Effects of Nanoparticle Charge and Shape Anisotropy on

Oct 22, 2012 - The geometries along the pull simulations were saved and used as windows for using umbrella sampling technique. .... Goodman , C. M.; M...
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Effects of Nanoparticle Charge and Shape Anisotropy on Translocation through Cell Membranes Shikha Nangia† and Radhakrishna Sureshkumar*,†,‡ †

Department of Biomedical and Chemical Engineering and ‡Department of Physics, Syracuse University, Syracuse, New York 13244, United States S Supporting Information *

ABSTRACT: Nanotoxicity is becoming a major concern as the use of nanoparticles in imaging, therapeutics, diagnostics, catalysis, sensing, and energy harvesting continues to grow dramatically. The tunable functionalities of the nanoparticles offer unique chemical interactions in the translocation process through cell membranes. The overall translocation rate of the nanoparticle can vary immensely on the basis of the charge of the surface functionalization along with shape and size. Using advanced molecular dynamics simulation techniques, we compute translocation rate constants of functionalized cone-, cube-, rod-, rice-, pyramid-, and sphere-shaped nanoparticles through lipid membranes. The computed results indicate that depending on the nanoparticle shape and surface functionalization charge, the translocation rates can span 60 orders of magnitude. Unlike isotropic nanoparticles, positively charged, faceted, riceshaped nanoparticles undergo electrostatics-driven reorientation in the vicinity of the membrane to maximize their contact area and translocate instantaneously, disrupting lipid self-assembly and thereby causing significant membrane damage. In contrast, negatively charged nanoparticles are electrostatically repelled from the cell membrane and are less likely to translocate. Differences in translocation rates among various shapes may have implications on the structural evolution of pathogens from spherical to rodlike morphologies for enhanced efficacy.



INTRODUCTION Nanomedicine facilitates the direct interaction of nanoparticles (NPs) with living tissue and can often lead to cellular uptake.1−10 Indirect exposure to tailored nanoarchitectures such as carbon nanotubes, plasmonic structures, photonic crystals, and quantum dots poses tangible human health risks.11−15 NP internalization can cause increased concentrations within cellular compartments and the subsequent disruption of normal cell function. Understanding the factors controlling the cellular uptake can assist in fabricating safer nanoparticles with minimal biological and environmental impact. Although it is widely recognized that the internalization of NPs is greatly influenced by their shape, size, surface charge, functionalization, and chemical composition, how these factors influence NP internalization mechanisms is still not well understood. This has hindered the development of quantitative measures of nanotoxicity and standardized safe handling procedures for nanoparticulate systems. In this work, we have developed a coarse-grained molecular dynamics (MD) simulation framework capable of predicting the energy barriers, translocation rate constants, and half-lives of NPs through lipid membranes as a function of the physiochemical properties of the NPs. The translocation rates and half-lives are experimentally measurable8,16 and hence could serve as quantitative measures of nanotoxicity in screening or designing NPs for specific applications. © 2012 American Chemical Society

Numerous experimental and computational studies conducted to elucidate the internalization pathways indicate that internalization can occur via multiple energy-dependent or passive pathways with or without the involvement of membrane receptors.8,17−20 More recent studies on the effect of the shape and surface charge interdependence for a wide range of NP sizes indicated that the endocytosis of high-aspect-ratio rodlike nanoparticles occurs more efficiently than for more symmetric, lower-aspect-ratio spheroids.16,21−23 Furthermore, the internalization rates were reported to be highly surface-chargedependent, where the cationic particles showed enhanced translocation compared to anionic NPs counterparts.8,16 The hypothesis that emerges from these experimental observations is that the surface charge density, σ, and shape are the principal factors influencing the trans-membrane trafficking efficiency. Molecular simulations reported in this work offer a rigorous test of this hypothesis and provide a systematic computational framework to correlate the physical properties of NPs to their translocation rates and cytotoxicity quantitatively. NPs can be derived from organic, inorganic, and metallic materials. Metallic NPs show strong enhanced localized surface plasmon resonance at optical frequencies that are highly shapeReceived: August 27, 2012 Revised: October 19, 2012 Published: October 22, 2012 17666

