Article pubs.acs.org/Langmuir
Cite This: Langmuir XXXX, XXX, XXX−XXX
Domain Formation and Conformational Changes in Gold Nanoparticle Conjugates Studied Using DPD Simulations Asli Raman,† Carlos Jaime,*,† and Victor F. Puntes*,‡,§,∥ †
Department of Chemistry, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain Institut Català de Nanociència i Nanotecnologia (ICN2-BIST), Campus UAB, 08193 Bellaterra, Barcelona, Spain § Vall d’Hebron Institut de Recerca (CIBBIM - VHIR), 08035 Barcelona, Spain ∥ Institució Catalana de Recerca i Estudis Avançats (ICREA), P. Lluis Companys 23, 08010 Barcelona, Spain ‡
S Supporting Information *
ABSTRACT: A gold nanoparticle (AuNP) conjugate formed with 11-mercaptoundecanoic acid (MUA) and thiolated polyethylene glycol (SH-PEG) is simulated using dissipative particle dynamics (DPD) methods, obtaining an excellent agreement with previous experimental observations. The simulations cover the isolated components (AuNP, MUA, and SH-PEG), as well as pairs of components, and finally the all three components at the same time. In this latter case, changes in the order of addition of MUA and SH-PEG over the AuNP are also considered. The AuNP is formed by independent gold beads and keeps an almost spherical shape throughout the simulation. MUA forms micelles of four to six MUA units when dispersed in water, while SH-PEG stays individually and well solvated. When exposed to AuNP, both molecules show a tendency to form patches on the surface. SH-PEG displays two different conformations (radial and tangential) depending on its relative concentration and the presence of other molecules at the NP surface. When combined at subsaturation concentrations, MUA arrives faster to the AuNP surface than SH-PEG and forms patches while SH-PEG occupies the remaining free surface. In these conditions, the order of addition of the different components partially alters these results. When SH-PEG is added over an already formed MUA/AuNP partial layer, it adopts a radial conformation over the MUA formed patches; on the contrary, if MUA is added over an already formed SH-PEG/AuNP partial layer, much less SH-PEGs adopt a radial conformation and MUA patches are significantly smaller.
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INTRODUCTION
A well-known example of NP models are gold NPs (AuNPs) synthesized by sodium citrate reduction.5 On the one hand, gold is one of the most interesting materials of use due to its outstanding chemical stability and excellent biocompatibility, along with its unique size and shape-dependent optical properties at the nanometer scale. On the other hand, the citrate layer can be easily replaced by an array of common ligands that have higher affinity for the NP surface, such as molecules containing thiol- and amine-functional groups, allowing simple and easy functionalization. As a result, AuNPs have been selectively delivered to target regions, providing enhanced opportunities for controlled drug delivery,6 cancer treatment,7 biomedical imaging,8 and diagnosis.9 However, while the unique physicochemical properties of AuNPs have been extensively studied10 and are precisely controlled by tuning their size and morphology, the control of their interactions with their surroundings via surface modifications is still challenging. In a context where nanobiointeractions are determined by the nature of NP surface, the
Colloidal inorganic nanoparticles (NPs) interact with the environment in which they are immersed via their surfaces. As a result, the successful development of NPs-enabled technologies requires not only the production of NPs with well-defined physicochemical properties but also the study and understanding of their precise surface chemistry. This has a particular relevance in the biological context,1 where the surface properties of NPs play a determinant key role in the extent of the interaction between NPs and biological systems, making similar NPs useful medical tools2 or toxic compounds.3 The NPs high surface energies tend to be minimized via homo- (particle−particle) and hetero- (particle-molecule) interactions.4 Hence, surface modification methods via (intended or unintended) functionalization of NPs with relevant biomolecules have been used to improve the colloidal stability and compatibility of NPs in biological systems, increase NP circulation times and NP targeting, as well as reduce overall aggregation and toxicity. In these processes, the ligand molecules remaining on the surface, after the NP core synthesis, are exchanged by others able to provide new properties and functionality to the particles. © XXXX American Chemical Society
Received: September 21, 2017 Revised: November 16, 2017
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Figure 1. Coarse-grained model of the system. (a) Coarse-grained representation of MUA and SH-PEG, beads including thiol group (type S) are depicted in yellow, while the hydrophobic beads (type P) are depicted in blue and hydrophilic beads (type HMUA, HSH‑PEG) are depicted in red. (b) Snapshot of a model of AuNP (water particles were removed for clarity).
