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Free Energy Calculations of the Adsorption of Amino Acid Analogues at the Aqueous Titania Interface S. Monti† and T. R. Walsh*,‡ Instituto di Chimica dei Composti OrganoMetallici (ICCOM), UOS di PISA, Area della Ricerca, Via G. Moruzzi, 1 - 56124 Pisa, Italy, and Department of Chemistry and Centre for Scientific Computing, UniVersity of Warwick, CoVentry, CV4 7AL, United Kingdom ReceiVed: August 19, 2010; ReVised Manuscript ReceiVed: October 13, 2010
The potential of mean constraint force approach, in partnership with atomistic molecular dynamics simulations, is used to calculate the change in free energy upon adsorption of amino acid side chain analogues at the aqueous rutile titania (110) interface. Our results indicate that both positively charged and negatively charged moieties have favorable free energy of binding to the titania surface. Stable contact, mediated via the first two solvent layers at the interface, is also indicated for the charged adsorbates. Hydrophobic adsorbates showed no appreciable binding to the titania surface. In contrast, the binding for our serine analogue (methanol) features a slight possibility to bind via hydrogen bonding to the titania surface. Our calculated results indicate very good agreement with available experimental data. In partnership with other information regarding peptide conformation and intrapeptide interactions, our findings should be helpful in building design principles for peptide sequences with predictable and controllable binding to titania. Introduction Investigations of the structure and properties of the interface between biological matter and titania surfaces has attracted a great deal of attention in recent years. Aqueous titania-biomolecule interfaces are of fundamental importance not only in the search to develop biocompatible materials for surgical implants, but also feature in a wide range of areas, from the bioinspired fabrication of nanostructured materials1-4 through to unravelling the origins of life on earth.5 Many recent studies in this wideranging area have made use of the recognition properties between peptides and inorganic materials. Such recognition between peptides and titania has been explored by using combinatorial screening approaches including phage-display6-10 and cell-surface display.11 Experimental characterization of the peptide-titania interface10,12-18 has revealed that electrostatic interactions play a role15 and that peptide flexibility may also be important.14,17 Many groups have published simulation studies of peptides (of various lengths) adsorbed at the aqueous titania interface.19-29 The study of Skelton et al.29 in particular highlighted the importance of the structured water layers at the aqueous titania interface, and how the peptide-surface interaction can be mediated by these layers. Despite these experimental and theoretical advances, the problem of understanding and therefore optimizing and/or predicting peptide-surface binding behaviors remains complex, since the current consensus in the community is that peptide sequence can affect peptide conformation, which in turn can influence binding. Therefore, two peptides with the same amino acid content, but where this content is presented in a different order, can yield very different surface-binding properties; this has been observed experimentally30,16 and inferred by using bioinformatics approaches.31 Previous studies have sought to * To whom correspondence should be addressed. E-mail: t.walsh@ warwick.ac.uk. † Instituto di Chimica dei Composti OrganoMetallici (ICCOM), UOS di PISA. ‡ University of Warwick.
disentangle these complexities by using model systems. For example, in a systematic study, Willet et al.32 characterized the surface binding for a range of homopeptides, of length 8-10 amino acids onto a variety of different inorganic surfaces. While very valuable, such data do not necessarily give information about the binding characteristics of a particular individual residue, precisely because of this interplay between sequence, conformation, and binding (e.g., the conformation of RRRRRRRR may be very different from the conformation of PPPPPPPP, and therefore the observed binding behaviors may also be very different). Therefore, the fact that it is currently not practical in experiments to construct peptides where the conformation can be rigorously controlled, while changing the sequence and/or amino acid content, presents significant obstacles to our understanding of how this interplay works. Only with such understanding will we be able realize the goal of designing peptide sequences with predictable, controllable adhesion properties on titania, amenable to exploitation in a wide range of nanofabrication applications.33-36 Therefore, there exists a genuine need for identification and characterization of binding propensities of the side groups of a range of individual amino acids, when adsorbed onto inorganic substrates. This knowledge of such individual binding propensities, and the molecular-level understanding of the underlying reasons for these propensities, will be a valuable and complementary contribution to aiding the unplaiting of these threads of sequence, conformation, and binding.37,38 Data describing surface binding of individual side chains will provide a baseline from which we can then infer positional and spatial proximity effects (of neighboring residues) on the binding of “key” residues in a peptide (e.g., as might be suggested by alanine scan experiments6). We recognize here that side chain binding data alone will not be sufficient to complete the complex task of separating peptide adsorption from peptide conformation. However, these data, in partnership with other information (e.g., regarding the conformational propensities of given sequence motifs38), will enable researchers to ascribe reasons for (and
10.1021/jp107859q 2010 American Chemical Society Published on Web 12/02/2010
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ultimately, predict and design) modulation of surface binding behaviors of particular residues when embedded in a peptide. Characterization of the structure and properties of the interface between liquid water and the inorganic substrate in question (in this case, titania) gives a foundation upon which to base and interpret adsorption studies of molecules at the aqueous titania interface. The titania-water interface has most recently been investigated with both experimental X-ray studies,39 as well as molecular simulation approaches.40-42 Experimentalists have also used a range of approaches to explore the adsorption behavior of amino acids at the aqueous titania interface. The work of McQuillan and co-workers43,44 used attenuated total reflectance infrared spectroscopy (ATR-IR) to probe adsorption of lysine and aspartic acid on titania under aqueous conditions, while Pa´szti and Guczi45 recently reported use of sum-frequency generation (SFG) vibrational spectroscopy to study adsorption of glutamine, phenylalanine, aspartic acid, and glutamic acid onto titania films. Using potentiometric measurements and adsorption experiments, Jonsson et al. have characterized the adsorption of glutamic acid46 and aspartic acid47 on the rutile titania surface. However, the use of amino acids in these studies implies the ammonium and carboxylate termini of the amino acids were also available for participation in surface binding. This adds further complexity regarding the transferability of these findings to the situation of a particular residue embedded in a surface-adsorbed peptide, since in the latter case the residue will not have terminating groups. Wei and Latour48 have recently reported surface-binding characterization using host-guest peptides of the form TGTG-X-GTGT, where X was the residue under investigation, in probing the adsorption of residues on gold-supported self-assembled monolayers (SAMs), via surface plasmon resonance (SPR) spectroscopy measurements, as a means of overcoming this limitation. In terms of calculating quantities associated with residue adsorption, a range of studies have been reported previously. Molecular simulation, in the form of Car-Parrinello molecular dynamics (CPMD), has been used previously by Langel and Menken to study the adsorption of glycine, methionine, serine, and cysteine on partially hydroxylated rutile (100) and (110) surfaces49 in the presence of water. These authors found that weak adsorbate-substrate interactions involving both carboxylate and ammonium moieties were possible. Langel and Koppen used a similar approach to study the adsorption of amino acids adsorbed on the anatase titania (101) and (001) surfaces, and the rutile (110) surface,50 under aqueous conditions. These authors reported estimates of the interaction energy (defined by the difference in potential energy of the bound and unbound systems) of adsorption of zwitterions of cysteine, lysine, glutamic acid, and histidine. In another study, these authors calculated interaction energies for a range of small molecules (acetylene, ethylene, catechol, methanol, methanal, ethanol, and ethanal) adsorbed on the rutile (100) and anatase (001) surfaces.51 Simulation studies reporting calculations of the change in free energy upon adsorption of small molecules at the aqueous interface of any inorganic surface are more rare. Raut et al.52 reported use of the probability ratio (PR) method to estimate the free energy of adsorption of the GGGG-K-GGGG peptide sequence onto functionalized SAM surfaces. However, the PR approach appeared problematic when applied to strongly adsorbing systems. O’Brien et al.53 have since modified these calculations, reporting use instead of biased replica-exchange molecular dynamics simulations to estimate free energies of adsorption for this peptide at the polylactide interface. The peptides studied by Latour and co-workers52,53 are relatively
