Molecular Simulation To Characterize the Adsorption Behavior of a

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Langmuir 2005, 21, 1103-1117

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Molecular Simulation To Characterize the Adsorption Behavior of a Fibrinogen γ-Chain Fragment Madhuri Agashe,† Vivek Raut,† Steven J. Stuart,‡ and Robert A. Latour*,† Department of Bioengineering and Department of Chemistry, 501 Rhodes Engineering Research Center, Clemson University, Clemson, South Carolina 29634 Received August 30, 2004. In Final Form: November 2, 2004 Implants invoke inflammatory responses from the body even if they are chemically inert and nontoxic. It has been shown that a crucial precedent event in the inflammatory process is the spontaneous adsorption of fibrinogen (Fg) on implant surfaces, which is typically followed by the presence of phagocytic cells. Interactions between the phagocyte integrin Mac-1 and two short sequences within the fibrinogen γ chain, γ190-202 and γ377-395, may partially explain phagocyte accumulation at implant surfaces. These two sequences are believed to form an integrin binding site that is inaccessible when Fg is in its soluble-state structure but then becomes available for Mac-1 binding following adsorption, presumably due to adsorptioninduced conformational changes. The objective of this research was to theoretically investigate this possibility by using molecular dynamics simulations of the γ-chain fragment of Fg over self-assembled monolayer (SAM) surfaces presenting different types of surface chemistry. The GROMACS software package was used to carry out the molecular simulations in an explicit solvation environment over a 5 ns period of time. The adsorption of the γ-chain of fibrinogen was simulated on five types of SAM surfaces. The simulations showed that this protein fragment exhibits distinctly different adsorption behavior on the different surface chemistries. Although the trajectory files showed that significant conformational changes did not occur in this protein fragment over the time frame of the simulations, it was predicted that the protein does undergo substantial rotational and translational motions over the surface prior to stabilizing in various preferred orientations. This suggests that the kinetics of surface-induced conformational changes in a protein’s structure might be much slower than the kinetics of orientational changes, thus enabling the principles of adsorption thermodynamics to be used to guide adsorbing proteins into defined orientations on surfaces before large conformational changes can occur. This finding may be very important for biomaterial surface design as it suggests that surface chemistry can potentially be used to directly control the orientation of adsorbing proteins in a manner that either presents or hides specific bioactive sites contained within a protein’s structure, thereby providing a mechanism to control cellular responses to the adsorbed protein layer.

Introduction Protein adsorption, defined as a noncovalent bonding of a protein to a surface, is important in many applications in biotechnology, and in particular, it plays a key role in the biocompatibility of medical implants. Numerous studies in the past have demonstrated qualitatively the complexities of protein adsorption and the influence of protein adsorption on cellular response.1-3 Surfaces of most commonly used biomaterials spontaneously adsorb a layer of host proteins within seconds after tissue or blood contact.4,5 The blood proteins that adsorb most abundantly are albumin, fibrinogen, and immunoglobulin G (IgG). Of these, fibrinogen is of special interest because of the important role that it plays in the thrombin-mediated blood coagulation cascade.6,7 Studies have also shown that * To whom correspondence may be addressed. E-mail: LatourR@ clemson.edu. † Department of Bioengineering. ‡ Department of Chemistry. (1) Dobkowski, J.; Kolos, R.; Kaminski, J. J. Biomed. Mater. Res. 1999, 47, 234-242. (2) Kazuhiro, N.; Takaharu, S.; Koreyoshi, I. J. Biosci. Bioeng. 2001, 91, 233-244. (3) Hlady, V.; Buijs, J. Curr. Opin. Biotechnol. 1996, 7, 72-77. (4) Baier, R. E.; Dutton, R. C. J. Biomed. Mater. Res. 1969, 3, 191206. (5) Sevastianov, V. I. Crit. Rev. Biocompat. 1988, 4, 109-154. (6) Yee, V. C.; Pratt, K. P.; Cote, H. C.; Trong, I. L.; Chung, D. W.; Davie, E. W.; Stenkamp, R. E.; Teller; D. C Structure 1997, 5, 125-138. (7) Helene, C. F.; Lord, S. T.; Pratt, K. P. Blood 1998, 92, 2195-2212.

spontaneous adsorption of fibrinogen is critical to the pathogenesis of the biomaterial-mediated inflammatory response.8-12 Thus, fibrinogen plays a strategic role not only in thrombus formation but also in eliciting inflammatory responses; both are key issues for the design of biomaterials. Previous investigations carried out to define the molecular determinants of fibrinogen-mediated acute inflammatory responses have revealed that the proinflammatory activity resides within the D fragment of fibrinogen.12 In particular, interactions between phagocyte integrin Mac-1 (CD11b/CD18) and two short sequences within the fibrinogen D domain, γ190-202 and γ377395 (Figure 1), partially explain phagocyte accumulation on implant surfaces. Investigations of the events involved in the surface-mediated conversion of fibrinogen to a proinflammatory state have indicated that the fibrinogen adsorption to biomaterial surfaces exposes the γ190202(P1) and γ377-395 (P2) epitopes, which are normally occult in the soluble state of fibrinogen. The extent of biomaterial-mediated exposure of P1 and P2 has been shown to be directly related to the severity of inflammatory responses when tested with a panel of different bioma(8) Tang, L.; Eaton, J. W. J. Exp. Med. 1993, 178, 2147-2156. (9) Tang, L.; Eaton, J. W. Mol. Med. 1999, 5, 351-358. (10) Hu, W. J.; Eaton, J. W.; Tang, L. Blood 2001, 98, 1231-1238. (11) Tang, L. J. Biomater. Sci., Polym. Ed. 1998, 9 (12), 1257-1266. (12) Tang, L.; Ugarova, T. P.; Plow, E. F.; Eaton, J. W. J. Clin. Invest. 1996, 97, 1329-1334.

