To What Extent Does Surface Hydrophobicity Dictate Peptide Folding

Oct 20, 2015 - This is consistent with previous works by Garde and co-workers(22, 23) that water density next to a surface is not a good indicator of ...
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To what extent does surface hydrophobicity dictate peptide folding and stability near surfaces? Gül H. Zerze, Ryan G. Mullen, Zachary A. Levine, Joan-Emma Shea, and Jeetain Mittal Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.5b03814 • Publication Date (Web): 20 Oct 2015 Downloaded from http://pubs.acs.org on October 26, 2015

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To what extent does surface hydrophobicity dictate peptide folding and stability near surfaces? G¨ul H. Zerzea,† Ryan G. Mullen,‡ Zachary A. Levine,¶ Joan-Emma Shea,∗,¶ and Jeetain Mittal∗,† Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA 18015, USA, Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA, and Department of Chemistry and Biochemistry, University of California, Santa Barbara, CA 93106, USA E-mail: [email protected]; [email protected] a

GHZ, RGM anf ZAL contributed equally to this work.

Abstract Proteins-surface interactions are ubiquitous in both the cellular setting and in modern bioengineering devices, but how such interactions impact protein stability is not well understood. We investigate the folding of the GB1 hairpin peptide in the presence of self-assembled monolayers and graphite like surfaces using replica exchange molecular dynamics simulations. By varying surface hydrophobicity, and decoupling direct protein-surface interactions from water-mediated interactions, we show that surface ∗

To whom correspondence should be addressed Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA 18015, USA ‡ Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA ¶ Department of Chemistry and Biochemistry, University of California, Santa Barbara, CA 93106, USA †

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wettability plays a surprisingly minor role in dictating protein stability. For both the β-hairpin GB1 and the helical miniprotein TrpCage, adsorption and stability is largely dictated by the nature of the direct chemical interactions between the protein and the surface. Independent of the surface hydrophobicity profile, strong protein-surface interactions destabilize the folded structure while weak interactions stabilize it.

Introduction In dilute environments, small globular proteins reliably fold to a well-defined three dimensional structure, which is stabilized by hydrophobic interactions, hydrogen bonds, and electrostatic interactions. This folded structure is intimately tied to the protein’s biological function. While bulk studies have been invaluable in eludicating many aspects of the thermodynamics and kinetics of protein folding, they fail to capture the complexity associated with folding in more realistic environments. For instance, in the cell, proteins reside in a crowded environment, 1 where their folding is affected by the presence of a host of other molecules, from osmolytes to nucleic acids, to lipids. Proteins in the cell can bind to surfaces (among others, the ribosome exit tunnel, chaperones and membranes), a process that can alter protein folding kinetics and stability. Protein-surface interactions are also ubiquitous in biotechnological applications (biosensors, microarrays, etc.) 2 and used by various organisms (for instance, mussels use adhesive proteins for underwater adhesion to a variety of surfaces). 3 An understanding of how proteins adsorb onto biological and nano-based surfaces and the impact of those surfaces on protein stability is key for advancing the development of biotechnological devices. A common practice in the literature is to characterize polymer adsorption near a surface in terms of surface wettability or hydrophobicity (we will use these two terms interchangeably in this manuscript). 4–8 A correlation has been noted between free energies of adsorption and macroscopic contact angles, but it remains to be determined how surface wettability affects the stability of a protein. The majority of computational studies on relating surface 2