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Figure 1. Coarse-grained gold nanoparticles and the MD simulation setup. (a) Six NP shapes, each with the longest characteristic length of 4 nm, are shown with the charged CG surface beads (orange) and uncharged core (yellow). (b) An illustration of a typical simulation cell with an unconstrained lipid bilayer (green, magenta, and gray) in the center of the box interacting with spherical NPs surrounded by CG water (light blue) and counterions (pink).

phosphatidyl glycerol (DSPG) molecules in a ratio of 3:1. Figure 1 illustrates the CG NPs along with a typical simulation cell. No constraints were imposed on the bilayer throughout the simulation, allowing it to interact self-consistently with the NPs and consequently undergo deformation during the translocation process. The simulation setup and parameters used are provided in the Methods section.

dependent. Remarkable differences in the plasmon resonances have been observed for sphere-, cube-, tetrahedron-, octahedron-, triangle-, and rectangle-shaped gold and silver NPs.24,25 Because of their tunable optical absorption, fluorescence, and electrical conductivity, gold NPs are excellent labels for numerous cancer drug delivery, biosensing, and bioimaging applications because pure gold NPs are chemically inert in biological media.4,26,27 However, it is known that functionalized gold NPs can translocate through cell membranes, resulting in membrane damage. Hence, in this work we utilize a composite NP model that consists of an inert gold core and a charged shell to mimic the effect of functionalization. The shape effects are investigated by including high-index faceted shapes, for example, rice and pyramid, and compared to their less-faceted, similarly sized rodlike and cone-shaped counterparts. Molecular modeling of the dynamics of NP translocation through lipid membranes is computationally very challenging because of the presence of multiple chemical species with disparate characteristic sizes, ranging from simple ions to selfassembled lipid layers and relatively larger metallic NPs. The time scales of the dynamic interactions and the translocation rates could vary by orders of magnitude depending on the NP charge and shape. Fully atomistic simulations are prohibitively expensive to allow for carrying out a set of meaningful case studies that would differentiate among various shapes and charge densities. To circumvent this problem, we resort to coarse-grained (CG) molecular models that we have previously employed in the context of the self-assembly of amphiphilic systems.28,29 The CG models are based on the MARTINI CG force fields30,31 capable of faithfully representing the intrinsic chemical structure and interactions for several classes of molecules including lipids, proteins, water, and ions, all of which are relevant to the present work. The CG NP model is described in the Methods section. Six shapes were studied, including sphere, cylinder, rice, cone, cube, and pyramid, each with the longest characteristic length of 4 nm. The selfassembled lipid bilayer is formed by neutral distearoyl phosphatidyl choline (DSPC) and negatively charged distearoyl



METHODS

The simulations were performed in the coarse-grained (CG) representation using the MARTINI force field30,31 description implemented in the GROMACS package, version 4.5.4.32 The negatively charged lipid membrane was modeled using a 3:1 ratio of DSPC (neutral) and DSPG (negatively charged) lipid molecules selfassembled in the center of a box of dimensions 16 × 16 × 25 nm3 surrounded by standard 56176 CG water. The electroneutrality of the system was achieved by adding positively charged CG counterions in water. The system was energy minimized followed by equilibration in the isothermal−isobaric ensemble maintained at 310 K and 1 atm of pressure. The equilibrated neutral lipid−water−counterion system was used as a template to introduce each of the various NP shapes. The composite NPs consist of an inert gold core and a charged shell. They were constructed by obtaining the desired shapes (sphere, rice, rod, pyramid, cone, and cube) from the atomistic gold lattice followed by coarse-graining using the MARTINI four-to-one mapping prescription.31 The NP surface beads were given a Q0 particle type with a fractional negative/positive charge per bead (in the range of 0.0−0.4 units/bead), and the core was kept neutral as a C1 particle. The other parameters (bonded and nonbonded) for CG gold NPs were obtained from the literature.9 The zeta potentials for the positively charged spherical NPs were computed to be in the range of 36−43 mV using standard electrical double-layer theories, suggesting that the NPs would form a stable aqueous dispersion.33 Pull simulations were performed over a distance of 20 nm in the z direction by applying a constant force of 1000 kJ mol−1 nm−2 to the center of mass of the NP to make it pass through the lipid bilayer. The geometries along the pull simulations were saved and used as windows for using umbrella sampling technique. For each umbrella sampling window, NPT equilibration was performed followed by an MD production run of 0.1 μs with a step size of 20 fs. The temperature was maintained at 300 K using a Nose-Hoover thermostat while the pressure was controlled at 1 atm by employing the Parrinello−Rahman 17667