composition and its structure will define the final identity of the NP. Yet, it is still challenging to evaluate the number and conformation of the coating layer, especially in the case of mixed compound coating layers.11 Furthermore, not only the properties of the conjugate at a precise time point, such as its final size, surface charge, surface hydrophilicity, and surface chemistry, are determined by the nature of the NP surface, but also its stability, evolution in contact with other biological entities such as proteins (which has been a subject of intense research and it is known as protein corona 12 ), and biodistribution.13 In summary, the NP surface is ultimately responsible to elicit the desired effect on cellular and molecular responses.14 Beyond the chemical composition of the coating molecular layer,15 molecular conformation and formation of molecular patterns are of special relevance when addressing their interactions of NP conjugates and the immune system.16 Thus, NPs can be designed to pass unrecognized by the immune system, avoiding their rapid clearance from the bloodstream,17 or they can be designed to be specifically immunogenic.18 In these cases, the composition and distribution of the different molecules at the NP surface has been found to be of paramount importance. Subtle conformational changes of the molecules alter the final properties of the conjugate, producing variations of their biodistribution and toxicity.19 Additionally, the structure of the coating layer and the core can synergistically interact, which often leads to nonadditive nature of NP properties.20 In this sense, the accurate control of the surface chemistry composition and conformation represents a crucial aspect, not only in the efficient development of NP-based medical technologies, but also in the full exploitation of the potential differential benefits of NPs. In order to control21 and predict22 the behavior of mixed composition coated NPs, the composition and structure of the coating layer needs to be determined.23 In this context, we herein address the computational study of the distribution and conformational changes of two relevant molecules: 11-mercaptoundecanoic acid (MUA) and thiolated polyethylene glycol (SH-PEG), using dissipative particle dynamics (DPD) simulations which has been applied to study membranes, ionic surfactants, and small biological systems,24−27 and also to nanosystems containing AuNPs.28 MUA is a typical surfactant molecule employed in a number of NP systems,29 which provides colloidal stability to the NPs at physiological pH by electrostatic repulsion. Furthermore, its carboxylic acid functional group has been used to bond and transport drugs.30 PEG, and SH-PEG, is a regular coating in nanomedicines used to avoid opsonization and interaction with cell membrane receptors while providing colloidal stability to
the NP via steric repulsion.31−33 Remarkably, PEG can be absorbed on the NP surface in flat or radial conformations, and only in the latter case does it stabilize NPs against aggregation and opsonization.34 Recently published experimental results31 on the formation of mixed layers of MUA and SH-PEG on AuNPs describe a change in the conformation of SH-PEG depending on the presence of MUA at the surface or in solution, indicating how the competition between the MUA and SH-PEG for the AuNP surface is a key point in understanding these systems. In this work, the exposure of AuNPs to different MUA/SH-PEG ratios resulted in different conformational organizations of SH-PEG molecules onto the NP surface. Furthermore, in previous studies by Stellacci et al.,35 it was suggested that a mixture of molecules tends to form segregated domains when conjugated to a NP surface, which opens the opportunity to make polarized multifunctional NPs. However, despite the outstanding consequences of these results, the systematic evaluation of these aspects is greatly limited by the experimental techniques and resources available to study the distribution and conformation of two different molecules attached to an NP surface in the liquid phase. This work focuses on the study of an AuNP conjugate formed by a gold core surrounded by MUA and SH-PEG molecules. We first address the model and behavior of each individual component (Au, MUA, and SH-PEG) in the presence of water, describing how gold spontaneously forms an NP where MUA and SH-PEG dynamically occupy the formed AuNP surface. Later on, the competition between both thiolated compounds is described. Finally, the effect of the order of addition to the AuNP solution (first MUA, then SHPEG, or vice versa) is also addressed, aiming to study the competitive effects of both molecules and how their relative concentration and order of addition determine the conformation and structure of the mixed coating layer. This should allow further engineering of the NP surface.
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EXPERIMENTAL SECTION
Dissipative Particle Dynamics (DPD). DPD is a mesoscopic method developed by Hoogerbrugge and Koelman36 in 1992, and is suitable for simulating systems that contain a large number of atoms at the nanosecond time and nanometer length scale.37,38 Important contributions to the methodology were added by Español and Warren.39 The original DPD simulations consist of a collection of soft repelling, frictional, and noisy balls. In this direction, we can say that DPD is a coarse grained method of molecular dynamics (MD) where atoms are grouped together up to one mesoscopic bead, defined as groups of atoms of common chemistries, such as methyl or carbonyl groups. This strategy allows large time-scale simulations. The DPD software developed by Smit et al. was used, taking advantage of the successful study on the effect of cholesterol on lipidmediated protein−protein interactions,40 among others. DPD could B