Monti and Walsh large; in terms of similar calculations on smaller adsorbates, Monti and co-workers26 have previously used temperatureaccelerated dynamics, in partnership with the PR method, to estimate the free energy of binding of a tripeptide on a range of inorganic substrates, including the titania rutile (110) surface. Delle Site and co-workers used carefully constructed force fields to calculate the change in free energy upon adsorption of small fragments (such as the side chains of histidine and phenylalanine) not on oxide surfaces, but on the Ni (111)54 and Pt (111)55 surfaces. Recently, Notman and Walsh reported potential of mean force (PMF) calculations giving estimates of the free energy of adsorption of amino acid analogues, not on titania but at the aqueous quartz (100) interface.56 In a similar spirit, Hoefling et al.57 very recently published PMF calculations of terminal-capped amino acids adsorbing at the aqueous Au (111) surface. In this work, we have followed a PMF approach similar to that reported by Notman and Walsh, using molecular dynamics (MD) simulations to estimate the change in free energy upon adsorption of a number of amino acid side chain analogues at the aqueous rutile titania (110) interface. The analogues we have chosen to study cover the spectrum of physicochemical properties of these molecules, including neutral, nonpolar species (alanine, phenylalanine), neutral polar species (serine), and charged polar species (lysine, aspartic acid, and arginine). These molecules were also chosen to probe the similarities and differences in size, shape, and physicochemical properties. For example, the side chains of alanine and phenylalanine are both hydrophobic, yet are very different in size and shape. On the other hand, the side chains of phenylalanine and arginine have different physicochemical properties (one is charged, one is not), yet have similarities in terms of structure, as both contain rigid, planar groups. It has not been our objective to calculate quantitatively accurate data on the absolute binding free energies of these adsorbates. Rather, our aim was to obtain binding trends as a function of distance from the surface for these side chain analogues, to provide a starting point for the rational design of surface-binding peptides with desired properties. We rationalize this approach with the view that peptide/protein adsorption on a substrate, is in part controlled, at least during the approach path, by a combination of the interactions of the individual side chains of the peptide/protein that face the surface; as a consequence it is of fundamental importance to understand and predict the adsorption contributions of the individual residues, and, in particular, their side chains.58 Even though the relative adsorption free energies presented herein do not represent the real interaction energy of the peptide/protein, they could give a preliminary estimate of the forces and type of interactions that could take place at the interface. Methods System Details and Simulation Setup. We have carried out MD simulations of the interface between the (110) surface of rutile titania and liquid water using Gromacs 3.3.3.59 The initial structure of the titania-water cell was taken from an earlier study by one of us.29 We modeled a 5-layer titania slab, presenting the (110) surface in the xy-plane with dimensions of roughly 37 × 35 Å2. Three-dimensional periodic boundary conditions were imposed such that the average interslab (vertical) spacing was around 36 Å, amounting to a total of 1503 water molecules located between neighboring slabs. The c lattice parameter was varied such that the bulk TIP3P water density was recovered in the central water region between the titania slabs. This setup yielded a central layer of bulk water
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with approximate thickness of 15 Å. The system was modeled using an adapted version of the CHARMM27 force field60 for the amino acid analogues, the modified TIP3P force field61,62 for water, and the force field reported by Predota et al.41 for the titania surface. This combination of force fields has been used previously to describe the titania-water interface42 (where it yielded excellent agreement with previous simulations41 and experimental structural data39), and the aqueous peptide-titania interface.29 For charged adsorbates, a counterion (either Na+ or Cl-) was added to ensure overall charge neutrality of the simulation cell. The atoms in the titania slab were held rigid throughout. MD simulations were carried out in the NVT ensemble; the temperature of the system was maintained at 300 K with the Nose-Hoover thermostat.63,64 Long-ranged electrostatic interactions were handled with particle-mesh Ewald,65 with a real space cutoff of 12 Å. The equations of motion were integrated by using a time step of 1 fs, with coordinates saved every 1000 steps (1 ps). Free Energy Calculations. The adsorption of water and the various amino acid analogues on the titania (110) surface was investigated by calculating the free energy profiles of the molecules as a function of the separation between the slab surface and the molecule. We used the potential of mean constraint force method, which enables calculation of the free energy change as a system evolves along some reaction coordinate. In this case, our reaction coordinate was merely z, the vertical distance between the top plane of the titania slab and the center of our amino acid analogue. We performed around 40 runs per adsorbate, where the vertical separation, z, was constrained to a different value in each run. Each run was 1.5 ns in length, with 0.5 ns used for equilibration, amounting to roughly 60 ns total simulation time for a typical adsorbate. The Gromacs pull code59 was used to keep z constant. By integrating the resulting average constraint force, λ, over all values of z, the position-dependent PMF of free energy change, F(z), is obtained:
F(z) )
∫ 〈λ〉z dz
(1)
The standard error in our free energy profiles was first obtained by performing a block average66 of the constraint force. These errors were then propagated in our integration of these forces as a function of z. Results Water (Single Water Molecule). The resulting change in free energy is shown in Figure 1. There are four distinct minima in this PMF profile, when the water molecule is located at distances of 2.3, 3.6, 4.8, and 6.0 Å from the basal Ti atoms in the top layer of the titania surface (as indicated as minima 1-4 in Figure 1). The deepest minimum occurs closest to the surface, with a value of around -38 kJ mol-1. These data indicate at least four layers of structured solvent at the interface. The location of these minima is in good agreement with the positions of peaks in the interfacial density profiles reported from previous simulations.41,42 As the water molecule moves toward the surface from the bulk, three successive barriers were encountered between these minima, of heights around 2, 8, and 5 kJ mol-1, respectively, suggesting that thermal activation is required for the water molecule to pass from layer 3 to layer 2, and from layer 2 to layer 1 (where layer 1 is closest to the surface). However, the reverse barriers (for water moving from the surface to the bulk) between layers 1 and 2, and layers 2 and 3, are
Figure 1. PMF free energy curve of water adsorption at the aqueous TiO2 (110) interface, where z is the distance between the water center of mass and the basal Ti atoms. Numbers in bold indicate minima, as referred to in the text.
