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Simulations of Ovocleidin-17 Binding to Calcite Surfaces and Its Implications for Eggshell Formation Colin L. Freeman,*,† John H. Harding,† David Quigley,‡,|| and P. Mark Rodger§,|| ‡
Department of Engineering Materials, University of Sheffield, U.K. Department of Physics, §Department of Chemistry, and Centre for Scientific Computing, University of Warwick, U.K. )
†
ABSTRACT: Ovocleidin-17 has been identified as a major eggshellforming protein although the role and function it performs is still uncertain. Classical molecular dynamics simulations are presented for the adsorption of the whole ovocleidin-17 protein onto the {10.4} surface of calcite in several different configurations. For each configuration detailed data are presented of the bound protein with hydrogen-bond analysis, structural examination, and adsorption energies. The simulations demonstrate that binding is a competition between the protein and the strongly bound surface water such that the most energetically favorable configuration minimizes the displacement of this surface water. The ovocleidin-17 protein is found to be relatively rigid, undergoing few structural changes on contact with the surface, and the arginine residues are the most important binders to the calcite surface.
1. INTRODUCTION The avian eggshell is a fascinating part of the biomineral world as its formation is one of the fastest known biomineralization processes, depositing 56 g of calcite in 22 h.1 In order for the embryo to survive, the eggshell must satisfy a stringent set of criteria: it must allow gas and water exchange, it must provide protection from physical trauma and microorganisms but allow for the eventual escape of the bird, it must minimize temperature fluctuations, and it must provide calcium for the developing skeleton. Given these diverse requirements it is little surprise that the eggshell possesses a complex structure.2 The eggshell structure can be divided into three layers. The innermost layer consists of two nonmineralized fibrillar sublayers with a core mostly made of cross-linked type X collagen. The second layer, the mammillae, is an aggregation of organic material that provides the substrate for the initial calcium carbonate deposition. The bulk of the calcite is located in the third layer where it grows in large columns known as palisades which terminate at the cuticle of the shell. Unlike many biomineral systems (e.g., coccolithophores) the eggshell may appear to demonstrate less morphological control over the calcite. This is deceptive. For example, the predetermined density of microcrystals in the inner palisade region will propagate cracks allowing the young chick to peck out. 1.1. Ovocleidin-17. Analyzing the eggshell matrix has identified several proteins unique to the matrix and therefore expected to be crucial to the production of the eggshell. Of these, the C-type lectin group is thought to be present in all the avian species. This group is thought to have a well-preserved residue structure with a calcium binding region.3 Of these, ovocleidin-17 (OC-17) was the first to be characterized4 and subsequently sequenced5 and is found uniformly throughout the palisade layer, r 2011 American Chemical Society
but in greater concentration within the mammillary layer, suggesting a potential link to initial calcite deposition. The OC-17 protein is composed of 142 amino acids (residues). The structure, as shown in Figure 1, is largely globular with two long helix segments (residue numbers 2734 and 5060) and several regions of β-sheets. There are two long chainlike sections that do not have any clear secondary or tertiary structure. The protein has six cysteine residues which have an R group including a sulfur atom which is able to covalently bond to the sulfur atom from another cysteine residue forming a strong disulfide bridge (see Figure 1F). The three disulfide bridges within OC-17 impose a large degree of stability on the structure. The protein sequence includes a large number of charged residues (see Table 1) which give the protein an overall charge of þ7 at a pH of 7. Unlike other C-type lectins (e.g., ansocalcin) OC-17 does not appear to bind calcium ions well6,7 and may bind carbonate ions.8 The comparative study of ansocalcin and OC-17 by Lakshminarayanan et al.7 noted only a 36% similarity between the sequences of OC-17 and ansocalcin and particularly that some key residue locations may be different, suggesting that the proteins could perform different functions. This study also observed that the charged surfaces of the two proteins are dissimilar with a positive charge on the surface of OC-17 and a negative charge on the surface of ansocalcin. The lack of aggregation in OC-17 compared to ansocalcin, as interpreted from dynamic light scattering tests, was also highlighted by the same authors. In this study the crystallization of calcium Received: January 6, 2011 Revised: March 1, 2011 Published: March 31, 2011 8175
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Figure 1. Ovocleidin-17 protein, shown in three different orientations in panels A, C, and E. The R-helices are depicted in purple, β-sheets in yellow, loop regions as thick blue coils, and the cysteine residues are shown with individual atoms with the disulfide bridges in yellow. The orientations are also shown with transparent sections to highlight the (B) helices and sheets, (D) loop regions, and (F) cysteine residues.