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Soft-Repulsive Interactions. To simulate a system, the nonbonded interactions between beads should be described with softrepulsive interactions.37 Our repulsive parameters are closely based on those four types defined by Smit when he studied lipid bilayers and their interaction with proteins or with cholesterol,40,42−45 which in turn are based on the water/water repulsion parameter (25kBT) determined by Groot.37 Table 2 shows all the soft-repulsive interaction
help to understand the complexity of nanostructures, using an algorithm which mixes MD with Monte Carlo (MC) methods. In addition to the conservative force acting between particles, the total force on a particle i also contains a dissipative force and a random force. Forces acting on each bead are shown in eq 1:
fi =
∑ (FCij + FijD + FijR ) (1)
i≠j
Table 2. Soft-Repulsive Interaction Parameters Used in This Study
where FCij is the conservative force, is linear in the bead−bead separation, and contains two contributions. The first considers the nonbonded interactions, and the second gathers an elastic contribution (representing the bonding between beads) and a bond-bending contribution (representing the bending of two consecutive bonds). FDij is the dissipative force and is proportional to the relative velocity of beads i and j. FRij is the random force between bead i and its neighboring bead j (see the Supporting Information for more details). In addition to this, the sum runs over all other particles within a certain cutoff radius rc. Coarse-Grained Model. In our model, one bead consists of roughly three heavy atoms. One water bead comprises three water molecules, and one gold bead comprises three gold atoms. MUA was considered to have four beads of three different types, SH-PEG was considered to have 15 beads of two different types (Figure 1), while PEG contained 15 beads of only one type. Both have the same thiol group which lets them to bond to the gold surface with the same strength. This assumption may seem too simple, but density functional theory (DFT) studies on (RSAu)4 clusters41 showed that ligand exchange modifies the cluster electronic structure, which give rise to large changes on electronic spectra but it has very minor effects on structural and energetic data, reinforcing our approach. Simulation Technique. The behavior of AuNPs was studied using a hybrid model of Dissipative Particle Dynamics-Monte Carlo (DPDMC) simulation technique. MC moves were used with the NPT ensemble. Reduced units were used to measure energy and length: ε0 = 1kBT, d0 = 0.646 nm, respectively.40 Almost all simulations were performed in a cubic water box of size 30 × 30 × 30 d03 where the cutoff for nonbonded interactions is defined as RC ≡ 1 d0 and with Δt = 0.03. Periodic boundary conditions were applied. The dimensionless temperature used throughout the simulations was 0.42 (23.5 °C). All the systems were simulated for 18 × 104 cycles, equivalent to ∼270 ns. The systems always contain 240000 water molecules formed by 80000 beads, and 15000 gold atoms formed by 5000 beads. In addition, 120 MUAs formed by 480 beads or/and 120 SH-PEGs formed by 1800 beads were added. Individual components were simulated in water boxes of 600000 water molecules (200000 beads), and a total of 15000 gold atoms, and 120 molecules of MUAs, PEGs and SH-PEGs were also used. All the simulations started at a random point. The dissipative and random forces act together as a thermostat, which means the overall effect is a system simulated at constant temperature. Systems were considered to be equilibrated when unbonded energy was stable during more than 200 ns. Table 1 shows the mean values for the nonbonded energy, temperature, pressure, and volume, as well as their standard deviations, which represent small fluctuations of 0.1%, 1.2%, 0.1%, and 0.06%, respectively, along simulation time for the case of gold, and 100 MUAs, as an example.
W Au S P HMUA HSH‑PEG
V (nonbonded)
T
P
V
3.49 × 105 5.01 × 102
0.41 5.13 × 10−3
22.3 0.02
2.84 × 104 17.0
0.14
1.25
0.13
Au
S
P
HMUA
HSH‑PEG
25 120 15 120 15 30
120 20 1 120 20 80
15 1 35 80 35 40
120 120 80 25 80 80
15 20 35 80 35 45
30 80 40 80 45 35
parameters between the six types of beads used in this study: water (W), gold (Au), thiolated bead (S), hydrophobic bead (P), hydrophilic bead for MUA (HMUA), and hydrophilic bead for SH-PEG (HSH‑PEG). The hydrophilic beads in MUA and PEG/SH-PEG could have both been, in principle, considered equal to the hydrophilic head of lipids.45 However, close inspection to their hydrogen-bond capabilities (much bigger for a carboxylic acid or carboxylate anion than for an ether) suggests the introduction of a new type for the hydrophilic-PEG beads (HSH‑PEG), which is defined as to be slightly less hydrophilic than the hydrophilic head for lipids (see h in Table S1 in the Supporting Information). To set the interaction parameters between gold−gold, values of 5, 10, 15, and 20 were used. Two possibilities where considered for goldwater, 97.5 and 120. Initially, we followed the work of Chen et al.46 where repulsion parameters for gold/gold and for water/gold were set to 15 and 97.5, respectively. However, the repulsion for water/gold was finally decided to be 120 (equal to that used