc interacted strongly with water (-5.9+/-0.9 eV) in Figure 6(a). The adsorption of ZnPc on the graphene while limiting their interaction with the solvent leads to a non negligible supplementary interaction term, i.e. the ZnPc/graphene nanoflake interaction (-2.0+/-0.1 eV) in Figure 6(b). If we define the adsorption energy as the difference, in presence of the solvent, between all the interaction energy contributions in the adsorbed case and the interaction energy of the system alone, we obtain a value nearly equal to -0.4 eV for one ZnPc adsorbed on the graphene nanoflake. The negative value of the adsorption energy, lower than the thermal energy (around 27 meV at T=310K), indicates a system which is preferentially stabilized when the


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molecule and the vector are in interaction together. This is why ZnPc tends to always return on the graphene layer when water surrounds the system. To desorb the molecule, it is necessary to give to the system, via an external physical or chemical action, an excitation which would compensate the adsorption energy. This ultimate nanovector carrying one molecule is thus very stable not only in vacuum but more importantly in biological environment.

3.2.2 Close to a membrane cell The same kinds of simulations were performed in a more complex situation since each system was immersed in biologic solvent containing an infinite periodic lipid bilayer mimicking a membrane cell. Here again, different observables (RMSD, interaction energy, relative position) were computed to compare the graphene nanoflake and the ZnPc isolated sub-systems to the ZnPc/graphene nanoflake system. The equilibration time was chosen to be equal to 5 ns while the running phase was developed for almost 200 ns. To study it, we have simulated in salt water + POPC membrane medium, one system built with one ZnPc. The progressive evolution of the drug carriers are depicted in Figure 7 showing different snapshots of the simulations as a function of time.


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Figure 7. Snapshots of the molecular dynamic simulations of (a) graphene nanoflake and (b) ZnPc/graphene nanoflake near POPC membrane in biological solution from t=0 ns to 200ns. Water has been not shown for convenience.

For the graphene nanoflake or the ZnPc molecule alone close to the membrane cell, the physical behaviors are completely different. Due to the strong hydrophobic character of graphene, the small carbon nanoflake diffuses rapidly towards the membrane cell, before landing on it. Then, it penetrates immediately the extra cellular part of the membrane to insert inside the hydrophobic lipid environment made of POPC trail (Figure 7(a)). This behavior is not new since it was already observed for other hydrophobic structures such as carbon or boron nitride nanotubes, or


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carbon cages (fullerene)65. On the contrary, the affinity of ZnPc for the membrane cell is not demonstrated here. Using our force field parameter, optimized in solvent (as for graphene), the ZnPc molecule diffuses inside water randomly, comes close to the membrane before coming back to the solvent. In all simulations, no ZnPc landing or ZnPc passive diffusion through the cell was observed. This is, of course, of fundamental importance to improve PDT yield imposed to the cell via the ZnPc molecule. The most striking feature appearing on this figure is the complete landing on the POPC membrane of the ZnPc/graphene nanoflake system. No passive diffusion inside the membrane is observed, whatever the simulated system. This indicates a strong energy competition between the drug carrier, the water molecules and the lipid membrane environment (Figure 7(b)). To understand such behavior differences, the interaction energies of each entity were computed. They are depicted in Figure 8 as a function of the simulation time. In the isolated graphene nanoflake case, the progressive increase (respectively decrease) of the dashed curves for water (respectively POPC) interactions is concomitant with the dynamic of the graphene insertion in POPC (Figure 8(a)). Besides, the variation of the total energy interaction, deduced as the difference between the total inserted and total immersed cases is clearly in favor with the inserted case (around at less -1.5 eV). On the contrary, the fluctuations of the dotted curves (Figure 8(b)) demonstrates the difficult interaction of ZnPc with the POPC membrane, with a clear energy preference towards water medium compared to membrane cell (energy variation equal to 2 eV, with only one instant where the two contributions are equivalent (t=60ns on Figure 8(b)).