Table 1. Description of Significant Residues Present in the OC-17 Proteina residue
functional group
alanine
CH3
arginine aspartic acid
(NH2)2þ CO2
serine
OH
a
The functional groups present in the R group of each amino acid are listed.
carbonate with these two proteins showed marked differences. The rate of crystallization was enhanced with OC-17 but with little influence over the final calcite morphology. In comparison, ansocalcin produced screw dislocations at low protein concentrations and porous, polycrystalline aggregates at high protein concentrations. These data suggest that the role and function of OC-17 may be different to other C-type lectins. Morphological control of calcium carbonate has, however, been observed6 where crystal aggregation and step rounding was reported. The function
of OC-17 in eggshell mineralization remains uncertain, but the above experimental data suggests that the primary role of OC-17 may be in the initial crystallization process. The process of calcite crystallization remains a topic of high interest and debate. Traditional models for nucleation are being replaced by theories involving amorphous precursors.9 Amorphous calcium carbonate (ACC) has been observed in several biomineral systems10 including (in vitro) quail eggshell mineralization11 and hen eggshell formation12 where it acts as an intermediate to the formation of more thermodynamically stable polymorphs of calcium carbonate such as calcite and aragonite. Simulation methods are increasingly being used to tackle complex biomineral systems with the development of force fields to model the mineralwatermolecule interface,13 binding of molecules to the mineral surfaces,14,15 and the advent of largescale computing essential to model explicitly the huge number of atoms present in this system. The determination of the crystal structure for OC-176 now means that a full biomineralizing protein can be modeled in contact with its biomineral. As part of this study the authors have already examined the crystallization of ACC nanoparticles in contact with OC-17 and observed the ability of the protein to encourage the formation of calcite.16 The OC-17 binds to ACC nanoparticles and lowers or removes the energy barrier to crystallization, facilitating the formation of calcite, agreeing closely with experimental suggestions that OC-17 is involved in initial crystallization. After crystallization, OC-17 readily detaches from the larger simulated calcite nanoparticles (of 300 CaCO3 formula units) which leads to the speculation that this protein may operate as a catalyst, sequentially encouraging crystallization in ACC nanoparticles. This leaves fundamental questions about the binding process of OC-17 with calcite, which are also instrumental for our understanding of any morphological control that OC-17 can exert on calcite. To further answer these questions it is essential that a full systematic study of the interactions of OC-17 with the solution and calcite is performed to determine the actual binding motifs present in this system. Here we present simulations of OC-17 in contact with the calcite {10.4} surface in a variety of configurations that clearly demonstrate the vital characteristics of the protein binding to the mineral surface.
2. SIMULATION METHODS All the molecular dynamics (MD) simulations were performed using classical molecular dynamics as implemented in DL_POLY 3.0923 using the NVT ensemble with a relaxation time of 0.1 ps and 1 fs time steps. The Pavese force field24,25 was used to model the calcite mineral, and the TIP3P model26 was used for the water. The potentials for the protein were taken from the general united atom AMBER force field set27 (the terms for the disulfide bridges were added from the general all-atom force field). Interactions between the solvent/protein and the mineral were either taken from refs 13 and14 or, in the case of sulfur groups, fitted using the methods described in these two references (see section 2.2 for further details). Slabs of {10.4} calcite were constructed from preoptimized surface structures using the METADISE (minimum energy techniques applied to dislocation interface and surface energy)28 code. The slabs were 100.6 Å 97.5 Å and were 10 layers thick giving a total of 4800 CaCO3 formula units. The slabs were solvated and run for 1 ns at 310 K with no constraints on the atomic positions to ensure that the surface and slab structure 8176