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wettability with protein folding have focused on homopolymers consisting of hydrophobic residues, whose behavior may differ from proteins, which are heteropolymers with small, imperfect hydrophobic cores. In general terms, there are three major contributions to protein stability on a surface: (i) an excluded-volume (EV) effect from the physical presence of the surface that reduces the entropy of the unfolded state, 9,10 thereby stabilizing the protein, (ii) direct surface-protein interactions that compete with intra-peptide interactions, therefore (mostly) destabilizing effect, and (iii) an effect related to water-mediated interactions near surfaces dependent on surface wettability. This indirect effect, due to modified water behavior near surfaces, is particularly pertinent in the case of a hydrophobic surface, which could be either stabilizing or destabilizing. The complicating factor in developing a predictive theoretical framework is that the three terms listed above are not necessarily independent of each other. The EV entropic reduction is a consequence of protein adsorption onto the surface, which is in turn driven by proteinsurface attraction and/or hydrophobic effect. And the same factors that make a surface hydrophilic, e.g., high surface charge density or strong van der Waals attraction, may also increase protein-surface attraction. In this work, we focus on the contribution of surface hydrophobicity to protein stability. To address this question, we consider two types of surfaces that are used for different applications: self-assembled monolayers (SAMs) and graphite-like surfaces (GLSs) that are relevant for numerous bio-nano-technology applications. First, we characterize the surface wettability by computing the contact angle of a water droplet on each of the SAMs and GLSs. SAM hydrophobicity is determined by the physico-chemistry of the headgroup, whereas the hydrophobicity of the GLS stems from the strength of the van der Waals attraction. We note that practically there are many ways to change the wettability of a GLS. We consider SAMs and GLSs ranging from hydrophilic to hydrophobic. Next, we present the results of replica exchange molecular dynamics (REMD) simulations on the folding of a

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alkane connected to three different head groups: hydroxyl (-OH), methoxyl (-OCH3 ) and methyl (-CH3 ). The -CH3 surface is hydrophobic, having a contact angle θ = 112◦ . The -OCH3 SAM is neutral with θ = 85◦ . The -OH surface is hydrophilic with the water droplet completely spreading across the SAM. Average air-water interface of droplets on SAMs and GLSs are shown in supporting information (SI) Fig. S1. We consider three GLSs of different hydrophobicity. Each surface shares the same honeycomb lattice structure in each layer and interlayer spacing, but have different Lennard-Jones (LJ) parameters (see SI Table S1). A hydrophilic GLS (θ = 38◦ ) is obtained using the default AMBER ff03 LJ parameters for sp2 carbon. The neutral case parameters are chosen to approximately match the experimental graphite contact angle, for which the LJ carbon-carbon well-depth ǫCC is less than half of the hydrophilic sp2 ǫCC . 11 The MD contact angle is θ = 78◦ without finite-size corrections as compared to the experimental contact angle θ = 86◦ . A hydrophobic GLS (θ = 123◦ ) is created using a shallow LJ potential, with a minima an order of magnitude higher than the neutral case. The -CH3 SAM and weakly attractive GLSs considered in this work are both hydrophobic (θ > 90◦ ). Similarly, -OCH3 SAM and base case GLS exhibit neutral wettability (θ ∼ 90◦ ) and the -OH SAM and strongly attractive GLSs are hydrophilic (θ < 90◦ ). Our primary aim is to find out if surface hydrophobicity (defined by the water contact angle) alone is sufficient to predict whether a given surface will have a stabilizing or destabilizing influence on protein folding. Next, we address this question by REMD simulations of a well-studied β-hairpin peptide, 12–16 which displays many features of a real protein such as two-state folding, tertiary contacts, and hydrogen bonding. 17–19 REMD simulations are performed to investigate the folding thermodynamics of the GB1 hairpin on the SAMs and GLSs described above. GB1 hairpin is a 16-residue peptide sequence that interconverts between a stable folded β-hairpin and a variety of unfolded conformations in aqueous solution, with an estimated folded fraction around 0.5 from different experiments at the room temperature. 20,21 Here, the folded fraction at 300 K is assessed using

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GB1 hairpin is stable on hydrophobic and hydrophilic self-assembled monolayers To identify the effect of surface hydrophobicity on water and protein structuring near SAM surfaces, we plot water and protein density distributions normal to each SAM surface in Fig. 2. In all three cases, the water density profiles are quite similar (Fig. 2a) despite significant differences in surface hydrophobicity (characterized by water droplet contact angle). This is consistent with previous works by Garde and co-workers 22,23 that water density next to a surface is not a good indicator of hydrophobicity, and quantities such as contact angle and density fluctuations are more quantitative measures. Also, water exhibits minimal layering at any of the three SAM surfaces, and water density is close to the bulk value except in the small interfacial region (z < 0.75 nm in Fig. 2a). Additionally, the protein density profiles (Fig. 2a) show significant protein density only in the interfacial region (z < 1 nm) indicating that GB1 adsorbs onto the SAM surface in each case. Near the hydrophobic SAM GB1 orients with the aromatic side chains– Trp-3, Tyr-5 and Phe-12 –next to the surface (Fig. 2a, red shaded). The aromatic rings on these residues are predominantly oriented parallel to the surface (see SI Fig. S3). Small but detectable changes in protein density profiles are visible with decreasing surface hydrophobicity; profile broadens only slightly near the neutral SAM. Near the hydrophilic SAM there is non-zero protein density even beyond 2 nm distance from the interface. Additionally, the orientation of aromatic side chains changes significantly near the hydrophilic SAM: Trp-3 and Phe-12 adopt a wide range of orientations and Tyr-5 is predominantly oriented perpendicular to the surface (see SI Fig. S3). The width of the protein density profile is indicative of the width of the free energy basin of the adsorbed peptide. The broader density profile near the hydrophilic SAM suggests that the adsorption free energy basin would also be wide. Deighan et al. previously observed that two peptides LKα14 and LKβ15 exhibit a broader free energy basin near a hydrophilic SAM than near a hydrophobic SAM. 24 The protein density profile cannot, however, be used 7