Figure 2. PMF free energy curves of adsorption of ammonium and methane, at the aqueous TiO2 (110) interface, where z is the distance between the molecule center of mass and the basal Ti atoms. Numbers in bold indicate minima, as referred to in the text. R1, R2, and R3 indicate regions 1, 2, and 3, respectively, as explained in the text.
sufficiently great to ensure that the waters present in layers 1 and 2 will be dynamically trapped with respect to significant motion perpendicular to the surface plane. The first layer in particular is bound very strongly, forming a highly structured arrangement, commensurate with the lattice of under-coordinated Ti atoms on the top of the titania surface; this is also in agreement with findings from previous simulations of this system.41,42 The second layer of water is located above the surface bridging oxygens, oriented such that the water hydrogens point toward these bridging oxygen atoms. Layer 3 waters are positioned laterally between the layer 1 and 2 waters, with the layer 3 oxygen atom generally directed toward the layer 1 hydrogens, with the layer 3 hydrogens oriented in the direction of the layer 2 oxygen atoms. Clearly, the structuring of these water layers (especially layers 1 and 2) is expected to impact on the adsorption of other adsorbates. Skelton et al. found that stable peptide adsorption at this interface could take place with the residues adsorbing onto the first two water layers, rather than onto the titania surface itself.29 Ammonium Ion (Analogue for Lysine Side Chain). As shown in Figure 2, the interaction between the ammonium and the surface acts over a longer range than was seen for water, with a minimum located as distant as 10.6 Å from the surface. However, just as was seen for water, there are four distinct minima in the PMF profile, situated at distances of 3.7, 5.9, 8.6, and 10.6 Å, respectively, from the titania surface. The position of the closest minimum (minimum 1) is coincident with the corresponding distance of layer 2 of water, suggesting that
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Figure 3. PMF free energy curve for adsorption of methanol at the aqueous TiO2 (110) interface, where z is the distance between the methanol center of mass and the basal Ti atoms. Numbers in bold indicate minima, as referred to in the text.
the ammonium group can displace water in this layer without a free energy penalty. However, the free energy barrier between minimum 1 and minimum 2 (moving from the bulk toward the surface) is around 21 kJ mol-1. Minimum 2 is located at the same distance from the surface as layer 4 of the interfacial water, again suggesting that displacement of water from this layer by the ammonium is a favorable process. The barrier encountered by ammonium in traversing from minimum 2 to minimum 3 is less than 2 kT at room temperature. Similarly, the reverse of this free energy barrier is around kT, indicating that transitions between these two minima should be observable in molecular dynamics simulations of reasonable duration. The positively charged ammonium molecule is limited in how close it can approach the surface, presumably due to the fact that the surface sites that give the closest binding are the under-coordinated Ti atoms (by definition), which carry a positive partial charge in the force field. Consequently, the optimal free energy of binding is not as strong as that seen for water. However, the ammonium well-depth of minimum 1 is over 50% greater than the water well-depth at a comparable distance for water (at ∼3.7 Å, corresponding to minimum 2 of water); we propose that the charge of the molecule is the cause of the relatively stronger binding seen at this particular molecule-surface separation. Strong orientational ordering accompanies the free energy changes as the molecule enters minimum 1 and adsorbs at the titania interface. Our measure of molecule orientation, calculated with respect to distance from the surface (shown in Figure S1 of the Supporting Information; accompanying text in the SI explains how this orientation was calculated) shows that the abrupt onset of preferential orientation, with the ammonium N-H bond aligned with the titania surface normal, coincides at a molecule-surface separation roughly in line with minimum 1 of the ammonium profile shown in Figure 2. This orientation does not change further as the molecule gets closer to the surface from this point. The optimal binding geometry, corresponding to minimum 1 of ammonium, is illustrated in Figure 4a. Methane (Analogue for Alanine Side Chain). Figure 2 also shows the free energy profile for adsorption of methane. This profile shows a largely repulsive interaction between the methane and the aqueous titania interface at all molecule-surface separations. In contrast to ammonium, there is no preferred orientation for the methane as it approaches the surface (data not shown); the adsorbate is able to tumble freely, even at molecule-surface distances corresponding with very repulsive interactions. There appear to be three distinct trends in the free energy plot for surface separations less than 7 Å: the repulsive
Monti and Walsh wall for small separations (region 1), a shoulder region from around 5.4 Å onward (region 3), and a central region where the ammonium and methane profiles overlap (region 2). These regions are marked on the plot shown in Figure 2. Inspection of the trajectories revealed a broad alignment of lateral mobility of these two adsorbates with these three regions. In region 1, the methane has little in-plane mobility and is positioned between two 5-coordinated surface Ti atoms (along the [001] vector). In region 2, the methane is found sitting above one of the “rails” as defined by the surface bridging oxygens arranged along the [001] direction, with some mobility up and down the rail. In region 3, the change in slope marks a transition to the molecule traversing between rails, ultimately enabling a full exploration of the entire xy plane. The similarity between the ammonium and methane profiles in region 2 suggests that the shape of the adsorbate (both have 4 hydrogen atoms tetrahedrally arranged around a central atom) dominates this region of free energy change. Inspection of trajectories for both adsorbates at these molecule-surface separations confirms this; in region 2, both molecules are adsorbed onto, and move along, the bridging oxygen rails. We suggest the free energy penalty for methane displacing water in the first few solvent layers is not sufficiently offset by attractive interactions, unlike in the ammonium case. Methanol (Analogue for Serine Side Chain). As shown in Figure 3 the substitution of a single hydroxyl for a methane hydrogen can bring substantive changes to the free energy profile. Indeed, the plot shows two free energy minima, located at around 2.8 (minimum 1) and 3.9 (minimum 2) Å, respectively. The center of mass of methanol lies approximately halfway along the carbon-oxygen bond, hence the slight mismatch of the peaks and troughs of this plot compared with that for water shown in Figure 1. However, visual inspection of trajectories at molecule-surface separations corresponding with minimum 2 show the methanol located above the surface bridging oxygens, with the OH bond roughly perpendicular to the surface plane, pointing down toward the bridging surface oxygenssee Figure 4b. The hydroxyl on the methanol has replaced a water molecule in layer 2 of the solvent. The methanol is seen to sporadically hop along the rail of bridging oxygens (along the [001] direction), and also is seen to rotate freely around the near-perpendicular OH bond. The methyl group is vertically positioned in the void between solvent layers 1/2 and layer 3, thus minimizing disruptions to the structuring of the solvent at the interface. Trajectories corresponding to minimum 1 show the methanol hydroxyl in the place of a solvent layer 1 water molecule, vertically positioned directly over a 5-coordinated basal Ti atom. Layer 1 water molecules typically order such that the vector from hydrogen to hydrogen in these water molecules roughly aligns (on average) with the [11j0] direction. The methanol is seen to conform with this alignment, which persisted throughout the entire trajectory, such that the long-axis of the molecule roughly pointed along the [11j0] direction (see Figure S2 in the Supporting Information). This orientation of the methanol also minimizes displacement of adjacent layer 1 solvent along the [001] direction. Because of the relative orientation adopted by the surface-bound hydroxyl in minimum 1, the methyl group protrudes into layer 3 of the solvent. We therefore propose that minimum 1 is relatively higher in free energy than minimum 2 due to configurational entropy considerations; methanol in minimum 2 loses less entropy upon adsorption (it has considerable freedom to move as outlined above). Even though the potential enthalpic gains are relatively greater for methanol adsorbed in minimum 1 (compared with minimum 2), the
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Figure 4. Snapshots of (a) ammonium in minimum 1 and (b) methanol in minimum 2, adsorbed at the aqueous titania interface. In both cases, the adsorbate has displaced a water molecule from layer 2 of the solvent.