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The Journal of Physical Chemistry C were stable. The protein structure was taken from ref 6 and ionized for a pH of 7. 2.1. Configurational Exploration. The protein may bind to the surface in a large number of potential positions or orientations. Over the course of a single simulation it is extremely unlikely that all these configurations will be explored and the lowest energy configuration found. It is therefore vital to sample a range of configurations by performing multiple simulations in order to sample a large enough region of phase space to find the low-energy configurations. The size of the system (over 100 000 atoms) under investigation in this paper makes including water too expensive to perform on a large set of configurations. (The simulations presented here were performed on the U.K. supercomputer HECToR which at the time was ranked 20th in the world top 500 list. Each full simulation used 512 processors for over 350 h.) To reduce the computational expense the molecule was simulated in both vacuum and explicit solvent for 500 ps. The resulting structures were found to be very similar (due to the presence of the disulfide bridges), justifying the option of using vacuum conditions for the exploratory simulations to rapidly sample an increased range of configurational space. In vacuum, the binding process is rapid and the protein does not explore multiple configurations by moving parallel to the surface or undergoing large rotations. To avoid the protein being trapped in a single potential well, the protein was placed 8 Å above the calcite slab in 25 positions generated by an equally spaced 5 5 grid in the plane parallel to the surface plane, and at each of these positions the protein was rotated through 64 different orientations (comprising four 90° C rotations around each axis). This gave a total of 1600 different starting points for the exploratory simulations. These 1600 configurations were then used as starting points for vacuum simulations of 200 ps. All these simulations resulted in the protein binding tightly with a large number of functional groups on the surface. Because structurally the configurations were difficult to differentiate, energy was used as a selection criteria for the next simulations. The lowest and highest final energy configurations were selected for each of the 25 surface positions (from the 64 orientations available at each position). The protein was removed from the vacuum box and solvated (in its current conformation) with 20 500 water molecules using the Packmol program29 to generate a water density of 990 kg m3. This protein and water box were then recombined with the calcite slab so that the protein and water molecules were ∼4 Å and ∼8 Å above the surface, respectively. The simulation was then heated from a starting temperature of 10 K in 50 K steps every 100 ps until a final temperature of 310 K was reached. The pressure was set as 1 atm. Each configuration was then run for 2 ns, and the lowest and highest energy configurations were again selected from these configurations. These two configurations were then run until their energies were stable and, under visual examination, the protein was showing no signs of translation; this typically amounted to approximately 20 ns. In order to isolate the effects of position and orientation on the surface binding a further configuration (configuration 3) was run. In this system, the same position and orientation of the protein as in configuration 1 was used, but the simulation was started with the protein closer to the surface to ensure that the starting separation between the surface and protein was not limiting the contact achieved. Convergence with the size of the simulation box was confirmed by simulation of the protein in a range of solvated boxes with sides ranging from 85 to 100 Å. The same protein structure
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Table 2. List of Additional Cross-Term Potentials Used for the Protein Binding to Calcite mineral Ca
Buckingham Potentials (A exp(F/r) C/r6) organic A (eV) F (Å) C (eV Å6) S
1442.35
0.2962
0.0
Lennard-Jones 126 potentials (E0[(R0/r)12 2(R0/r)6]) mineral organic E0 (eV) R0 (Å) O
OH
0.00218
3.721
and interaction energy with the water was observed for boxes with a size 85 Å or greater. 2.2. Additional Potentials. Although the sulfur atoms were not expected to interact with the surface due to their confined location within the protein, potentials were derived for completeness. This fitting procedure used the same methods described in ref 13 using CaS as the base mineral. The final values used in the simulation can be seen in Table 2. In addition, a further Lennard-Jones 126 potential was added for the alcohol-hydrogen interacting with the carbonate oxygen of the calcite (see Table 2). This was introduced to prevent the alcohol-hydrogen passing too close to a carbonate-carbon as the two atoms had no short-range interaction between them. 2.3. Analysis Methods. Several methods were used to analyze the interaction between the protein and calcite slab which are described below. 2.3.1. Z-Density. The Z-density records the density of a particular atom type as one moves along the Z-direction of the simulation cell. For these simulations this plots out the density of the atom as one moves away in a direction perpendicular to the mineral surface. 