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Figure 2. Analysis of high-charge-density (+0.3 units/bead) rice NP translocation through the lipid bilayer. (a−d) Coarse-grained MD simulation snapshots of rice NP (orange) approaching the lipid bilayer (green, magenta, and gray) and undergoing reorientation during translocation. The CG water and ions are not shown for clarity. (e) Post-translocation, 3D contour plot of changes in the cell−membrane thickness (nm). The contour ranges are provided in the legend below the plot. (f) PMF (kJ/mol) profile as a function of center-of-mass separation (nm) of the NP from the center of the lipid bilayer. The background image of the plot is provided as a visual aid to track the reorientation of the NP along the PMF curve.

Figure 3. Analysis of low-charge-density (+0.1 units/bead) rice NP translocation through the lipid bilayer. (a−d) Coarse-grained MD simulation snapshots of rice NP (orange) approaching the lipid bilayer (green, magenta, and gray) and undergoing translocation perpendicular to the membrane. The CG water and ions are not shown for clarity. (e) Post-translocation, 3D contour plot of changes in the cell-membrane thickness (nm). The contour ranges are provided in the legend below the plot. (f) The PMF (kJ/mol) profile as a function of the center-of-mass separation (nm) of the NP from the midplane of the lipid bilayer. The background image of the plot is provided as a visual aid to track the perpendicular orientation of the NP along the PMF curve.



scheme. Lennard-Jones and short-ranged Coulombic interaction were reduced to zero gradually in the range of 0.9−1.2 nm using shifted potentials.31 The weighted histogram analysis method was applied to all of the umbrella sampling windows to calculate the potential of mean force (PMF). The free-energy activation barrier for each translocation simulation was calculated by taking the difference between the maximum and the minimum energy points in the PMF curve. The rate constants were calculated by using the transition state theory rate constant equation

k=

⎡ ΔG⧧(s) ⎤ kBT ⎥ exp⎢− h kBT ⎦ ⎣

RESULTS AND DISCUSSION Simulations of NP with negatively charged functionalization showed no preference for translocation across the lipid bilayer, consistent with experimental observations.8,16 Negatively charged NPs had high energy barriers in the PMF profiles because they are electrostatically repelled by the negatively charged lipid bilayer. In contrast, for the neutral and positively charged NPs, the change in the surface charge density (σ) had a pronounced effect on translocation. Similar trends have been reported experimentally where citrate (negatively charged)coated gold NPs showed low cell membrane adhesion and low translocation compared to their neutral and positively charged counterparts.8 Simulations also indicate the importance of NP adhesion to the cell membrane, which for negatively charged NPs is energetically less favorable. For the positive charged NPs, however, adhesion is electrostatically attractive and the NPs show a strong shape and orientational dependence on the translocation. NP adhesion disrupts the equilibrium charge distribution of the cell membrane, and using its flexible, self-assembled structure, the cell membrane can permit NP internalization. Previous computational studies indicate the possibility of membrane