resulting adsorption geometry is confined with little mobility. Furthermore, the geometric constraints imposed by this confinement force the methyl group to protrude into layer 3 of the solvent, possibly disrupting the water structuring in this locality. A barrier of around 30 kJ mol-1 is presented to the methanol moving closer to the surface, from minimum 2 to minimum 1. Despite the fact that minimum 1 is relatively higher in free energy, it is conceivable that the molecule could become kinetically trapped at the surface once located in minimum 1, as the reverse free energy barrier is still quite large, at around 25 kJ mol-1. Nevertheless, the equilibrium positioning of this molecule is expected to lie at molecule-surface distances corresponding with minimum 2. Methanoate Ion (Analogue for Aspartic Acid Side Chain). The profile for methanoate adsorption, shown in Figure 5, displays a strong degree of structuring comparable to that seen for water, featuring four distinct minima. Minima 1-4 are positioned at molecule-surface distances of 2.4, 3.2, 5.1, and 7.8 Å, respectively. Unlike the case for water, minimum 1 (positioned closest to the surface) is not the lowest in free energy. Inspection of the trajectories associated with each minimum gives clues regarding the relative energetics of these minima. Minimum 1 is associated with the carboxylate exclusively adopting a bridging bidentate coordination, with each carboxylate oxygen coordinating to a 5-coordinated basal Ti atomssee Figure 7a. The carboxylate is aligned such that the oxygen-oxygen vector points along the [001] direction, resulting in displacement of two layer 1 water molecules. This arrangement persisted throughout the entire trajectory, with the adsorbate showing no lateral mobility over the surface. We propose that the overall enthalpic change upon methanoate adsorption at minimum 1 is perhaps not favorable, since the two waters coordinated to the two Ti atoms are replaced with a single carboxylate, where the carboxylate oxygen-oxygen distance is around 2.2 Å, not entirely commensurate with the distance between two 5-coordinated Ti atoms along the [001] direction (around 2.9 Å). We also propose that the overall entropic gain is also not large; two rigidly coordinated water molecules are released from layer 1 of the solvent (but not necessarily back into the bulk), but the methanoate is then rigidly locked into this binding geometry. The overall free energy
Figure 5. PMF free energy curve for adsorption of methanoate ion at the aqueous TiO2 (110) interface, where z is the distance between the methanoate center of mass and the basal Ti atoms. Numbers in bold indicate minima, as referred to in the text.
change is close to zero (with respect to the molecule in bulk solvent far from the surface). Further disruption to the solvent layers appears minimal, since the CH bond of the methanoate sits in the void directly above the layer 1 waters. The trajectories corresponding to minimum 2 involve monodentate coordination of one of the carboxylate oxygens to a single 5-coordinated basal Ti atom (shown in Figure S3 of the Supporting Information). The carboxylate oxygen not involved in surface binding points into layer 3 of the solvent, while the methanoate hydrogen points toward the layer 2 water oxygen atoms. The adsorbate again does not display lateral mobility, but does exhibit free rotation about the Ti · · · O (carboxylate) direction. One layer 1 water molecule is displaced by this configuration. In this instance we suggest the enthalpic difference is again not necessarily favorable overall, with the origin of the entropic differences perhaps less clear. The methanoate remained locked onto one Ti surface site, but retained some rotational freedom, while the layer 1 water molecule released by the methanoate adsorption recovers at least some mobility. Also, the uncoordinated carboxylate oxygen is positioned at an average surface separation of around 3.5 Å, which may impinge on the structuring of the water layer above it in a localized sense.
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For minimum 3, corresponding to the optimal moleculesurface distance, no layer 1/2 waters are displaced to accommodate the adsorbate. Monodentate coordination between the carboxylate oxygen and the waters above the basal Ti atoms was predominantly observed, but involving less rigidity than was noted for minimum 2; a number of events where the monocoordinated carboxylate oxygen was swapped were noted in the trajectories (see Figure S4, Supporting Information). The adsorbate stayed within the confines between two rails, and did not coordinate directly with the surface Ti atoms. Rather, this minimum seems to describe a water-mediated interaction with the surface, where the methanoate oxygens appear to be interacting with the hydrogen atoms on the layer 1/2 water molecules adsorbed at the surface sites, as shown in Figure 7b. The adsorbate also exhibited reasonable lateral mobility, with hopping between adsorbed waters noted; however, the methanoate remained within a single diamond-shaped region bounded by two 5-coordinated Ti surface atoms and two 6-coordinated Ti surface atoms, all four of which are located between two rails. In minimum 3, while the enthalpic gain in the methanoate adsorbing from bulk solution must be relatively weaker compared with minima 1 and 2, the entropic change associated with this minimum might not be unfavorable; no layer 1/2 waters are displaced, but the methanoate enjoys considerable lateral mobility and freedom to rotate (including swapping of the coordinated carboxylate oxygen atom). Lastly, minimum 4 was associated with coordination distances that reached beyond layer 3 of the solvent. A snapshot representative of this minimum is shown in Figure S5 of the Supporting Information. The methanoate ion was seen to rotate freely and exhibited substantial lateral mobility. However, a loose ordering of the carboxylate oxygen atoms remained (see Figure S6, Supporting Information). Inspection of the trajectories suggests that the methanoate is interacting weakly with the layer 3 waters. The structuring in layer 3 of the solvent is not as profound as seen for layers 1 and 2, but there remains a degree of orientational ordering (see refs 41 and 42) in this layer, where the water hydrogens on average point away from the titania surface. However, the entropic and enthalpic balance for minimum 4 does not appear to be strongly favorable. The structure of the free energy landscape along the molecule-surface separation coordinate indicates a rugged “funnelling” toward minimum 1, provided the barrier of around 60 kJ mol-1 in transitioning from minimum 4 to 3 has been surmounted. However, the majority of the equilibrium population should lie with minimum 3, where the methanoate interacts with the titania surface via the adsorbed water layers. Benzene and Guanidinium Ion (Analogues for Phenylalanine and Arginine, Respectively). Both of these adsorbates have a rigid, planar geometry with a considerable spatial extent; benzene has a diameter (hydrogen atom to hydrogen atom) of roughly 5 Å, while similarly, guanidinium has a diameter of just over 4 Å. The distance between the bridging oxygen rails that run along the [001] direction on the titania surface is around 6 Å. Taking the van der Waals (vdW) radii of all atoms into account, these various length scales imply that benzene will be unable to adsorb flat onto the titania surface (between the rails), while for arginine, this adsorption mode should be possible but quite repulsive. It follows that any minima will require the plane of the adsorbate adopting at least some tilt with respect to the surface plane. Since our free energy profiles are calculated with respect to distance from the surface to the adsorbate center of mass, this necessarily means that the adsorption minima, where
Monti and Walsh
Figure 6. PMF free energy curves for adsorption of benzene and the guanidinium ion, at the aqueous TiO2 (110) interface, where z is the distance between the adsorbate center of mass and the basal Ti atoms. Numbers in bold indicate minima, as referred to in the text.