2.3.2. Adsorption Energy. The adsorption energy describes the strength of interaction between the calcite surface and the protein, so the lower the adsorption energy the stronger the interaction, and a negative value implies that adsorption is energetically favored. In the solvated system the protein must move from the solution into contact with the surface displacing any of the surface water on the calcite and some of the proteinsolvent water shell. Therefore, the adsorption energy of the protein (Eproteinmineral) was calculated with respect to the water-only solvated surface (Ewatermineral) and the solvated protein (Ewaterprotein) in a similar fashion to that reported for other molecular binding14,22 and organicmineral interfaces,30 and the reader is referred to these articles for further details. Eprotein mineral ¼ Ewater mineral protein Ewater mineral Ewater protein ð1Þ where Ewatermineralprotein is the configurational energy from the simulation of the whole system. In order to calculate this energy, further simulations of the solvated molecule, bulk water, and water at the mineral surface were performed. All these simulations used the same methods described above and were run until the energies showed convergence, whereupon the final configurational energies were collected over the last 1 ns of simulation time. To ensure consistency, the watermineral cell contained the same number of water molecules as the watermineralprotein simulation (23000) and an identical slab of {10.4} calcite. The only difference between these simulations was the removal of the protein and the 8177
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2.3.3. Residue Binding. It is particularly interesting to examine which protein residues (and which part of these residues) bind to the calcite surface. This analysis was performed by calculating the separation of all the protein residues from the surface every 10 ps throughout the simulation. When atoms showed contact with the surface (any atom of the residue within 2.5 Å of the surface) for a long period of the time (∼1 ns) during the simulation it was assumed that this residue may be binding and the interaction was examined in more detail. 2.3.4. Protein Structure. The structure of the protein was also examined during the course of the simulation with two methods: hydrogen-bond analysis and the root-mean-square displacement (rmsd). Hydrogen bonds were assumed to have maximum bond lengths of 3.3 Å (OHO), 3.5 Å (OHN), and 3.5 Å (NHN) with a maximum deviation of 30° from a linear bond. The H-bonds were counted within the protein and with the surrounding water every 10 ps. To analyze the interactions between the protein, surface, and water, hydrogen bonds were also calculated between the protein and the surface carbonate oxygen ions. The rmsd for each protein was calculated every 10 ps. The distance, δi2, was taken between R-carbons of every four residues. sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 i¼N 2 rmsd ¼ δi ð2Þ N i¼1
∑
3. RESULTS AND DISCUSSION
Figure 2. Binding of OC-17 to the calcite {10.4} surface in (A) configuration 1, (B) configuration 2, and (C) configuration 3.
reduction of the c-axis of the cell, perpendicular to the surface, to account for the smaller cell volume with the loss of the protein volume while maintaining the same water density. The bulk water and proteinwater simulations also used identical numbers of water molecules to the watermineralprotein simulation with again adjustments in the c-axis of the cell to ensure the same water density.
3.1. Protein Binding. The final three configurations are shown in Figure 2. Table 3 lists the residues that are in contact with the surface. In configuration 1 three arginine residues (residue numbers 46, 86, and 89) are in contact with the surface. As can be seen, the arginine groups bind through their hydrogen atoms (see Table 1 for details of each residue’s functional groups). The hydrogen atoms form a hydrogen bond with the oxygen atoms of the surface carbonates. Over the course of the simulation the nitrogen atom does occasionally come into close contact with the surface (the calcium cations), but the majority of the interaction is through the hydrogen. The separations between the atoms are relatively constant over the course of the simulation implying a strong interaction. In configuration 2, several other residues can be seen in contact with the surface including alanines and serines. The serines bind through the alcohol functional group with a Coulombic interaction between the alcohol-oxygen and the calcium and a hydrogen bond between hydrogen and the carbonate-oxygen, although this seems to be a weaker interaction judging by the variation of the bond during the course of the simulation. This is very similar to that modeled for simple alcohol molecules on calcite surfaces.13 The interactions of the alanine residue arise from the amino acid backbone as the carboxyloxygen makes contact with the surface calcium ions. Configuration 3 shows far more residues binding to the surface (see Table 3). Along with several extra arginine residues, we also observe a nonpolar proline, alanine, and serine residue and an aspartic acid residue. The acidic functional group of the aspartic acid binds via a Coulombic interaction with the calcium ions in the surface. The proline residue binds through the oxygen which interacts electrostatically with the calcium ions in the surface. 8178
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Table 3. List of Amino Acid Residues That Bind to the Calcite Surface for Each Configurationa configuration
a
residues (no.)