for the hydrophobic part of proteins in all the works from Smit et al.)40 because the hydrophilicity of AuNPs must be at least that of proteins, which contain many polar groups, even in the hydrophobic moiety. Although the gold/gold values of 15 and 20 produced similar results, the spherical shape and the compactness of the nanoparticle were kept better with repulsion values of 20 and 120 for gold−gold and watergold interactions, respectively (see the Supporting Information). The repulsion parameter between gold and the thiol group beads was decided after obtaining the effect that different gold−thiol repulsion parameters produced on simulations containing an AuNP formed by 2000 gold beads and 1000 ethanethiol beads (shown in Figure 2). Only with a repulsion constant of 1, all the thiol beads are on the surface of the AuNP, indicating a strong gold−thiolate bond. To confirm our previous derivation of the soft-repulsion parameters between gold beads and the rest of beads, quantum mechanics calculations on simple models were performed at the level of density functional theory with the Gaussian 09 program package.47 Geometry optimizations employed the hybrid meta exchange-correlation function M06-2X48−50 at the LANL2DZ effective core potential and associated double-ζ basis set for describing the gold metal atom.51 Each bead represents three heavy atoms in our coarse-grained model. Thus, acetate anion, dimethyl ether, and propane were selected as representative models for the different bead types used in this work (HMUA, HSHPEG, and P, respectively). In all cases, no symmetry constraints were enforced. The vibrational frequency analysis was carried out at the same level of theory to ensure that the geometry obtained corresponds to an energy minimum, and this was ensured by checking for the absence of negative eigenvalues (imaginary frequencies). Solvent effects (H2O) were evaluated by applying the polarizable continuum model (PCM) with the integral equation formalism variant (IEFPCM).52 The binding energies (kcal/mol) in aqueous solution obtained for each interaction were −7.1, −4.0, and −2.3, for the Au/HMUA, Au/HSHPEG, and Au/P, respectively. These
Table 1. Mean values, Standard Deviations, and Relative Percent for Different Variables (Expressed in the Corresponding Reduced Units) of a AuNP with 100 MUA as an Example
mean standard deviation %
W
0.06 C
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Figure 2. Number of thiol beads on the surface of the AuNP (S···center of mass (com) distance < 4.8 nm) graphed for each frame, depending on the gold−thiol repulsion constants (changed from 1 to 35); simulations were performed using 1000 thiol beads and an AuNP formed by 2000 gold beads.
Figure 3. (a) Snapshots of MUA (water particles were removed for clarity); (b) radial distribution function (in red) for S···S in MUA, and its integral (in blue); insets are micelles with 3, 5, and 7 S atoms. values correlate well with the soft-repulsion parameters used in this work (20, 80, and 120, respectively).
beads. This value is in good agreement with that obtained in a previously published work where AuNPs had been studied by DPD simulations.46 This size corresponds to the AuNPs resulting from the sodium citrate reduction method, which is probably one of the most employed to obtain gold colloids.5 MUA was studied in a similar water box without any other component, using 120 MUA molecules for the simulation. They formed micelles in water from the very early moments of the simulation (Figure 3a). This is consistent with the fact that MUA is a linear molecule with a hydrophobic central part, and both ends hydrophilic. Therefore, by clamping together, they protect their hydrophobic chains while exposing their hydrophilic ends. As a control experiment to avoid the patching of the MUAs, unrealistic repulsion values were introduced to observe if this behavior continued. In the end, patches were observed, even with these unrealistic values, indicating how hydrophobicity was driving the formation of these micelles. The radial distribution function (rdf) for the thiol group (S···S) was
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RESULTS AND DISCUSSION Single Components. Since this work was inspired in the experiments from Comenge et al.,31 the AuNP was built using 15000 gold atoms initially located randomly in a water box formed by 600000 water molecules (see Methods section and Supporting Information for further details), using values of 20 and 120 as the repulsion parameters for gold−gold and for water−gold, respectively. The results of the simulation produced a compact and spherical AuNP with a diameter of about 9 nm (on the lower limit of the experimental31 size distribution). The mean size for the AuNP radius was obtained by computing for each frame the mean distance from the AuNP center of mass to the farthest 666 gold beads. The “magic” number of 666 was deduced by considering a close-packed spherical arrangement (26% of unoccupied space)53 of gold D
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Figure 4. Snapshots of (a) PEG and (b) SH-PEG alone in water (water particles were removed for clarity).
Figure 5. (a) Example of one final distribution of the 120 MUA molecules onto the AuNP surface. (b) Variation of the number of S···S distances along the simulation of a model AuNP (formed by 15 000 gold atoms) containing 120 MUA molecules. Graphs for different S···S distances are shown. The inset corresponds to the last snapshot saved in the simulation in which water particles were removed for clarity.