present, will appear relatively more distant from the surface compared with our more compact adsorbates. The free energy profile for benzene (Figure 6) shows a trend very similar to what was seen for methane adsorption: essentially no change in free energy in moving from bulk solution toward the interface until a molecule-surface distance of around 7 Å is reached. In contrast, the guanidinium ion features two minima, located at molecule-surface distances of around 4.5 and 6.8 Å for minimum 1 and 2, respectively (Figure 6). Minimum 1 is the deepest seen for any of the adsorbates aside from water. Inspection of trajectories associated with this minimum reveals a bidentate bridging coordination, via the NH2 hydrogens, to two adjacent bridging oxygens along the [001] direction (see Figure 7c). In this configuration the guanidinium has replaced two waters from the layer 2 solvent, and is rigidly bound to the surface with no lateral mobility and only a little rotational mobility (about the [110] vector). The normal to the guanidinium plane remained roughly parallel with the surface plane throughout the production run. In the trajectories associated with minimum 2, we again noted a water-mediated interaction at the interface, as illustrated in Figure 7d). The guanidinium again adopts a bridging bidentate coordination, this time between the NH2 hydrogens and the oxygens of the layer 2 water molecules, such that the molecular center of mass sits directly above (much further above) the surface bridging oxygen. This interaction appears to be much weaker than the direct interaction noted for minimum 1; for most of the trajectory, the molecule loosely adopts an overall orientation similar to that seen for minimum 1 (molecular plane aligned along the [001] direction, with the normal to the molecule plane roughly parallel with the surface). In addition, the molecule has substantial lateral mobility and is seen to hop between the bridging oxygen rails (see Figure S7, Supporting Information). No waters from solvent layers 1 or 2 are displaced to accommodate the guanidinium in minimum 2. We rationalize the strong binding in minimum 1 as a combination of enthalpic gain and minimization of entropic costs; layer 2 waters are less rigidly bound than layer 1 waters, and so gain less entropy when displaced, while the guanidinium retains a modicum of rotational freedom upon binding. Discussion Our description of the aqueous rutile titania (110) interface is a modified version of a force field that describes interactions between titania and water, reported and validated by Pr˘edota et al.41 In the Pr˘edota force field, water was described using the SPC/E model. In our work, we have instead used the TIP3P
Adsorption of Amino Acid Analogues model, to ensure compatibility with the CHARMM force field, used to describe the biomolecular adsorbates. This combination of Predota force field and TIP3P has been previously validated in detail42 against existing simulation data,41 and experimental X-ray studies.39 The broad features of the interfacial water structuring and the trends in binding free energy found in this work are in satisfactory agreement with previous studies. The surface structural model used here for the rutile (110) surface is also an ideal one; studies using structural models involving surface charge density and partial hydroxylation,41 appropriate for describing the surface at physiological pH, are currently underway in our laboratories.67 We remark that the density of hydroxyls in these revised models still allows for substantial areas of “ideal” titania surface (as studied in this work) to be available for adsorbate binding. Nevertheless, our preliminary results indicate that adsorption (even for charged adsorbates) of the functional groups maintains very similar vertical positioning (i.e., the free-energy minima are located roughly at the same values of z), while the binding free energies (the well depths) show a little, but not dramatic, variation. We point out that in comparing experimental results with these calculations, not all of the available experimental data have been obtained with use of rutile TiO2 (110) surfaces (the potentiometric studies of Jonsson et al.46,47 and the peptide selection experiments of Dickerson et al.8 do primarily make use of the (110) surface). For example, the studies of McQuillan and co-workers44,43 probed adsorption onto amorphous titania films. Therefore, some of our findings that are intimately connected to the underlying geometrical features of the (110) surface should be interpreted cautiously. The sensitivity of the resulting PMF profiles was also checked with respect to the length of simulation time (for each constrained molecule-surface separation). For the guanidinium ion, we extended the run at each separation by a further 0.5 ns. This gave a total of 2 ns per separation (with around 50 molecule-surface separations in total, amounting to a total simulation time per PMF profile of roughly 100 ns). Discarding the first 0.5 ns of each point as an equilibration period, we recalculated the PMF profile using an average of the forces over the last 1.5 ns of each run. A plot of the original PMF profile and the recalculated profile are shown in Figure S8 of the Supporting Information. Visual inspection indicates there is scant difference between the two profiles (especially for the position and depths of the minima), suggesting that our PMF profiles are reasonably converged with respect to simulation time. A comment regarding the reliability of our free energy estimates at short range (for small values of z), with respect to our simulation times, is warranted. In the general case, we point out that a run time of 1.5 ns might not be sufficient for a molecule to sample all of the equivalent adsorption sites on a surface. Indeed, this could be a severe problem if the surface has a varied morphology (so that a variety of different possible adsorption sites are available for binding), such that only a subset of these sites are visited by the adsorbate during the simulation. However, in our case the periodicity of the surface means that, when the adsorbate is very near the interface, the unique sites are very small in number and easily covered. What is not achieved by some of our simulations at small z is the mobility (hopping) between these unique sites. For example, the methanoate ion adsorbed in minimum 1 (Figure 5) did not show any lateral mobility during the 1.5 ns run. Suppose that site-hopping events could only be observed (on average) over a 10 ns run (due to large energetic barriers). In this case, our 1.5 ns run has overestimated (by a small contribution) the loss of configura-
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Figure 7. Snapshots of the methanoate ion, and guanidinium ion, adsorbed at the aqueous titania interface. Methanoate adsorbed in minima 1 and 3 are shown in panels a and b, respectively. Guanidinium adsorbed in minima 1 and 2 are shown in panels c and d, respectively. In cases where the adsorption occurs via the water layers, layers 1 and 2 of the solvent are represented with ball-and-stick models.