1
arginine (46), arginine (86), arginine (89)
2
serine (27), arginine (28), serine (31), arginine (34), arginine (35), alanine (83), serine (85), arginine (86), arginine (89), arginine (112)
3
aspartic acid (1), proline (13), arginine (46), serine (47), alanine (48), arginine (52), arginine (86), arginine (89), arginine (97)
Residue numerical sequence taken from ref 5.
Table 4. Hydrogen Bonds for the Different Configurations of the Protein at the Surfacea H-bonds b
protein configuration
internal
waterc
waterd 1
119 117
311 348
2
119
298
3
124
294
a
Figure 3. Arginine residue 86 bound to the {10.4} calcite surface in configuration 1.
The arginine residues are the most common binders (see Figure 3 for a detailed image of the binding at the surface). This may be due to the long length of the guanidinium group which is able to reach to the surface through the water layers causing minimal disruption. These arginine residues seem to pull other parts of the protein into contact with the surface, and in these cases we frequently see the serine residue. The amine and alcohol groups can both bind as the nitrogen (amine) and oxygen (alcohol) interacts with the calcium ions, and the hydrogen can hydrogen-bond to the carbonate-oxygen. This dual binding may facilitate a stronger binding than the acidic groups, which are not frequently observed. These can only interact with the surface calcium and will have a repulsion from the surface carbonateoxygen. The interactions between OC-17 and carbonate anions have been observed in electrode studies8 which, along with Reyes-Grajeda et al.6 and Lakshminarayanan et al.,7 also found that OC-17, unlike other C-type lectins, does not significantly bind calcium cations. The behavior of ions within a mineral surface may be different to those in solution, but it does suggest that interaction through the carbonate ions is reasonable. The standard calcium binding region of alanine(105)arginine(109) is actually highly positive unlike the other C-type lectin proteins. Therefore, our simulations agree that positive functional groups may be more important to the function of this protein than negative (acidic) functional groups. The large number of arginines that are distributed across the whole protein also provides ample opportunity for the protein to bind whatever the orientation of the protein with the surface. This also suggests that the protein may be capable of interacting with many surfaces or ions simultaneously. 3.2. Protein Structure at the Surface. The number of hydrogen bonds internally present within the protein (119) is fairly constant between the solvated protein and when the protein is on the surface: 117, 119, and 123 for configurations 1, 2, and 3, respectively (Table 4). The number of hydrogen bonds between the protein and the water is significantly larger in configuration 1 compared to the solvated protein. This may be due to the protein sitting well above the calcite
The solvation of the protein in bulk water is also given for comparison. b H-bonds from proteinprotein interactions. c H-bonds from protein water molecules. d Protein solvated in water with no surface present.
surface where there is a increased density of water due to the surface ordering. For configurations 2 and 3 the number of hydrogen bonds is significantly reduced (by 13 and 17, respectively) when the protein binds to the surface, presumably due to the proximity of the surface that prevents a full solvation shell properly surrounding the protein in these configurations. In both configurations 2 and 3, parts of the protein backbone are in contact with the surface, and therefore a significant amount of the molecule is no longer solvated by the water. The rmsd values were calculated for the protein in each of the configurations and compared to the solvated protein. None of the rmsd values were substantially different (greater than 2 SD) from the solvated protein. This demonstrates, in agreement with the hydrogen-bond data, that no major structural changes are taking place within the protein when it binds to the surface. The protein sections with an rmsd value that is more than 1 SD from the values of the solvated protein are listed for each configuration in Table 5. In all configurations the residues that are demonstrating the changes are localized to particular regions, 6075, 9099, 104112, 117125, and these regions are not directly involved in binding to the surface. Examining the protein structure we can observe that these regions are all “loop” sections, i.e., chainlike regions of the protein (as highlighted in Figure 1D) that sit on the surface of the globule and are not near to the disulfide bridges and therefore should be highly flexible. As noted above, one of these regions alanine(105)arginine(109) is thought to bind cations in other C-type lectins, but this is unlikely in OC-17 as this region has a positive charge. So there may be a greater flexibility in this region due to the lack of cations that could stabilize the loop. The rmsd differences observed are therefore due to the random fluctuations of the protein structure during simulation rather than any particular features of the binding. There are a greater number of rmsd variations for configuration 1 compared to configurations 2 and 3, which is surprising given that configuration 1 has far less contact with the surface than the other two configurations. Considering this observation, 8179
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Table 5. Residue Sections with a Difference in the 14 rmsd of Greater Than 1 SD from That of the Solvated Protein Are Listed for Each Configurationa configuration
a
rmsd
1
5760, 5962, 6063, 6366, 6467, 6568, 6669, 6871, 9396, 9699, 97100, 98101, 104107, 105108, 106109, 107110, 108111,
2
110113, 115118, 117120, 118121, 121124 36, 47, 58, 5962, 6063, 6467, 6568, 6669, 8588, 97100, 98101, 107110, 117120, 118121, 120123, 121124
3
5255, 5760, 5962, 6366, 6467, 6871, 106109, 107110, 115118, 118121
Residue numerical sequence taken from ref 5.