calculated to observe the mean distance between two MUAs along the different simulations (red line in Figure 3b). Rdf is the conditional probability to find one object at a given distance (radius) from another object taken as the origin. In this case, the rdf provides information about the density of S atoms at a given radius from another S atom. Interestingly, rdf between SH groups indicates two zones of high probability of finding an S atom (a maximum at 0.61 nm and a shoulder at 1.5 nm), and an almost null value for distances larger than 2.3 nm, a distance that coincides with the total length of MUA. The integral below the curve (blue line in Figure 3b) indicates that 4 S atoms can be found at a distance less than 2.3 nm from any other S atom, i.e., micelles with a total number of 5 units of MUA are formed. PEG and SH-PEG were also studied in a water box formed by 600 000 water molecules without other components. The result of the simulations was quite similar for both. Due to their large hydrophilicity, PEG and SH-PEG occupy the total box without adopting any clear arrangement between them in any case (Figure 4). Rdf graphs of PEG and SH-PEG show that there is a small difference, where SH-PEGs are slightly more ordered than PEG, especially at short distances (see the Supporting Information for details), probably due to SH-SH
interactions. The integral curves are practically overlapping, indicating an identical behavior, despite the presence of the thiol group, which has a minor effect in solution until it reacts with the AuNP surface (vide infra). Systems with Two Components. Interactions between MUA and gold were studied in several simulations performed in a water box formed by 240 000 water molecules with 15 000 gold atoms and 120 MUA molecules. It is observed that MUA has the tendency to make patches onto the gold surface (Figure 5a). As with all the simulations performed in our laboratory, the initial positions of MUAs were given randomly. However, it becomes visible that MUAs start to form patches on top of the NP surface from the very beginning (early snapshots). The formation of segregated molecular domains is key to understanding heterogeneous (mixed) NP functionalization and open up the opportunity to make chemically polarized NPs.54 In this direction, it has been acknowledged that patchiness can define key properties to any NP.55,56 How MUAs are structured on the surface of the NP can be determined by analyzing the S···S distances along the simulation. Figure 5b shows how many S···S distances smaller than a cutoff (changed from 1.3 to 5.2 nm) are obtained in the E
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Figure 6. Snapshot of a model AuNP containing PEG or SH-PEG (water particles were removed for clarity): (a) PEG/AuNP; (b) SH-PEG/AuNP.
Figure 7. Snapshots of a model AuNP containing MUA and SH-PEG showing time-resolved evolution of the system (water particles were removed for clarity). Snapshots are taken between t = 1 ns and t = 270 ns.
simulation. In addition, the snapshot corresponding to the last saved structure of the simulation is shown as an inset, and it can be appreciated that, at the end of the simulation, all the MUA molecules are on the gold surface and form patches of different sizes. Interestingly, the evolution of the S···S distances shows three well-defined regions. During the first 70 snapshots and the last 120, the number of S···S distances remains almost constant, indicating somehow stable configurations, while a transition can be observed in the central part of the trajectory. At the beginning of the simulation, MUA forms small micelles, similar to those depicted in Figure 3a. Those will have S···S distances of about 1.95 nm, which corresponds to the overall length of a MUA molecule. Figure 5b indicates that, for distances 0.6, SH-PEG mainly adopts a radial (or brush) conformation, while at ratios < 0.6 the conformation of SH-PEG is mostly tangential (or mushroom), in excellent agreement with experimental results. Finally, this work has been developed for 9 nm AuNPs, but, in principle, different NP sizes and shapes could modify the results. With increasing the NP size and decreasing the curvature radii, an increase in the affinity of MUA for the NP surface is expected. In flat surfaces, the hydrophobic MUA chains can pack better. However, in the case of SH-PEG, a high curvature radius may decrease the steric repulsion between different attached SH-PEG molecules, thus resulting in an increased affinity as the NP size decreases. In this situation, what was observed here would also be observed for larger NPs, since the affinity of MUA would increase, while the affinity of SH-PEG would decrease.
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CONCLUSIONS We have presented here the study of AuNP conjugates by DPD simulations, which have been effective in explaining the experimental observations in their formation. We have obtained different behaviors depending on the components. While MUA molecules exist in groups of four to six disordered micelles in solution, PEG and SH-PEG do not adopt any defined arrangement when dispersed in water. The presence of a thiol group is crucial for adopting a radial conformation once SH-PEG has been complexed the AuNP. In the absence of the thiol group, PEG mainly wraps around the AuNP surface, while in its presence the radial conformation can be easily observed at high coverage rates. MUA and SH-PEG I
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Langmuir final NP design and behavior. Indeed, recently, computational studies have provided another point of view to help understanding these systems once the initial simulation tools have been adapted and developed for the nanoscale.62 In addition, they give valuable guidelines to the engineering of multifunctional NPs and molecular surface structure of NPs, which is difficult to measure due to the nature of these small coatings in NP dispersions.