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to calculate the binding strength accurately. Specialized sampling techniques that bias the peptide-surface separation distance would be more appropriate to compute an accurate free energy of adsorption. 6,24 For example, Deighan et al. observed that LKα14 and LKβ15 are more strongly bound to a hydrophilic SAM than to a hydrophobic SAM using such a technique. Fig. 2b shows the bulk free energy surface projected along dRMS and Rg . The narrow folded basin is characterized by low dRMS (< 1.5 ˚ A) and Rg (∼0.8 nm) values, whereas the unfolded basin is quite broad and characterized by a range of dRMS and Rg values. The free energy surfaces for peptide adsorbed onto SAM surfaces are also shown in Fig. 2b. The adsorption appears to stabilize the folded state with respect to bulk in all three SAM cases, irrespective of the surface hydrophobicity. To quantify this stabilization, we calculate the fraction folded using two criteria. Using the dRMS < 1.5 ˚ A cutoff, the fraction folded is 76%, 91% and 95% respectively for hydrophobic, neutral and hydrophilic SAMs as compared to 53% for the bulk case. 25 The dominant cluster in each case is also composed of folded configurations, comprising 75%, 86% and 84% of the population respectively for hydrophobic, neutral and hydrophilic SAMs, as compared to 47% for the bulk case. The representative structures of the dominant cluster are shown in Fig. 2c. To quantify the folded state stabilization near SAM surfaces, we calculate the change in folding free energy with respect to bulk as, ∆∆F = ∆FSAM - ∆Fbulk , where ∆F = -kB T ln(Pf olded / (1 - Pf olded )). Based on the folded population from dRMS cutoff, we estimate ∆∆F = -0.6, -1.7, -2.3 kB T for hydrophobic, neutral and hydrophilic SAMs, respectively. The order of stability is: bulk < hydrophobic SAM (-CH3 ) < neutral SAM (-OCH3 ) < hydrophilic SAM (-OH), i.e., increase in stability with decreasing SAM hydrophobicity. The preceding results would seem to indicate that hydrophobic surfaces destabilize the protein as compared to hydrophilic surfaces (note that protein is still more stable near a hydrophobic SAM than in bulk). To what extent is this destabilization due to surface wettability, and not to surface chemistry and topography? To address this question, we