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Combining ZnPc to graphene, used as drug cargo, appears here essential since the affinity of the graphene for the POPC membrane cell could help ZnPc to be closer to the membrane cell for a longer time in view of photodynamic therapy. The different interaction energy contributions between all the system components shown on Figure 8(c) support the above observations.

0 0 (a)

(c)

-1 -2

E (eV)

E (eV)

-2

-3

-4

-6 -4 Graphene/Water Graphene/POPC ZnPc/Water ZnPc/POPC Graphene/ZnPc

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ZnPc/water ZnPc/POPC -4

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100

t (ns)

Figure 8. Fluctuations of the different interaction energy contributions as a function of time: (a) for isolated graphene nanoflake; (b) isolated ZnPc and (c) ZnPc/graphene nanoflake in water/POPC. (d) Minimal distance between the Zn atom of ZnPc molecule and the graphene plane during the simulation.


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We can observe that the ZnPc/graphene nanoflake has the same comportment than the graphene nanoflake alone. It avoids rapidly the solvent medium to come into contact with the membrane cell. In this configuration, the total interactions of the graphene with the molecule become clearly favorable since graphene turns against the lipid while ZnPc belongs to the water solvent. However, we never observed any diffusion inside the lipid during the simulation course. This is due to the presence of ZnPc which interacts strongly and nearly constantly with water molecules (around -6 eV, with fluctuations appearing around 150 ns when the nanocarrier approaches the membrane), even in the presence of the membrane cell. This interaction is at the origin of the graphene blockage at the membrane interface (after 180 ns the carrier is landed on the membrane). Note also that the ZnPc/graphene nanoflake energy did not vary during the whole simulation, indicating a stable drug vector even in the presence of the membrane. The distance between the ZnPc and the graphene plane, quasi constant during the whole simulations, even in the presence of the membrane cell, confirms this stability (Figure 8(d)). Finally, our MD results confirm the choice of the ZnPc molecule interacting with the graphene nanoflake as a carrier in photodynamic therapy.

4. CONCLUSION In this study we have investigated, by means of density functional theory (DFT), time dependent density functional theory (TDDFT) and molecular dynamics (MD) simulations, the system involving a ZnPc molecule adsorbed onto a graphene nanoflake in environments of progressive complexity. Our results show that the non-covalent interactions of the ZnPc molecule on a graphene nanoflake perturb neither the electronic structure of the molecule nor the energetic


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stability of the system. Moreover, the calculated absorption spectra, obtained within a TDDFT code, show a slight redshift of around 50 nm of the Q-band from vacuum to water medium. The ZnPc photodynamic response is thus not perturbed by the graphene nanoflake. To simulate a system close to the biological conditions, MD simulations have been conducted. They emphasize that the ZnPc/graphene nanoflake system stays energetically stable from vacuum to biological environment. The graphene nanoflake, used as a nanovector, stabilizes the ZnPc photosensitizer at the proximity of the membrane cell, while the ZnPc molecule presence anchors the graphene nanoflake on the membrane. The ZnPc photodynamic properties are not switched off by the graphene nanovector, which permits to envision better photodynamic therapy yield at proximity of the cell membrane with less ZnPc molecules. The ZnPc molecule on a graphene nanoflake system represents, finally, a good candidate to transport and stabilize the ZnPc molecule near the cell membrane for a longer time than the isolated ZnPc molecule. In this way, the choice of the graphene nanoflake as a nanovector paves the way to ZnPc photodynamic therapy improvement. Moreover, the graphene nanoflake may be used as a nanovector for other promising molecules for PDT, such as SiPc or naphtalocyanine molecules.

AUTHOR INFORMATION Corresponding Author * E-mail : [email protected] (Philippe Sonnet)


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ACKNOWLEDGMENT In this present work, calculations were performed with the supercomputer regional facility Mesocenters of the Universities of Franche-Comté and Strasbourg and the National Calculations Ressources of the TGCC supercomputer.

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