Table 6. Adsorption Energies for the Proteina configuration
a
adsorption energy/kjmol1
1
422 ( 43
2
201 ( 36
3
53 ( 42
Errors calculated by binning 0.5 ns sections of the simulation data.
the smaller structural differences in configurations 2 and 3 probably arise because the surface imposes a steric limit on the flexibility of the protein by reducing the available space, which is less significant for configuration 1 where the protein is further from the surface. In all cases the protein remains relatively unchanged in both solvated and bound states. This lack of structural change may be an important feature of its function. The presence of three disulfide bridges (see Figure 1F) within the protein implies that the structure is intended to remain relatively rigid, as does the globular shape which makes it less prone to twisting or turning. The inability of the protein to undergo large structural changes may limit multiple functional groups from binding to the surface at the same time, which will affect the binding strength. A more flexible protein may be able to get more functional groups in contact with the surface than OC-17 without disrupting much surface water which will increase the strength of binding. 3.3. Adsorption Energies. The adsorption energies of the protein in the three different configurations can be seen in Table 6. What is surprising is that the adsorption energy is lowest for configuration 1 which has only three arginine residues in contact with the surface compared to 10 and 9 residues for configurations 2 and 3, respectively. Both these configurations have as many or more arginine residues in contact with the surface, so this implies that the energy is not dependent only on the binding of particular functional groups. In addition the planar position and orientation of the protein with respect to the surface in configurations 1 and 3 is the same, so it is unlikely that a particularly favorable spatial arrangement of the 3 arginine residues can be used to explain the substantial energy differences. The proteins do undergo some structural relaxation at the surfaces when binding, so this may be partially responsible for some of these energy differences, but the structural changes are generally small. In addition the greatest structural change is observed for configuration 1, which has the lowest binding energy, which suggests that the structural changes are not energetically prohibitive. Another issue that should be considered is the involvement of the surface water in the simulation. The effect of water has been identified in several cases14,17,18 as being responsible for unexpected adsorption energies. Calcite surfaces produce a large degree of ordering in the water structure at the interface causing
Figure 4. Z-density of water molecules at the calcite surface for configuration 1 (green with circles), configuration 2 (magenta with triangles), configuration 3 (black with squares), and the system with no protein present (red with crosses). The inset shows the first two peaks of the plot in greater detail.
the water to form layers as observed in both experiment19 and theory.20,31 Any molecule adsorbing at the surface must disrupt this water structure, and therefore, any energy gain from the binding of residues will be countered by the energy loss of water displaced from the surface. Figure 4 shows the Z-density profile of the water at the calcite surface for the three configurations and for the surface with no protein present. The water produces the ordered layered structure described in both experiment and theory in all four cases. As expected, a greater density of water molecules is present at the interface with no protein present compared to configurations 1, 2, and 3. Close inspection, however, reveals differences between the density profiles of the three protein adsorption configurations. There is a greater density of water present in the first water layers in configuration 1 compared to configurations 2 and 3. In this configuration the protein only binds through three arginine groups, whereas in the other cases the whole protein backbone is in close proximity to the surface and displaces far more water. The adsorption energies suggest that the binding of the protein backbone is energetically less favorable than that of the water (Table 6). When the protein adsorbs onto the surface many of the atoms within the molecule have a weak interaction with the surface since they possess little charge, e.g., the hydrocarbon-hydrogens and the backbone. Although several of the functional groups (such as the alcohol and amine groups) within the protein bind strongly to the mineral they cannot compensate for the weak binders also present at the interface. The configuration with the lowest adsorption energy is the one where only the strong binding 8180
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Figure 5. Fraction of water volume for each configuration compared to the calcitewater system with no protein present: configuration 1 (red with crosses), configuration 2 (magenta with triangles), configuration 3 (green with circles).