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to use more robust measures such as contact angle and density fluctuations 22 to characterize surface wettability. GB1 hairpin adsorbs onto each GLS, as evidenced by the protein density profiles in Fig. 3a. On the neutral GLS, GB1 hairpin orients with the hydrophobic side chains– Trp-3, Tyr-5 and Phe-12 –next to the surface (see Fig. 3c) and the aromatic rings on these residues are predominantly oriented parallel to the surface (see SI Fig. S4). Next to the hydrophilic surface, the hydrophobic residues are positioned similarly as in the neutral case, even though the peptide as a whole is closer to the surface. Near the hydrophobic surface, the peptide is shifted further away from the surface than the neutral case. As a result, the aromatic rings are only weakly oriented parallel to the surface (see SI Fig. S4). Fig. 3b shows the free energy surfaces projected along dRMS and Rg for the three GLS cases. Near the hydrophilic surface, GB1 hairpin completely unfolds and no configurations have dRMS < 1.5 ˚ A. Consequently, the folded basin is not present in the free energy landscape. The largest structural cluster is populated by disordered configurations. Near the neutral surface, 11 ± 6% of the peptide population remains folded, i.e., exhibits dRMS < 1.5 ˚ A. In agreement with the dRMS analysis, the cluster of folded configurations comprises 11% of the population, while the folded population of GB1 hairpin in the bulk is 53%. 25 Near the hydrophobic surface, peptide remains predominantly folded. dRMS analysis shows a 81 ± 6% folded population and the dominant cluster (82%) is of folded configurations. Based on the folded population from dRMS cutoff, we estimate the change in folding free energy with respect to bulk, ∆∆F = ∆Fgraphite - ∆Fbulk = -0.8 and +2.7 kB T for hydrophobic and neutral GLSs, respectively. The order of stability is: hydrophilic GLS < neutral GLS < bulk < hydrophobic GLS, i.e., increase in stability with increasing surface hydrophobicity. Most importantly and somewhat surprisingly, the comparison between the SAM and GLS data highlights differences in interfacial protein folding and stability, dependent on surface chemistry, even if the two surfaces have similar hydrophobicity. In contrast to the stabilizing effect of hydrophilic and neutral SAMs (Fig. 2), the proximity to GLSs with similar contact

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angles (Fig. 3) has a destabilizing effect on hairpin folding, with respect to bulk. To understand this behavior, we return to our earlier decomposition of surface-induced contributions to protein stability in terms of excluded-volume (EV) effects (∆FEV ), direct surface-protein interactions (∆Fprot−surf ), and water-mediated effects near the surface (∆Fhyd ). The contribution from confinement induced EV effects will be comparable due to similar distance between confining surfaces in all the cases and cannot account for the observed differences in ∆∆FSAM/GLS . One can approximately estimate the range of EV induced stabilization from the hydrophilic SAM case, (∆∆Fhphil SAM = -2.3 kB T), as the direct protein-surface interactions are minimal (based on the broad protein density profile), and the protein is solvated in bulk-like water away from the surface (∆Fprot−surf ∼ ∆Fhyd ∼ 0). We note that stronger protein-surface interactions can also increase the EV induced stabilization as the protein will be localized near a surface as opposed to being confined within two surfaces. In the next section, we assess the relative impact of protein-surface (∆Fprot−surf ) and water-mediated interactions (∆Fhyd ) on the observed destabilization of the GB1 hairpin with respect to EV stabilization, for the case of GLSs.

What controls protein folding near surfaces – protein-surface interactions or surface wettability? The hydrophilic GLS described above has a strong van der Waals attraction to both water and protein atoms. Likewise, the hydrophobic surface has a weak attraction to all the atoms. We will refer to these hydrophilic and hydrophobic surfaces as strong-hydrophilic and weak-hydrophobic, respectively. Two additional GLSs are obtained by decoupling the surface-water and surface-protein interactions as shown in SI Tables S1 and S2. The weak-hydrophilic surface interacts weakly with protein atoms, but its interactions with water (and protein-water interactions) are unchanged from the strong-hydrophilic case. Similarly, the strong-hydrophobic surface is strongly attractive to protein atoms, but surfacewater (and protein-water) interactions are unchanged with respect to the weak-hydrophobic 11

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strong-hydrophobic cases, respectively. The water density profiles are identical, but the protein density profiles differ significantly, with the protein density showing a peak close to the surface in the strong-hydrophobic case. On the other hand, when we reduce protein-surface attraction strength with respect to the originial hydrophilic surface, the protein desorbs from the surface and exhibits a broad density peak in the middle, in contrast to the peak near the surface that is observed in the strong-hydrophilic case (compare panels (c) and (d) in Fig. 4). In the case of weak interactions between the protein and the surface (weak-hydrophilic case), the strongly adhered layer of water near the hydrophilic surface prevents GB1 hairpin adsorption, reminiscent of the simulations by Garde and co-workers in which a hydrophobic polymer did not absorb to a -OH SAM surface. 6 In keeping with the results from the protein density profiles, the free energy profiles differ significantly between the original and decoupled constructs. Compared to the case of the original hydrophobic GLS surface (panel a), increasing protein-surface attraction (at the same level as for the original hydrophilic GLS) leads to complete destabilization of the folded state (panel b). On the other hand, decreasing protein-surface attraction (at the same level as for the original hydrophobic GLS) for a hydrophilic surface stabilizes the folded state significantly (compare panels c and d). We note that the free energy profiles are similar for surfaces with the same protein-surface but different surface-water interaction parameters (compare panels a and d, and panels b and c). Taken together, these results strongly suggest that direct protein-surface attraction rather than water-mediated interactions (a hydration contribution) constitute the driving force for determining protein stability for the systems studied here. Since the GB1 hairpin is stable on all SAM surfaces with respect to bulk, we can conclude that the effective protein-surface attraction is relatively weak regardless of the SAM headgroup. The enhanced protein adsorption (Fig. 2a) with increasing surface hydrophobicity is indicative of stronger surface-protein interactions, and therefore reduced stability as we have observed. While comparing the observed behavior between SAMs and GLSs in the