tional disorder that accompanies the surface adsorption of methanoate at small z. This suggests that, for small values of z, the unsigned value of the change in entropy, in moving from bulk water to the surface, is overestimated by our simulations. This in turn suggests the predicted free energy change at small z should be slightly more negative than we have calculated. We prefix our comparisons between theory and experiment by reminding the reader that our calculations describe the interaction between the surface and the functional group of the side chain, not the residue side chain itself (e.g., we have not considered the methylene spacer groups between the R carbon and the functional group). However, while this omission may modify the absolute binding free energies, we expect the vertical positioning of the functional groups to not be substantially affected. On the basis of our methane adsorption data, we expect that any spacer groups in the side chain will be optimally positioned as far as possible from the surface, thereby limiting the free energy penalty incurred. This caveat, mentioned above, is apposite for comparison of our calculated methanoate ion adsorption data with experimentsspecifically because McQuillan and co-workers44,43 identified different adsorption behavior for aspartic acid, compared with glutamic acid (both of which feature the methanoate ion in the side chain, but with a different number of side chain spacer groups). However, these studies used amino acids as adsorbates, and it was proposed by these authors that the differences noted between these two amino acids might be attributed to participation of the C-terminal group in glutamic acid, in partnership with a longer side chain in glutamic acid. As far as aspartic acid adsorption is concerned, vibrational spectroscopy experiments have reported evidence for both bridging bidentate44 and monodentate45 coordination (albeit at
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different solution pH), both in “direct” conformations (i.e. not mediated by water layers) on the titania surface. Further, the recent potentiometric and adsorption study of aspartate adsorption on rutile titania crystals (with (110) as the predominant growth face) reported by Jonsson et al.47 gives evidence for the coexistence of two broad types of surface coordination: the “direct” bridging bidentate form suggested by McQuillan and co-workers and an “indirect” form (referred to in their paper as “outer-sphere coordination”). The data from these experimental studies do not necessarily contradict each other, as “indirect” species may not have been readily detected in the ATR-IR experiments. Our calculated optimal binding geometries at minimum 3 (indirect) and minimum 1 (direct, bridging bidentate) broadly agree with these experimental findings, despite the amorphous nature of the surface in the ATR-IR experiments. Considering that McQuillan and co-workers reported a binding constant for aspartic acid on titania of 9 ( 2 × 103 M-1 at a pH solution of 3, but were unable to measure it at higher pH we could say that this value, which corresponds to a binding free energy of roughly -23 kJ mol-1, represents an upper limit. Moreover, evidence from other, less direct experimental sources also indicates that carboxylate groups have some affinity for titania surfaces, particularly the presence of aspartic acid in the titania-binding peptide identified and characterized by Shiba and co-workers.6 These authors showed that binding affinity for the titania surface was significantly diminished upon mutation of the aspartic acid residue for alanine. Many previous simulations have indicated both “direct” and “indirect”29,19,26 contact between carboxylate groups and the titania surface under aqueous conditions. However, in a previous study,29,68 it was noted that “direct” configurations could only be obtained by constructing a “direct” initial geometry; i.e., a transition from “indirect” to “direct” was never observed in any of these simulations, consistent with the presence of a high free energy barrier between these two states. Lysine (ammonium) adsorption is indicated as being a favorable process in our calculations, with a binding free energy of around -6 kJ mol-1. McQuillan and co-workers reported a binding constant for lysine on titania of 3 × 103 M-1 at a pH of 7.4, equating to roughly -20 kJ mol-1. These authors suggested that the binding on titania was quite weak and mediated principally by electrostatic interactions (since they did not detect any changes in the vibrational spectra between free and adsorbed lysine). Our findings broadly agree with this conclusion; indeed, in the optimal binding geometry (minimum 1) lysine interacts with the surface bridging oxygen atoms, while in minimum 2 the interaction takes place through the water layers. Indirect evidence from peptide selection experiments also indicates that the affinity between lysine and titania is favorable; many of the reported “strong-binding” peptide sequences for titania heavily feature lysine.6-8,10,11,16,17 Designed peptides, enriched in lysine content, have also been recently shown to adsorb strongly onto titania in aqueous solution.18 When embedded in a peptide sequence, lysine has been shown by previous molecular simulations to form stable and lasting complexes with the aqueous titania interface.19,26 Skelton et al.29 reported peptide-titania simulations where the lysine residue formed stable contacts at nitrogen-surface distances corresponding with minimum 2 (see Figure 2 in this paper). The similarity of the measured binding free energy between lysine and aspartic acid is reflected in our findings. The adsorption of the guanidinium ion was calculated to be the most favorable of all the adsorbates considered, other than water. The free energy profile also appeared uncomplicated, with
Monti and Walsh only two minima, and lacking the extremely high free energy barriers as seen for methanoate. While, to the best of our knowledge, no direct experimental observations of the binding at the arginine-titania interface have been reported, again, indirect evidence, based on results of peptide selection experiments6-8,11,16 (including experiments with single-crystal rutile titania (110) target surfaces8), suggests that arginine has a strong affinity for titania. In particular, Hayashi et al.16 demonstrated that their peptide-titania adhesion forces were significantly reduced upon mutating arginine for alanine, and showed a slight decrease upon mutation of arginine for lysine. One possible explanation of the latter result is that arginine has a stronger binding affinity for titania compared with lysinesas echoed in our results. Previously reported simulations of the peptide-titania interface have also demonstrated that arginine can form stable interactions in both the “indirect”29 (corresponding with minimum 2 of Figure 6 in the present