(1)

where kB is the Boltzmann constant, T is the temperature, h is Planck’s constant, and −ΔG⧧(s) is the free energy of activation along the translocation coordinate s.34 Considering the translocation to be a first-order reaction, we calculated the half-lives

t1/2 =

0.693 k

(2)

using the rate constant values. The half-life is related to the characteristic lifetime, τ, as

t1/2 = 0.693τ

(3)

because τ = /k. 1

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Table 1. Calculated Barrier Heights (kJ/mol), Rate Constants (s−1), and Half-Lives (s) for Six NP Shapes with Varying Surface Charge Densities

Figure 4. Comparison of PMF (kJ/mol) profiles of NPs of varying shapes and surface charge densities as a function of the center-of-mass separation distance (nm). (a) PMFs for rice NP with surface charge densities of 0.0 (blue), 0.1 (orange), 0.2 (green), and 0.3 (pink). The numbers and the dotted lines indicate he minimum energy distance of the NP from the center of the lipid bilayer. (b) PMFs for spherical NPs with surface charge densities of 0.0 (blue), 0.1 (orange), 0.2 (green), 0.3 (pink), and 0.4 (black), with dotted lines and numbers indicating the corresponding minimum energy distances. (c) PMF curves for rod- (pink), rice- (red), cone- (purple), pyramid- (green), sphere- (blue), and cone-shaped (orange) NPs.

disruption and hole formation due to NP translocation.35 Therefore, the NP shape and surface charge density become critical as demonstrated most significantly by the rice-shaped NPs. The isotropic spherical NPs show no orientational dependence, as expected, but they do highlight stronger adhesion with increased σ like the rest of the shapes investigated in the present work. As the rice NPs approach the bilayer, high positive σ causes them to orient parallel to the oppositely charged lipid membrane. The parallel orientation maximizes adhesion caused by the attractive Coulombic interactions that overcome entropic orientation diffusion effects. This reorientation process was observed for NPs with different initial orientations away from the lipid bilayer. Representative snapshots in Figure 2a−d show an initially nearly perpendicular particle undergoing a sharp reorientation to a parallel configuration at a distance of

0.2 nm from the bilayer and maintaining it throughout the translocation process. This enhances the attractive Coulombic interactions between the NP and negatively charged DSPG molecules resulting in a substantial disruption of the lipid bilayer self-assembly. Consequently, as shown in Figure 2e, the bilayer thickness decreases from its unperturbed value of 5 to 6 nm to as low as 1 nm at the highest impact points. The energetic cost associated with the translocation is directly assessed from the barrier height of the PMF curve in Figure 2f. The background image in Figure 2f shows NP reorientation near the membrane. The orientational stabilization is evident from the downhill energy curve in Figure 2f from a separation of 9 to 4 nm. In contrast, a rice NP with low positive σ does not undergo reorientation because of diminished Coulombic interactions and translocates perpendicular to the bilayer. Representative 17669