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Figure 5: Free energy projected onto dRMS and Rg for TrpCage in bulk (Left) and TrpCage on hydrophobic GLS. context of direct surface-protein interactions, it is important to consider the surface density of atoms. A GLS has a surface density of 38.4 atoms/nm2 , whereas SAM surface density is about an order of magnitude lower at 4.7 headgroups/nm2 , which intrinsically leads to relatively weaker direct protein-surface interactions. Increasing the surface-water interactions in case of GLSs also lead to significant strengthening of direct surface-protein attractions, thereby protein destabilization with decreasing surface hydrophobicity.

Helical TrpCage protein is stabilized on a hydrophobic GLS Considering the SAM and GLS results as a whole, a picture emerges whereby the strength of direct protein-surface interactions plays a more dominant role than surface wettability in determining protein stability. In the case of SAM surfaces, attraction to the protein is sufficiently weak that the protein is stable on both hydrophobic and hydrophilic surfaces. For GB1 hairpin, the peptide is more stable on hydrophilic than hydrophobic SAM surfaces. We note that for the α-helix forming peptide LKα14, which interacts via different aminoacid/SAM contacts than in the case of GB1 hairpin, helicity is enhanced on a hydrophobic

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SAM as compared to a hydrophilic SAM. 24 This observation reinforces the point that specific protein-surface interactions determine the stability of the adsorbed protein. To further probe this issue, we turn to a protein with helical fold, TrpCage, and examine its folding near a weak-hydrophobic GLS (in other words, a surface with parameters constructed using the correct mixing rules, with weak interactions between water and surface, and between protein and surface atoms). Fig. 5 show the free energy landscapes in bulk and near a hydrophobic GLS. In addition to the folded basin, Trpcage populates a variety of unfolded configurations in bulk, but the overall dRMS values samples are lower than GB1 hairpin. Near a hydrophobic GLS, the peptide essentially remains folded and the unfolded basin is absent. The protein is ∼90% folded in the bulk 26 and retains its fold near the weak-hydrophobic GLS, with 98 ± 1% by dRMS and 94% of configurations belong to the largest cluster. This further confirms that weak interactions will lead to stabilization on hydrophobic surfaces.

Conclusions We have performed fully atomic, explicit solvent replica exchange molecular dynamics simulations of the folding of GB1 near SAMs and GLSs with different hydrophobicities. Our goal was to explore the question of whether surface hydrophobicity alone is sufficient to determine protein stability. Experimental studies of proteins adhering to hydrophobic surfaces at high protein/surface coverage show destabilization, while studies at low surface coverage generally show protein stabilization. The inference is that protein-protein interactions mediate denaturation, not protein-surface interactions. Our simulations mimic the low-surface coverage case and are consistent with the picture that hydrophobic surfaces stabilize proteins. However, our simulations reveal that the extent of stabilization depends critically on the specific interactions between the protein and the surface, an effect that trumps wettability arguments alone. In the case of the SAM surfaces, we found that all three SAMs considered (hydrophobic,