Figure 6. Z-density of configuration 2 (red with crosses) and configuration 3 (green with circles). Also shown is the difference in Z-density between configuration 2 and configuration 3 (magenta with triangles) with the units on the right-hand axis.
functional groups (amines) get into contact with the surface, so no weak binding elements of the protein displace the surface water. Figure 5 shows the integration of the Z-density as one moves out from the surface as a fraction of the water volume in the calcitewater system with no protein present. There is a greater volume of water in configuration 1 compared to configurations 2 and 3 near to the surface (approximately 10 water molecules between configurations 1 and 3). In addition to the calcitewater interface we should also consider the proteinwater interface. The protein is naturally surrounded by a solvent shell. Interactions with this shell will depend on the number of hydrogen bonds between the water and protein. When the protein was placed in close proximity to the surface in configurations 2 and 3 the number of hydrogen bonds with the water was reduced compared to the solvated protein, presumably due to the calcite surface. In contrast, the number of hydrogen bonds in configuration 1 is increased. Our analysis of the water structure at the surface shows a greater water density in the immediate vicinity of the surface compared to the bulk water density. In configuration 1 the protein resides above this surface water, and therefore, the greater water density may enable the formation of additional hydrogen bonds with the solvent. Molecular binding studies of peptides on titania surfaces have reported the peptide molecules effectively binding to the tightly held surface water.21 These extra interactions may also contribute to the greater adsorption energy of configuration 1 compared to configurations 2 and 3, which have lost water protein hydrogen bonds. The energy differences between configurations 2 and 3 are also interesting to consider. More residues bind in configuration 2 compared to configuration 3. There are six arginine and three serine residues in configuration 2 compared to five and one in configuration 3. The volume of water in configuration 3 at the surface is greater than in configuration 2 which implies that water effects would lower the energy for configuration 3. Examination of the actual Z-density (Figure 6), however, shows that there is a greater amount of water in the structured layers (the peaks) in configuration 2. The greater water volume of configuration 3 is due to the occupancy in the interlayer regions where the water is displaced from the surface. This suggests that a greater disruption
of the water structure occurs in configuration 3 than configuration 2. Therefore, the energy penalty for the water will be greater in configuration 3 compared to configuration 2. The differences are smaller compared with configuration 1, and we see the energy differences are also smaller. Moreover, we have already observed that more residues are in contact with the surface in configuration 2 than configuration 3, which would also generate a lower adsorption energy. The adsorption energies reported here are configurational energies not free energies and as such do not contain an entropy contribution. This cannot be calculated by a standard MD simulation. It is possible that entropy effects may be significant given that we are displacing largely ordered water molecules from a surface into the random water network (an entropy gain) and adsorbing a large molecule (an entropy loss). Given the sizes of the adsorption energies, and that there is a difference of only 10 water molecules between the configurations which could generate a maximum contribution of approximately 80 kJ mol1 K1 at 310 K (assuming each water molecule has an entropy change of 3RT between surface and bulk, i.e., all the classical translation and rotational entropy), it is unlikely that entropy will adjust the qualitative conclusions. The protein remains largely unchanged between the configurations so that its entropy change on binding can be assumed be relatively small. The effect of entropy change due to water should, however, be considered and will be examined closely in a forthcoming publication. 3.4. Implications for Ovocleidin-17 Function. In Freeman et al.16 OC-17 was demonstrated to encourage the crystallization of calcite from an amorphous nanoparticle and then detach itself from the surface potentially to start a new crystallization event. If OC-17 operates as a catalyst to calcite crystallization for multiple nanoparticles, it is important that the binding is not too strong to prevent the molecule detaching from the surface and also that the structure of the protein is not lost on binding. Given the large number of configurations explored, the adsorption energy of 422 kJ mol1 for configuration 1 should represent a low-energy configuration (although not necessarily the lowest) and so can be compared with confidence to other adsorption energies. A single methanoic acid molecule and trisaccharide molecule on {10.4} calcite have been reported with 8181
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configuration 1 very little of the protein is actually in contact with the surface. This positive region is mainly the surface exposed to the tightly bound water layer, but due to the tilt of the protein, some of this region is perpendicular to the surface. In configuration 2 most of the binding residues (the helix and loop sections) in contact with the surface are part of the positive region. Given that these two configurations were selected as strong and weak binders it is interesting to observe that they both appear to expose the positive region to the surface implying that it may not be an important part of surface binding, although with only two configurations this cannot be conclusive. Experimental results7 suggest that OC-17 molecules do not aggregate, so it is unlikely that the charge distribution encourages interactions with other proteins. Obviously this cannot be investigated with only a single protein in the simulation, but the role of aggregation will be investigated in a future publication.