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snapshots of the simulations are provided in Figure 3a−d. There is minimal damage to the bilayer after the NP translocation as shown in Figure 3e. Furthermore, the translocation process is associated with a relatively larger energy barrier (cf. Figures 2f and 3f). As shown in Table 1, when σ for rice NPs is increased from 0 to +0.4, the translocation energy barrier decreases from 224 kJ/ mol to practically 0. The calculated rate constants and half-lives reflect the same trend. The half-life of σ = +0.4 is 0 (instantaneous translocation) compared to 1 × 1026 s for a charge-neutral NP. The translocation half-life provides a very useful quantitative estimate of the translocation efficacy and nanotoxicity. An analysis of minimum energy locations of the PMF curves, shown in Figure 4a, indicates that increases in charge decrease the equilibrium separation distances between the NPs and the bilayer. Spherical NPs also show pronounced charge dependence in their translocation through the membrane. Uncharged particles interact weakly with the cell membrane and have substantially long half-lives comparable to the experimentally observed halflives of about 6−17 h for charged gold NPs.8 The degree of adhesion to the cell membrane is indicated by the minimum energy of the PMF curve. A separation of 6.3 nm is observed between the center of masses of the NP and the membrane midplane for σ = 0 and it decreases to 3.8 nm for σ = +0.4 (Figure 4b). The closer the NP sits to the membrane midplane, the stronger the adhesion and consequently the easier the translocation. Table 1 provides the calculated barrier heights, rates constants, and estimated half-lives for all of the cases considered. Overall, the translocation rates span 60 orders of magnitude. A comparison of the different shapes for σ = +0.4 shows that the rice NP is very easily internalized followed by the sphere (4.3 ms), pyramid (0.04 s), cone (0.4 s), rod (1.4 s), and cube (8.7 s). Furthermore, PMF profiles in Figure 4c show that faceted nanoparticles have relatively low translocation energy barrier. The presence of facets on the NPs facilitates stronger adhesion by providing interacting flat index planes for NP and cell membrane interactions. A figure detailing the faceted gold NP with various index planes is provided in the Supporting Information. The presence of index planes in pyramidal nanoparticles provides a 1 order of magnitude lower half-life in comparison to that of a similarly sized conical NP. The same reasoning explains why the much more faceted rice NP translocates faster than the rodlike particle. To put into perspective the wide range of half-lives obtained for the various positively charged NPs, we compare in Figure 5 the computed half-lives to the experimental result reported for spherical gold nanoparticles coated with positively charged poly(allylamine hydrochloride) or PAA.8 Using eq 3, the experimental t1/2 value was calculated from the reported lifetime of 9.9 h observed for the association of the NPs with the cell membrane. Whereas a direct comparison between the experimental observation and simulation predictions cannot be made because of differences in particle size and surface charge densities, Figure 5 shows that the predicted half-life for a spherical particle with σ = +0.3 is very close to the experimental datum. For relatively small charge densities, the half-lives are significantly larger, suggesting that translocation is less likely.

Figure 5. Half-life of nanoparticles (logarithmic scale) as a function of the surface charge density for rice (blue, diamond), sphere (red, circle), cone (pink, triangle), pyramid (green, cross), rod (purple, unfilled circle), and cube (black, plus). The dotted black line indicates the experimental half-life obtained from ref 8.

constants and half-lives to characterize the effect of NP geometry and surface charge on their translocation through cell membranes. Overall, the simulated free-energy barrier values in conjunction with transition-state theory suggest that the translocation rates span 60 orders of magnitude depending on the NP shape and surface charge. NPs with negatively charged surface functionalization are electrostatically repelled from the cell membrane and are less likely to translocate compared to their positively charged counterparts. Shape anisotropy plays a critical role, and unlike isotropic NPs, charged faceted NPs undergo an electrostatics-driven reorientation in the vicinity of the bilayer, thereby enhancing the NP−membrane contact area, disrupting the self-assembly of the membrane lipids, and potentially causing acute nanotoxicity. These results have implications on the design and screening of NP-based systems for imaging, diagnostics, and therapeutics. The enhanced translocation rates of elongated shapes over spherical ones may have contributed to the structural evolution of pathogens such as bacteria and viruses from spherical to rodlike morphologies.16



ASSOCIATED CONTENT

S Supporting Information *

Description of the faceted rice-shaped nanoparticle. This material is available free of charge via the Internet at http:// pubs.acs.org



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS We gratefully acknowledge National Science Foundation grants PHY-1049489, CBET 1049454, and EFRI-1137186 for the support of this research.





CONCLUSIONS We have developed MD simulations capable of providing quantitative predictions of experimentally measurable rate

REFERENCES

(1) Goodman, C. M.; McCusker, C. D.; Yilmaz, T.; Rotello, V. M. Toxicity of gold nanoparticles functionalized with cationic and anionic side chains. Bioconjugate Chem. 2004, 15, 897−900.