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(6) Ghosh, P.; Han, G.; De, M.; Kim, C. K.; Rotello, V. M. Gold Nanoparticles in Delivery Applications. Adv. Drug Delivery Rev. 2008, 60, 1307−1315. (7) Medley, C. D.; Smith, J. E.; Tang, Z.; Wu, Y.; Bamrungsap, S.; Tan, W. H. Gold Nanoparticle-Based Colorimetric Assay for the Direct Detection of Cancerous Cells. Anal. Chem. 2008, 80, 1067− 1072. (8) Sharma, P.; Brown, S.; Walter, G.; Santra, S.; Moudgil, B. Nanoparticles for Bioimaging. Adv. Colloid Interface Sci. 2006, 123− 126, 471−485. (9) Baptista, P. V.; Koziol-Montewka, M.; Paluch-Oles, J.; Doria, G.; Franco, R. Gold-Nanoparticle-Probe-Based Assay for Rapid and Direct Detection of Mycobacterium Tuberculosis DNA in Clinical Samples. Clin. Chem. 2006, 52, 1433−1434. (10) Rivera Gil, P.; Oberdörster, G.; Elder, A.; Puntes, V.; Parak, W. J. Correlating Physico-Chemical with Toxicological Properties of Nanoparticles: The Present and the Future. ACS Nano 2010, 4 (10), 5527−5531. (11) Ong, Q.; Luo, Z.; Stellacci, F. Characterization of Ligand Shell for Mixed-Ligand Coated Gold Nanoparticles. Acc. Chem. Res. 2017, 50, 1911−1919. (12) Casals, E.; Puntes, V. F. Inorganic Nanoparticle Biomolecular Corona: Formation, Evolution and Biological Impact. Nanomedicine 2012, 7, 1917−1930. (13) Sperling, R. A.; Parak, W. J. Surface Modification, Functionalization and Bioconjugation of Colloidal Inorganic Nanoparticles. Philos. Trans. R. Soc., A 2010, 368, 1333−1383. (14) Moore, T. L.; Rodriguez-Lorenzo, L.; Hirsch, V.; Balog, S.; Urban, D.; Jud, C.; Rothen-Rutishauser, B.; Lattuada, M.; Petri-Fink, A. Nanoparticle Colloidal Stability in Cell Culture Media and Impact on Cellular Interactions. Chem. Soc. Rev. 2015, 44, 6287−6305. (15) Dobrovolskaia, M. A.; McNeil, S. E. Immunological Properties of Engineered Nanomaterials. Nat. Nanotechnol. 2007, 2, 469−478. (16) Puntes, V. Nanoparticle Interaction with Biomolecules: How it Shapes the Nano-Effects on Immunity. Current Biotechnology 2016, 2, 11−19. (17) Ginn, C.; Khalili, H.; Lever, R.; Brocchini, S. PEGylation and its Impact on the Design of New Protein-Based Medicines. Future Med. Chem. 2014, 6, 1829−1846. (18) Bastús, N. G.; Sánchez-Tilló, E.; Pujals, S.; Farrera, C.; López, C.; Giralt, E.; Celada, A.; Lloberas, J.; Puntes, V. Homogeneous Conjugation of Peptides onto Gold Nanoparticles Enhances Macrophage Response. ACS Nano 2009, 3 (6), 1335−1344. (19) Lipka, J.; Semmler-Behnke, M.; Sperling, R. A.; Wenk, A.; Takenaka, S.; Schleh, C.; Kissel, T.; Parak, W. J.; Kreyling, W. G. Biodistribution of PEG-Modified Gold Nanoparticles Following Intratracheal Instillation and Intravenous Injection. Biomaterials 2010, 31, 6574−6581. (20) Silvera Batista, C. A.; Larson, R. G.; Kotov, N. A. Nonadditivity of nanoparticle interactions. Science 2015, 350, 1242477. (21) Carenco, S.; Le Goff, X. F.; Shi, J.; Roiban, L.; Ersen, O.; Boissière, C.; Sanchez, C.; Mézailles, N. Chem. Mater. 2011, 23, 2270. (22) Singh, C.; Ghorai, P.; Horsch, M.; Jackson, A.; Larson, R.; Stellacci, F.; Glotzer, S. Phys. Rev. Lett. 2007, 99, 226106. (23) Goldmann, C.; Ribot, F.; Peiretti, L. F.; Quaino, P.; Tielens, F.; Sanchez, C.; Chanéac, C.; Portehault, D. Quantified Binding Scale of Competing Ligands at the Surface of Gold Nanoparticles: The Role of Entropy and Intermolecular Forces. Small 2017, 13, 1604028. (24) Groot, R. D.; Rabone, K. L. Mesoscopic Simulation of Cell Membrane Damage, Morphology Change and Rupture by Nonionic Surfactants. Biophys. J. 2001, 81, 725−736. (25) Jury, S.; Bladon, P.; Cates, M.; Krishna, S.; Hagen, M.; Ruddock, N.; Warren, P. Simulation of Amphiphilic Mesophases using Dissipative Particle Dynamics. Phys. Chem. Chem. Phys. 1999, 1, 2051−2056. (26) Prinsen, P.; Warren, P. B.; Michels, M. A. J. Phys. Rev. Lett. 2002, 89, 148302.
ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.langmuir.7b03318. Details on DPD methodology and on the models used for gold nanoparticle, MUA, PEG, and SH-PEG, as well as a test of reproducibility of the results; Cartesian coordinates for the representative models for the derivation of the soft-repulsive interactions (PDF)
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AUTHOR INFORMATION
Corresponding Authors
*E-mail:
[email protected]. *E-mail:
[email protected]. ORCID
Carlos Jaime: 0000-0002-9690-9053 Author Contributions
The manuscript was written with contributions by all authors. All authors have given approval to the final version of the manuscript. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS Universitat Autònoma de Barcelona is gratefully acknowledged for a fellowship to A.R.. This work was undertaken under the financial aid from Ministerio de Economiá y Competitividad (Grant No. MAT2015-70725R). This work was performed, in part, using the computer facilities from Consorci de Serveis Universitaris de Catalunya (CSUC). The authors thank Neus G. Bastús from Institut Català de Nanociència i Nanotecnologia (ICN2-BIST) for her comments and suggestions that greatly improved the manuscript.