work) and “direct”68 forms. As with aspartic acid, no transitions from “indirect” to “direct” contact were observed in the simulations reported by these authors.26 Aside from the charged adsorbates, our analogue for serine (methanol) also showed interesting behavior, with a possible but slight favoring of adsorption (see minimum 2, Figure 3). While to our knowledge there are no direct experimental observations of serine adsorbing at the aqueous titania interface, a number of recent peptide selection and characterization studies suggest that polar residues could play a role in promoting peptide-titania adhesion.7-10 In particular, the cross-selection experiments of Fang et al.,9 where the resulting sequences could bind to titania but not to silica, showed an enrichment of polar residues. Notwithstanding our calculations do not show the hydrogen bonding in this instance to yield a strong individual interaction, we could speculate that a number of such polar residues, operating collectively, could form multiple contacts with the surface to yield a stable binding geometry. Further, experimental studies have reported that peptide adsorption is not completely eliminated in solutions with high ionic strength;10 one explanation is that favorable electrostatic interactions may not be the sole contributor to peptide-titania binding.21 In contrast to the previously discussed adsorbates, our hydrophobic analogues (benzene for phenylalanine, methane for alanine) did not show any indication that these groups could bind strongly to the surface, since the free energy profiles in these two cases were roughly positive everywhere. The only experimental evidence for this seems to come from Pa´szti and Guczi,45 who used SFG vibrational spectroscopy of phenylalanine on titania, albeit under acidic conditions (solution pH of 3 and 6), inferring only very weak interactions at the interface. Our calculated free energy profiles became substantially repulsive once these adsorbates intruded into the regions of highly structured water at the interface. Our calculations therefore suggest that hydrophobic content in peptides should be found as far as possible from the titania surface. One consequence of this observation is the interpretation of our binding results for other residue analogues, and the connection of these data to the binding of actual residues. The principal difference between the side chain analogues we have examined and the real side chains is the lack of methylene spacers (that connect the side chain to the R carbon in the backbone). Since arginine has three such spacers, and lysine four, these methylenes should act to decrease the binding affinity of the full side chains in this case. However, these residues can adopt conformations at the interface that minimize these unfavorable interactions, e.g. by keeping the side chain as perpendicular to the surface as possible (rather
Adsorption of Amino Acid Analogues than parallel, where the chain would lie flat on the surface), thereby minimizing the amount of methylene spacer exposed to each structured solvent layer. Such conformations involving both lysine and arginine side chains have been noted in previous simulations of peptides adsorbed on titania.29,23 Another consequence for the repulsive free energy changes for hydrophobic content close to the interface is on the backbone conformation of surface-adsorbed peptides. For example, in previous simulations of the peptide-titania interface29 where the hydrophobic content of the peptide was located in the center of the sequence, the resulting structural effect was that the center of the peptide was pushed away from the surface, allowing the charged residues at either end of the chain the freedom to interact with the surface. On this basis we suggest that hydrophobic content in titania-binding peptide sequences could play a useful structural role, helping to present other content (e.g., charged and polar residues) as favorably as possible at the interface. Therefore, judicious positioning of hydrophobic content, relative to other types of residues in a sequence, might actually result in an increase in binding affinity to titania, rather than hinder binding to the surface. We are aware that the identification of trends in individual surface-binding free energies is only one aspect of a complex solution in the path to being able to fully harness the potential of controlling the properties of the interface between peptides and inorganic materials and other effects should be taken into account. However, we believe that these models, through which we have identified optimal adsorption configurations of single side chains, could be a good starting point for defining efficient and effective strategies to create peptide sequences with predictable behavior at the aqueous inorganic interface. Summary and Conclusions The potential of mean constraint force approach, in partnership with atomistic molecular dynamics simulations, was used to calculate the change in free energy upon adsorption of amino acid side chain analogues at the aqueous rutile titania (110) interface. Our results indicated that both positively charged and negatively charged moieties have favorable free energy of binding to the titania surface. Stable contact, mediated via the first two solvent layers at the interface, was also indicated for the charged adsorbates. Hydrophobic adsorbates showed no appreciable binding to the titania surface. In contrast, the binding for our serine analogue (methanol) featured a slight possibility to bind via hydrogen bonding to the titania surface. Our findings should be useful, in partnership with other data such as peptide conformation and intrapeptide interactions, in establishing the principles that control peptide binding to titania. Acknowledgment. The authors gratefully acknowledge the computing facilities of the Centre for Scientific Computing, University of Warwick. T.R.W. thanks Mr. Robert Innes for help with the orientation calculations. Supporting Information Available: Figures showing the average orientation of the N-H bond in ammonium as a function of distance from the titania surface, snapshot of methanol adsorbed at the aqueous titania interface in minimum 1, snapshot of the methanoate ion adsorbed at the aqueous titania interface in minimum 2, distance between each methanoate oxygen and a single underlying 5-coordinated surface titanium atom as a function of time, snapshot of the methanoate ion adsorbed at the aqueous titania interface in minimum 4, distance between each methanoate oxygen and the basal layer of