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(2) Rosi, N. L.; Mirkin, C. A. Nanostructures in biodiagnostics. Chem. Rev. 2005, 105, 1547−1562. (3) Kirchner, C.; Liedl, T.; Kudera, S.; Pellegrino, T.; Javier, A. M.; Gaub, H. E.; Stolzle, S.; Fertig, N.; Parak, W. J. Cytotoxicity of colloidal CdSe and CdSe/ZnS nanoparticles. Nano Lett. 2005, 5, 331− 338. (4) Shukla, R.; Bansal, V.; Chaudhary, M.; Basu, A.; Bhonde, R. R.; Sastry, M. Biocompatibility of gold nanoparticles and their endocytotic fate inside the cellular compartment: a microscopic overview. Langmuir 2005, 21, 10644−10654. (5) Nel, A.; Xia, T.; Madler, L.; Li, N. Toxic potential of materials at the nanolevel. Science 2006, 311, 622−627. (6) Pan, Y.; Neuss, S.; Leifert, A.; Fischler, M.; Wen, F.; Simon, U.; Schmid, G.; Brandau, W.; Jahnen-Dechent, W. Size-dependent cytotoxicity of gold nanoparticles. Small 2007, 3, 1941−1949. (7) Zhu, L.; Wu, W.; Zhu, M.-Q.; Han, J. J.; Hurst, J. K.; Li, A. D. Q. Reversibly photoswitchable dual-color fluorescent nanoparticles as new tools for live-cell imaging. J. Am. Chem. Soc. 2007, 129, 3524− 3526. (8) Cho, E. C.; Xie, J.; Wurm, P. A.; Xia, Y. Understanding the role of surface charges in cellular adsorption versus internalization by selectively removing gold nanoparticles on the cell surface with a I2/KI etchant. Nano Lett. 2009, 9, 1080−1084. (9) Lin, J.; Zhang, H.; Chen, Z.; Zheng, Y. Penetration of lipid membranes by gold nanoparticles: insights into cellular uptake, cytotoxicity, and their relationship. ACS Nano 2010, 4, 5421−5429. (10) Petros, R. A.; DeSimone, J. M. Strategies in the design of nanoparticles for therapeutic applications. Nat. Rev. Drug Discovery 2010, 9, 615−627. (11) Sun, Y.; Xia, Y. Shape-controlled synthesis of gold and silver nanoparticles. Science 2002, 298, 2176−2179. (12) Wang, H.; Brandl, D. W.; Le, F.; Nordlander, P.; Halas, N. J. Nanorice: a hybrid plasmonic nanostructure. Nano Lett. 2006, 6, 827− 832. (13) Trice, J.; Favazza, C.; Thomas, D.; Garcia, H.; Kalyanaraman, R.; Sureshkumar, R. Novel self-organization mechanism in ultrathin liquid films: theory and experiment. Phys. Rev. Lett. 2008, 101, 017802. (14) Davis, V. A.; Parra-Vasquez, A. N. G.; Green, M. J.; Rai, P. K.; Behabtu, N.; Prieto, V.; Booker, R. D.; Schmidt, J.; Kesselman, E.; Zhou, W.; Fan, H.; Adams, W. W.; Hauge, R. H.; Fischer, J. E.; Cohen, Y.; Talmon, Y.; Smalley, R. E.; Pasquali, M. True solutions of singlewalled carbon nanotubes for assembly into macroscopic materials. Nat. Nano 2009, 4, 830−834. (15) Erickson, D.; Sinton, D.; Psaltis, D. Optofluidics for energy applications. Nat. Photon 2011, 5, 583−590. (16) Gratton, S. E. A.; Ropp, P. A.; Pohlhaus, P. D.; Luft, J. C.; Madden, V. J.; Napier, M. E.; DeSimone, J. M. The effect of particle design on cellular internalization pathways. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 11613−11618. (17) Chithrani, B. D.; Chan, W. C. W. Elucidating the mechanism of cellular uptake and removal of protein-coated gold nanoparticles of different sizes and shapes. Nano Lett. 2007, 7, 1542−1550. (18) Chithrani, B. D.; Ghazani, A. A.; Chan, W. C. W. Determining the size and shape dependence of gold nanoparticle uptake into mammalian cells. Nano Lett. 2006, 6, 662−668. (19) Vácha, R.; Martinez-Veracoechea, F. J.; Frenkel, D. Receptormediated endocytosis of nanoparticles of various shapes. Nano Lett. 2011, 11, 5391−5395. (20) Schaeublin, N. M.; Braydich-Stolle, L. K.; Maurer, E. I.; Park, K.; MacCuspie, R. I.; Afrooz, A.; Vaia, R. A.; Saleh, N. B.; Hussain, S. M. Does shape matter? Bioeffects of gold nanomaterials in a human skin cell model. Langmuir 2012, 28, 3248−3258. (21) Yang, K.; Ma, Y.-Q. Computer simulation of the translocation of nanoparticles with different shapes across a lipid bilayer. Nat. Nano 2010, 5, 579−583. (22) Doshi, N.; Mitragotri, S. Needle-shaped polymeric particles induce transient disruption of cell membranes. J. R. Soc., Interface 2010, Suppl. 4; S403−S410.