Figure 7. Charge density of the OC-17 protein in (A) configuration 1 and (B) configuration 2. The proteins are shown in the same orientation as in Figure 1. The binding residues are highlighted. Red is negative charge, and blue is positive charge.
adsorption energies of 6414 and 94 kJ mol1,22 respectively. Given these molecules cover a very small amount of the surface in comparison to the protein, many more of these molecules could bind simultaneously for one protein molecule; therefore, the adsorption energy for the protein is not as large as might be expected. Nanoparticle adsorption is a different scenario due to the greater relaxation of the surface ions and the curvature of the surface compared to the periodic {10.4} surface. This will result in a different adsorption energy, but our results suggest that the OC-17 protein may not bind as strongly to a calcite surface as expected for a protein of its size. Our results also clearly indicate the structure of the protein remains relatively constant through the binding process. Both these features are consistent with a potential catalytic function for OC-17 in encouraging the formation of calcite. For a protein with only 142 residues, OC-17 has a large number of charged residues (21 basic and 14 acidic). This implies that a large charge density is a crucial part of the protein’s function. Examination of the charge density has shown that an overall positive charge loops around the molecule but is mostly concentrated in one region.6 This region mainly relates to one of the R-helices (2635), two loop sections (8198 and 103115), and part of the tail section (128135). Figure 7 shows the charge density of the protein molecule for configurations 1 and 2. In
4. CONCLUSIONS We have performed simulations of the binding of the OC-17 protein to a calcite {10.4} surface. Our simulations demonstrate that the water structure at the surface is crucial to controlling the protein binding. Due to the strong interactions between the water and calcite, the most energetically favorable protein binding minimizes the displacement of water from the surface. Therefore, the configuration with the lowest binding energy actually has the fewest residues in contact with the surface as this displaces the least water molecules with minimal disruption of the ordered water. Arginine residues are the major binding residues from the protein. The long chains of the R group are able to penetrate the water layer relatively easily and achieve a strong interaction with both the carbonate-oxygen and calcium ions at the surface through the amine functional groups. The protein structure remains relatively unchanged when it binds to the surface as demonstrated by rmsd and hydrogen-bonding analysis, which implies structural rigidity is an important feature of this protein. ’ AUTHOR INFORMATION Corresponding Author
*Phone: þ44 (0)114 222 5965. Fax: þ44 (0)114 222 5943. E-mail: c.l.freeman@sheffield.ac.uk.
’ ACKNOWLEDGMENT The authors thank EPSRC Grants GR/S80103/01, GR/ S80127/01, and EP/IOO1514/1 for funding and computing facilities on HECToR funded under EPSRC Grant EP/ F055471/1. They also thank Dr. Illian Todorov (Daresbury Laboratories) and Dr. Martyn Foster (Cray) for their assistance with porting DLPOLY onto HECToR and optimizing the code for this machine. ’ REFERENCES (1) Arias, J.; Fernandez, M.; Laraia, V.; Janicki, J.; Heuer, A.; Caplan, A. Mater. Res. Soc. Symp. Proc. 1991, 218, 193–201. (2) Chien, Y.-C.; Hincke, M.; Vail, H.; Mckee, M. J. Struct. Biol. 2008, 163, 84–89. (3) Drickamer, K. Curr. Opin. Struct. Biol. 1999, 9, 585–590. (4) Hincke, M.; Tsang, C.; Courtney, M.; Hill, V.; Narbaitz, R. Calcif. Tissue Int. 1995, 56, 578–583. (5) Mann, K.; Siedler, F. Biochem. Mol. Biol. Int. 1999, 47, 997–1007. 8182
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