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REFERENCES
(1) Daniel, M.-C.; Astruc, D. Gold Nanoparticles: Assembly, Supramolecular Chemistry, Quantum-Size-Related Properties, and Applications toward Biology, Catalysis, and Nanotechnology. Chem. Rev. 2004, 104, 293−346. (2) Wong, I. Y.; Bhatia, S. N.; Toner, M. Nanotechnology: emerging tools for biology and medicine. Genes Dev. 2013, 27, 2397−2408. (3) Bahadar, H.; Maqbool, F.; Niaz, K.; Abdollahi, M. Toxicity of Nanoparticles and an Overview of Current Experimental Models. Iran Biomed. J. 2016, 20, 1−11. (4) Casals, E.; Gonzalez, E.; Puntes, V. Reactivity of inorganic nanoparticles in biological environments: insights into nanotoxicity mechanisms. J. Phys. D: Appl. Phys. 2012, 45 (44), 443001. (5) Bastús, N. G.; Comenge, J.; Puntes, V. Kinetically Controlled Seeded Growth Synthesis of Citrate-Stabilized Gold Nanoparticles of up to 200 nm: Size Focusing versus Ostwald Ripening. Langmuir 2011, 27, 11098−11105. J
DOI: 10.1021/acs.langmuir.7b03318 Langmuir XXXX, XXX, XXX−XXX
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Langmuir (27) Rekvig, L.; Kranenburg, M.; Hafskjold, B.; Smit, B. Effect of Surfactant Structure on Interfacial Properties. Europhys. Lett. 2003, 63, 902−907. (28) Juan, S.; Hua, C.; Chen, C.; Sun, X.; Xi, H. Dissipative Particle Dynamics Simulation of a Gold Nanoparticle System. Mol. Simul. 2005, 31, 277−282. (29) Kaufman, E. D.; Belyea, J.; Johnson, M. C.; Nicholson, Z. M.; Ricks, J. L.; Shah, P. K.; Bayless, M.; Pettersson, T.; Feldotö, Z.; Blomberg, E.; Claesson, P.; Franzen, S. Probing Protein Adsorption onto Mercaptoundecanoic Acid Stabilized Gold Nanoparticles and Surfaces by Quartz Crystal Microbalance and ζ-Potential Measurements. Langmuir 2007, 23, 6053−6062. (30) Comenge, J.; Sotelo, C.; Romero, F.; Gallego, O.; Barnadas, A.; Parada, T. G.-C.; Domínguez, F.; Puntes, V. F. Detoxifying Antitumoral Drugs via Nanoconjugation: The Case of Gold Nanoparticles and Cisplatin. PLoS One 2012, 7 (10), e47562. (31) Comenge, J.; Puntes, V. F. The Role of PEG Conformation in Mixed Layers: from Protein Corona Substrate to Steric Stabilization Avoiding Protein Adsorption. ScienceOpen Research 2015, 1−10. (32) Avgoustakis, K.; Beletsi, A.; Panagi, Z.; Klepetsanis, P.; Karydas, A. G.; Ithakissios, D. S. PLGA−mPEG Nanoparticles of Cisplatin: in Vitro Nanoparticle Degradation, in Vitro Drug Release and in Vivo Drug Residence in Blood Properties. J. Controlled Release 2002, 79, 123−135. (33) Xia, X.; Yang, M.; Wang, Y.; Zheng, Y.; Li, Q.; Chen, J.; Xia, Y. Quantifying the Coverage Density of Poly(ethylene glycol) Chains on the Surface of Gold Nanostructures. ACS Nano 2012, 6, 512−522. (34) Puntes, V. Design and Pharmacokinetical Aspects for the Use of Inorganic Nanoparticles in Radiomedicine. Br. J. Radiol. 2016, 89, 20150210. (35) Jackson, A. M.; Myerson, J. W.; Stellacci, F. Spontaneous Assembly of Subnanometre-Ordered Domains in the Ligand Shell of Monolayer-Protected Nanoparticles. Nat. Mater. 2004, 3, 330−336. (36) Hoogerbrugge, P. J.; Koelman, J. M. V. A. Simulating Microscopic Hydrodynamic Phenomena with Dissipative Particle Dynamics. Europhys. Lett. 1992, 19, 155−160. (37) Groot, R. D.; Warren, P. B. Dissipative Particle Dynamics: Bridging the Gap Between Atomistic and Mesoscopic Simulation. J. Chem. Phys. 1997, 107, 4423−4435. (38) Groot, R. D.; Madden, T. J. Dynamic Simulation of Diblock Copolymer Microphase Separation. J. Chem. Phys. 1998, 108, 8713− 8724. (39) Español, P. Dissipative Particle Dynamics. In Handbook of Materials Modeling; Yip, S., Ed.; Springer: Dordrecht, 2005; pp 2503− 2512. (40) De Meyer, F. J. M.; Rodgers, J. M.; Willems, T. F.; Smit, B. Molecular Simulation of the Effect of Cholesterol on Lipid-Mediated