(23) Kolhar, P.; Doshi, N.; Mitragotri, S. Polymer nanoneedlemediated intracellular drug delivery. Small 2011, 7, 2094−2100. (24) Prodan, E.; Radloff, C.; Halas, N. J.; Nordlander, P. A hybridization model for the plasmon response of complex nanostructures. Science 2003, 302, 419−422. (25) Lu, X.; Rycenga, M.; Skrabalak, S. E.; Wiley, B.; Xia, Y. Chemical synthesis of novel plasmonic nanoparticles. Annu. Rev. Phys. Chem. 2009, 60, 167−192. (26) Connor, E. E.; Mwamuka, J.; Gole, A.; Murphy, C. J.; Wyatt, M. D. Gold nanoparticles are taken up by human cells but do not cause acute cytotoxicity. Small 2005, 1, 325−327. (27) Wang, Y.; Liu, Y.; Luehmann, H.; Xia, X.; Brown, P.; Jarreau, C.; Welch, M.; Xia, Y. Evaluating the pharmacokinetics and in vivo cancer targeting capability of Au nanocages by positron emission tomography imaging. ACS Nano 2012, 6, 5880−5888. (28) Sangwai, A. V.; Sureshkumar, R. Coarse-grained molecular dynamics simulations of the sphere to rod transition in surfactant micelles. Langmuir 2011, 27, 6628−6638. (29) Sangwai, A. V.; Sureshkumar, R. Binary interactions and saltinduced coalescence of spherical micelles of cationic surfactants from molecular dynamics simulations. Langmuir 2012, 28, 1127−1135. (30) Marrink, S. J.; de Vries, A. H.; Mark, A. E. Coarse grained model for semiquantitative lipid simulations. J. Phys. Chem. B 2004, 108, 750−760. (31) Marrink, S. J.; Risselada, H. J.; Yefimov, S.; Tieleman, D. P.; de Vries, A. H. The MARTINI force field: coarse grained model for biomolecular simulations. J. Phys. Chem. B 2007, 111, 7812−7824. (32) Van der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. C. GROMACS: fast, flexible, and free. J. Comput. Chem. 2005, 26, 1701−1718. (33) Magan, R. V.; Sureshkumar, R. Multiscale-linking simulation of irreversible colloidal deposition in the presence of DLVO interactions. J. Colloid Interface Sci. 2006, 297, 389−406. (34) Schenter, G. K.; Garrett, B. C.; Truhlar, D. G. Generalized transition state theory in terms of the potential of mean force. J. Chem. Phys. 2003, 119, 5828−5833. (35) Lin, J.-Q.; Zheng, Y.-G.; Zhang, H.-W.; Chen, Z. A simulation study on nanoscale holes generated by gold nanoparticles on negative lipid bilayers. Langmuir 2011, 27, 8323−8332.

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