J. Phys. Chem. C, Vol. 114, No. 50, 2010 22205 5-coordinated titanium atoms as a function of time, distance between the guanidinium carbon and two distinct, underlying surface bridging oxygen atoms (located in adjacent rails on the surface) as a function of time, and comparison of PMF profiles for the guanidinium ion showing the difference between the original profile and the recalculated profile. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) Sarikaya, M.; Tamerler, C.; Jen, A. K. Y.; Schulten, K.; Baneyx, F. Nat. Mater. 2003, 2, 577. (2) Dickerson, M. B.; Sandhage, K. H.; Naik, R. R. Chem. ReV. 2008, 108, 4935. (3) Belton, D. J.; Patwardhan, S. V.; Annenkov, V. V.; Danilovtseva, E. N.; Perry, C. C. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 5963. (4) Chen, C. L.; Rosi, N. L. Angew. Chem., Int. Ed. 2010, 49, 1924. (5) Lambert, J.-F.; Stievano, L.; Lopes, I.; Gharsallah, M.; Piao, L. Planet. Space Sci. 2009, 57, 460. (6) Sano, K. I.; Shiba, K. J. Am. Chem. Soc. 2003, 125, 14234. (7) Chen, H. B.; Su, X. D.; Neoh, K. G.; Choe, W. S. Anal. Chem. 2006, 78, 4872. (8) Dickerson, M. B.; Jones, S. E.; Cai, Y.; Ahmad, G.; Naik, R. R.; Kro¨ger, N.; Sandhage, K. H. Chem. Mater. 2008, 20, 1578. (9) Fang, Y.; Poulsen, N.; Dickerson, M. B.; Cai, Y.; Jones, S. E.; Naik, R. R.; Kro¨ger, N.; Sandhage, K. H. J. Mater. Chem. 2008, 18, 3871. (10) Khoo, X. J.; Hamilton, P.; O’Toole, G. A.; Snyder, B. D.; Kenan, D. J.; Grinstaff, M. W. J. Am. Chem. Soc. 2009, 131, 10992. (11) Gronewold, T. M. A.; Baumgartner, A.; Weckmann, A.; Knekties, J.; Egler, C. Acta Biomater. 2009, 5, 794. (12) Sano, K. I.; Sasaki, H.; Shiba, K. Langmuir 2005, 21, 3090. (13) Sano, K. I.; Ajima, K.; Iwahori, K.; Yudasaka, M.; Iijima, S.; Yamashita, I.; Shiba, K. Small 2005, 1, 826. (14) Yamashita, I.; Kirimura, H.; Okuda, M.; Nishio, K.; Sano, K. I.; Shiba, K.; Hayashi, T.; Hara, M.; Mishima, Y. Small 2006, 2, 1148. (15) Hayashi, T.; Sano, K. I.; Shiba, K.; Kumashiro, Y.; Iwahori, K.; Yamashita, I.; Hara, M. Nano Lett. 2006, 6, 515. (16) Hayashi, T.; Sano, K. I.; Shiba, K.; Iwahori, K.; Yamashita, I.; Hara, M. Langmuir 2009, 25, 10901. (17) Chen, H. B.; Su, X. D.; Neoh, K. G.; Choe, W. S. Langmuir 2009, 25, 1588. (18) Gertler, G.; Fleminger, G.; Rapaport, H. Langmuir 2010, 26, 6457. (19) Carravetta, V.; Monti, S. J. Phys. Chem. B 2006, 110, 6160. (20) Ko¨ppen, S.; Ohler, B.; Langel, W. Z. Phys. Chem. 2007, 221, 3. (21) Monti, S. J. Phys. Chem. C 2007, 111, 6086. (22) Monti, S.; Carravetta, V.; Zhang, W. H.; Yang, J. L. J. Phys. Chem. C 2007, 111, 7765. (23) Monti, S. J. Phys. Chem. C 2007, 111, 16962. (24) Polzonetti, G.; Battocchio, C.; Dettin, M.; Gambaretto, R.; Bello, C. D.; Carravetta, V.; Monti, S.; Iucci, G. Mater. Sci. Eng., C 2008, 28, 309. (25) Monti, S.; Carravetta, V.; Battocchio, C.; Iucci, G.; Polzonetti, G. Langmuir 2008, 24, 3205. (26) Monti, S.; Alderighi, M.; Duce, C.; Solaro, R.; Tine´, M. R. J. Phys. Chem. C 2009, 113, 2433. (27) Carravetta, V.; Monti, S.; Wang, W. H. Theor. Chim. Acta 2009, 123, 299. (28) Chen, M. J.; Wu, C. Y.; Song, D. P.; Li, K. Phys. Chem. Chem. Phys. 2009, 12, 406. (29) Skelton, A. A.; Liang, T.; Walsh, T. R. ACS Appl. Mater. Interfaces 2009, 1, 1482. (30) Goede, K.; Busch, P.; Grundmann, M. Nano Lett. 2004, 4, 2115. (31) Oren, E. E.; Tamerler, C.; Sahin, D.; Hnilova, M.; Seker, U. O. S.; Sarikaya, M.; Samudrala, R. Bioinformatics 2007, 23, 2816. (32) Willett, R. L.; Baldwin, K. W.; West, K. W.; Pfeiffer, L. N. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 7817. (33) Meyers, S. R.; Hamilton, P. T.; Walsh, E. B.; Kenan, D. J.; Grinstaff, M. W. AdV. Mater. 2007, 19, 2492. (34) Sano, K. I.; Yoshii, S.; Yamashita, I.; Shiba, K. Nano Lett. 2007, 7, 3200. (35) Kokubun, K.; Kashiwagi, K.; Yoshinari, M.; Inoue, T.; Shiba, K. Biomacromolecules 2008, 9, 3098. (36) Kashiwagi, K.; Tsuji, T.; Shiba, K. Biomaterials 2009, 30, 1166. (37) Evans, J. S.; Samudrala, R.; Walsh, T. R.; Oren, E. E.; Tamerler, C. MRS Bull. 2008, 33, 514. (38) Oren, E. E.; Notman, R.; Kim, I. W.; Evans, J. S.; Walsh, T. R.; Samudrala, R.; Tamerler, C.; Sarikaya, M. Langmuir 2010, 26, 11003. (39) Zhang, Z.; Fenter, P.; Cheng, L.; Sturchio, N. C.; Bedzyk, M. J.; Pr˘edota, M.; Bandura, A.; Kubicki, J.; Lvov, S. N.; Cummings, P. T.; Chialvo, A. A.; Ridley, M. K.; Be´ne´zeth, P.; Anovitz, L.; Palmer, D. A.; Machesky, M. L.; Wesolowski, D. J. Langmuir 2004, 20, 4954.
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(40) Koppen, S.; Langel, W. Surf. Sci. 2006, 600, 2040. (41) Pr˘edota, M.; Bandura, A. V.; Cummings, P. T.; Kubicki, J. D.; Wesolowski, D. J.; Chialvo, A. A.; Machesky, M. L. J. Phys. Chem. B 2004, 108, 12049. (42) Skelton, A. A.; Walsh, T. R. Mol. Simul. 2007, 33, 379. (43) Roddick-Lanzilotta, A. D.; Connor, P. A.; McQuillan, A. J. Langmuir 1998, 14, 6479. (44) Roddick-Lanzilotta, A. D.; McQuillan, A. J. J. Colloid Interface Sci. 2000, 227, 48. (45) Pa´szti, Z.; Guczi, L. Vib. Spectrosc. 2009, 50, 48. (46) Jonsson, C. M.; Jonsson, C. L.; Sverjensky, D. A.; Cleaves, H. J.; Hazen, R. M. Langmuir 2009, 25, 12127. (47) Jonsson, C. M.; Jonsson, C. L.; Estrada, C.; Sverjensky, D. A.; Cleaves, H. J.; Hazen, R. M. Geochim. Cosmochim. Acta 2010, 74, 2356. (48) Wei, Y.; Latour, R. A. Langmuir 2009, 25, 5637. (49) Langel, W.; Menken, L. Surf. Sci. 2003, 538, 1. (50) Koppen, S.; Bronkalla, O.; Langel, W. J. Phys. Chem. C 2008, 112, 13600. (51) Koppen, S.; Langel, W. Phys. Chem. Chem. Phys. 2008, 10, 1907. (52) Raut, V. P.; Agashe, M. A.; Stuart, S. J.; Latour, R. A. Langmuir 2005, 21, 1629. (53) O’Brien, C. P.; Stuart, S. J.; Bruce, D. A.; Latour, R. A. Langmuir 2008, 24, 14115. (54) Schravendijk, P.; Ghiringhelli, L. M.; Site, L. D.; van der Vegt, N. F. A. J. Phys. Chem. C 2007, 111, 2631. (55) Ghiringhelli, L. M.; Hess, B.; van der Vegt, N. F. A.; Site, L. D. J. Am. Chem. Soc. 2008, 130, 13460. (56) Notman, R.; Walsh, T. R. Langmuir 2009, 25, 1638.
Monti and Walsh (57) Hoefling, M.; Iori, F.; Corni, S.; Gottschalk, K.-E. Langmuir 2010, 26, 8347. (58) Basalyga, D. M.; Latour, R. A. J. Biomed. Mater. Res., Part A 2002, 64A, 120. (59) Lindahl, E.; Hess, B.; van der Spoel, D. J. Mol. Model. 2001, 7, 306. (60) MacKerell, A. D.; Bashford, D.; Bellott, M.; Dunbrack, R. L.; Evanseck, J. D.; Field, M. J.; Fischer, S.; Gao, J.; Guo, H.; Ha, S.; JosephMcCarthy, D.; Kuchnir, L.; Kuczera, K.; Lau, F. T. K.; Mattos, C.; Michnick, S.; Ngo, T.; Nguyen, D. T.; Prodhom, B.; Reiher, W. E.; Roux, B.; Schlenkrich, M.; Smith, J. C.; Stote, R.; Straub, J.; Watanabe, M.; Wiorkiewicz-Kuczera, J.; Yin, D.; Karplus, M. J. Phys. Chem. B 1998, 102, 3586. (61) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. J. Chem. Phys. 1983, 79, 926. (62) Neria, E.; Fischer, S.; Karplus, M. J. Chem. Phys. 1996, 105, 1902. (63) Nose´, S. Mol. Phys. 1984, 52, 255. (64) Hoover, W. G. Phys. ReV. A 1985, 31, 1695. (65) Essman, U.; Perela, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. J. Chem. Phys. 1995, 103, 8577. (66) Hess, B. J. Chem. Phys. 2002, 116, 209. (67) Walsh, T. R.; Monti, S., 2010, in preparation. (68) Skelton, A. A. Modelling the Interaction Between Titania Surfaces and Strong-binding Peptides, Ph.D. Thesis, University of Warwick, Department of Chemistry, 2008.
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