Protein-Protein Interactions. Biophys. J. 2010, 99, 3629−3638. (41) Grönbeck, H.; Walter, M.; Häkkinen, H. Theoretical Characterization of Cyclic Thiolated Gold Clusters. J. Am. Chem. Soc. 2006, 128, 10268−10275. (42) De Meyer, F. J.; Venturoli, M.; Smit, B. Molecular Simulations of Lipid-Mediated Protein-Protein Interactions. Biophys. J. 2008, 95, 1851−1865. (43) Venturoli, M.; Smit, B.; Sperotto, M. M. Simulation Studies of Protein-Induced Bilayer Deformations, and Lipid-Induced Protein Tilting, on a Mesoscopic Model for Lipid Bilayers with Embedded Proteins. Biophys. J. 2005, 88, 1778−1798. (44) Benjamini, A.; Smit, B. Lipid Mediated Packing of Transmembrane Helices − a Dissipative Particle Dynamics Study. Soft Matter 2013, 9, 2673−2683. (45) Kranenburg, M.; Smit, B. Phase Behavior of Model Lipid Bilayers. J. Phys. Chem. B 2005, 109, 6553−6563. (46) Chen, S.; Guo, C.; Hu, G.-H.; Liu, H.-Z.; Liang, X.-F.; Wang, J.; Ma, J.-H.; Zheng, L. Dissipative Particle Dynamics Simulation of Gold Nanoparticles Stabilization by PEO−PPO−PEO Block Copolymer Micelles. Colloid Polym. Sci. 2007, 285, 1543−1552. (47) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci,
B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, M. J.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, c.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian 09, Revision C.01; Gaussian, Inc.: Wallingford CT, 2009. (48) Zhao, Y.; Truhlar, D. G. Density Functionals with Broad Applicability in Chemistry. Acc. Chem. Res. 2008, 41, 157−167. (49) Zhao, Y.; Schultz, N. E.; Truhlar, D. G. Design of Density Functionals by Combining the Method of Constraint Satisfaction with Parametrization for Thermochemistry, Thermochemical Kinetics, and Noncovalent Interactions. J. Chem. Theory Comput. 2006, 2, 364−382. (50) Boys, S. F.; Bernardi, F. The Calculation of Small Molecular Interactions by the Differences of Separate Total Energies. Some Procedures with Reduced Errors. Mol. Phys. 1970, 19, 553−566. (51) Hay, P. J.; Wadt, W. R. Ab Initio Effective Core Potentials for Molecular Calculations. Potentials for K to Au Including the Outermost Core Orbitals. J. Chem. Phys. 1985, 82, 299−310. (52) Miertuš, S.; Scrocco, E.; Tomasi, J. Electrostatic Interaction of a Solute with a Continuum. A Direct Utilization of ab initio Molecular Potentials for the Prevision of Solvent Effects. Chem. Phys. 1981, 55, 117−129. (53) Atkins, P.; Overton, T.; Rourke, J.; Weller, M.; Armstrong, F.; Hagerman, M. Inorganic Chemistry, 5th ed.; W.H. Freeman and Company: New York, 2010; p 69. (54) You, C. C.; Chompoosor, A.; Rotello, V. M. The Biomacromolecule-Nanoparticle Interface. Nano Today 2007, 2, 34− 43. (55) Glotzer, S. C. Solomon, Anisotropy of Building Blocks and their Assembly into Complex Structures. Nat. Mater. 2007, 6, 557−562. (56) Zhang, Z.; Glotzer, S. C. Self-Assembly of Patchy Particles. Nano Lett. 2004, 4, 1407−1413. (57) Häkkinen, H. The Gold−Sulfur Interface at the Nanoscale. Nat. Chem. 2012, 4, 443−455. (58) Yarkony, D. R. Modern Electronic Structure Theory; World Scientific: Singapore, 1997; Vol. 3, pp 92−115. (59) Berne, B. J.; Pecora, R. Dynamic Light Scattering: With Applications to Chemistry, Biology, and Physics; Courier Dover Publications: New York, 2000. (60) Wang, Y.; Zeiri, O.; Neyman, A.; Stellacci, F.; Weinstock, A. I. ACS Nano 2012, 6, 629−640. (61) Simpson, C. A.; Agrawal, A. C.; Balinski, A.; Harkness, K. M.; Cliffel, D. E. ACS Nano 2011, 5, 3577−3584. (62) Charchar, P.; Christofferson, A. J.; Todorova, N.; Yarovsky, I. Understanding and Designing the Gold-Bio Interface: Insights from Simulations. Small 2016, 12, 2395−2418.
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DOI: 10.1021/acs.langmuir.7b03318 Langmuir XXXX, XXX, XXX−XXX