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neutral and hydrophilic) stabilized the protein with respect to the bulk, with the highest stability found for hydrophilic surfaces. This trend is qualitatively similar to what is observed in simulations of the collapse of hydrophobic homopolymers near SAMs: the polymer adopted extended, non-spherical conformations when adsorbed to hydrophobic surfaces, and spherical, compact globular conformations (similar to those seen in the bulk) in the presence of increasingly hydrophilic surfaces. We note that it is not straightforward to extrapolate from hydrophophobic homopolymers to proteins. Indeed, homopolymers do not have a well-defined folded state, and there is not always a clear separation between the folded and unfolded configurations when free energy is projected along the radius of gyration (a commonly used order parameter for polymers). Furthermore, the hydrophobic core of a protein is small, particularly for our peptide. In the case of larger proteins, the core can be imperfect, accomodating hydrophilic residues in its interior. The homopolymer studies would suggest that the protein would adsorb and unfold on hydrophobic GLS, and be stabilized on hydrophilic graphene, however, just the opposite is observed in our simulations. Construction of a hybrid model system in which water-surface interactions (hydrophobicity) was decoupled from protein-surface interactions (direct interactions) revealed that surface hydrophobicity does not govern protein stability. A GLS with strong protein-surface interactions has the same effect on protein stability whether the surface is hydrophobic or hydrophilic. The stabilization on hydrophobic surfaces observed for the β-hairpin GB1 was shown to hold as well for the α-helical TrpCage protein. Future work will involve extending these studies to larger proteins to investigate the extent to which additional factors, such as the presence of a well-defined hydrophobic core, can influence the conclusions drawn here based on the study of peptides.

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Materials and Methods Simulations were performed using Gromacs 4.6.1 (SAMs) and 4.5.6 27 (GLSs). For contact angle calculations, each SAM surface having 6.92 x 6.84 nm lateral dimensions are simulated with a droplet of 886 TIP3P 28 water molecules. Chains forming SAM whose side-views are illustrated in Fig. 1, are organized in hexagonal lattice geometry. To prevent chains from melting or diffusing into the solution, sulphur atoms representing thio-groups kept frozen in place during all the study. Force field parameters for SAM surfaces are reported in ref. 29 Each SAM-water droplet system was propagated using stochastic dynamics with a 1/ps friction coefficient and 2 fs timestep for 4 ns at 300 K. Each of the GLSs in this study are 4 layers thick and were generated using the Carbon Nanostructure Builder plugin for VMD. 30 The surface atoms are fixed in place and interact with water via a Lennard-Jones (LJ) potential with ǫ and σ parameters given in SI Table S1. The contact angle of water on each GLS was computed using a droplet of 1000 TIP3P 28 water molecules on a 12.0 x 12.3 nm GLS. The initial configuration of water molecules was a hemisphere. The system was propagated using stochastic dynamics with a 1 fs timestep for 1 ns. The temperature was set to 300 K with 1.0 ps coupling constant. Further details about contact angle calculations are given in SI. Folding of the GB1 hairpin on three SAMs and five GLSs were investigated by replica exchange molecular dynamics (REMD). 31 The GB1 hairpin corresponds to residues 41-56 of the full length GB1 protein (PDB: 1GB1 32 ). Amber ff03* force field (Amber ff03 33 with a modified ψ torsion potential 34 ) parameters were used for protein interactions. Cross-interactions between nonbonded atoms were obtained from the Lorentz-Berthelot combination rules. All simulations were performed at constant volume with periodic boundary conditions. Further details about simulation system and parameters are given in SI. Acknowledgements: We are grateful to Professor Shekhar Garde for providing the selfassembled monolayer surface parameters. JM acknowledges the participation of Dr. Apratim Bhattacharya in the early stages of this work. We acknowledge support from the Center for Scientific Computing at the California Nanosystems Institute (NSF Grant CNS-0960316), 17

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the National Science Foundation (NSF) Grant MCB-1158577, and the U.S. Department of Energy, Office of Basic Energy Science, Division of Material Sciences and Engineering under Award (DE-SC0013979). This work was supported by the MRSEC Program of the National Science Foundation under Award DMR 1121053. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant ACI-1053575. We would also like to acknowledge the computational capabilities of the Texas Advanced Computing Center at the University of Texas at Austin (Grants TG-MCA05S027 and TG-MCB120014), which provided HPC resources that contributed to the research results reported within this paper (www.tacc.utexas.edu). Supporting Information Available Text providing details of materials and methods, 2 tables and 4 figures are available. This material is available free of charge via the Internet at http://pubs.acs.org/.

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