10.1021/la0478346 CCC: $30.25 © 2005 American Chemical Society Published on Web 12/31/2004

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Figure 1. Spatial positioning of γ190-202 and γ377-395 in the three-dimensional structure of the fibrinogen γ-module with the γ190-202 and γ380-390 regions colored in red and blue, respectively.13 (A) The ribbon diagram of the fibrinogen γ-module (γ144402) based upon its crystal structure.6 (B) Space-filled model of the γ-module with exposed P1 and P2 residues highlighted. (Adapted from ref 13, with permission).

terials.10 Thrombin-mediated conversion of fibrinogen to fibrin also exposes these same epitopes. Thus phagocytes may recognize fibrinogen adherent to medical implants as fibrin and respond by launching a series of inflammatory and wound-healing responses normally initiated by fibrin clot formation. Although previous studies have effectively identified macrophage recognition of the P1, P2 epitopes of fibrinogen as an initiating factor for inflammatory responses against biomaterials, the actual molecular mechanisms leading to the exposure of these epitopes are still unclear. One hypothesis is that interactions between the adsorbed fibrinogen and the implant surface induce conformational changes to occur in the protein, causing the exposure of the aforementioned P1 and P2 epitopes.10 If the actual molecular mechanisms responsible for this behavior could be understood and predicted as a function of the chemistry of an adsorbent surface, then it is possible that a surface could be designed to adsorb fibrinogen in a manner to prevent the P1, P2 epitopes from being exposed and thus minimize the severity of the inflammatory response against implanted biomaterials. While much has been learned from fibrinogen adsorption from experimental studies, these studies have been limited in terms of their ability to provide details of the interactions taking place at the molecular level and this level of understanding is necessary if the conformational behavior following adsorption is to be controlled and used to direct biological response. On the other hand, molecular simulation presents one of the most direct approaches to theoretically investigate interactions at the molecular level and address the effect of surface chemistry on the adsorption behavior of proteins.14,15 Because of the size of the systems that need to be modeled, such simulation work requires the use of empirical force field methods.16 Advances in computational power and techniques in molecular simulations over the past several decades have led to the development of a variety of force fields, several of which have been specifically developed to simulate protein behavior in aqueous solution, e.g., AMBER, CHARMM, GROMACS, and OPLS.17-20 (13) Ugarova, T. P.; Solovjov, D. A.; Zhang, L.; Loukinov, D. I.; Yee, V. C.; Medved, L. V.; Plow, E. F. J. Biol. Chem. 1998, 273, 2251922527. (14) Raffaini, G.; Ganazzoli, F. Langmuir 2003, 19, 3403-3412. (15) Cristina, M.; Martins, L.; Ratner, B. D.; Barbosa, M. A. J. Biomed. Mater. Res. 2003, 67A, 158-171. (16) Leach, A. R. In Molecular Modelling. Principles and Applications; Pearson Education Ltd.: Harlow, U.K., 1996; pp 131-206. (17) Brooks, B. R.; Bruccoleri, R. E.; Olafson, B. D.; States, D. J.; Swaminathan, S.; Karplus, M. J. Comput. Chem. 1983, 4, 187-217.

The objective of this study was to use a protein force field to investigate the adsorption behavior of a 30 kDa γ chain fragment of fibrinogen as a function of surface chemistry presented by an alkanethiol self-assembled monolayer surface. Molecular dynamics (MD) simulations were carried out with explicit solvation over 5 ns of time using the GROMACS molecular simulation program to investigate the adsorption behavior of the γ chain of fibrinogen on five different surface chemistries: -CH3, -OH, -NH2, -COOH, and -(O-CH2-CH2)2-OH (oligoethylene glycol, OEG). Simulation results show that distinctly different adsorption behavior is exhibited for each type of surface chemistry, and specific molecular interactions that characterize the interaction of peptide residues with each type of surface are presented. Most importantly, the simulations predict that the protein fragment undergoes substantial rotational and translational motions over the surface prior to settling on a preferred orientation over the surface. This finding has potentially profound implications for protein adsorption in that it suggests that surface chemistry may be used to control protein orientation prior to inducing conformational changes in the protein structure. While much work remains to be done to validate a given protein force field for simulation of protein adsorption behavior, the present study serves to demonstrate how surface chemistry influences the adsorption patterns of a γ chain fragment of fibrinogen as predicted using the GROMACS molecular simulation program and force field. Materials and Methods Computational Environment. Calculations were performed on a 2.66 GHz Beowulf cluster computer system with GROMACS (v. 3.1.4) software.21,22 The GROMACS MD simulation package was selected for use in these studies because the GROMACS force field was specifically developed for the simulation of biomolecules, such as (18) MacKerell, A. D. J.; Brooks, B.; Brooks, C. L. I.; Nilsson, L.; Roux, B.; Won, Y.; Karplus, M. In Encyclopedia of Computational Chemistry; John Wiley & Sons: New York, 1998; Vol. 1 A-D, pp 271277. (19) Pitt, W. G.; Weaver, D. R. J. Colloid Interface Sci. 1997, 185, 258-264. (20) Lindahl, E.; Hess, B.; van der Spoel, D. J. Mol. Model. 2001, 7, 306-317. (21) Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R. Comput. Phys. Commun. 1995, 91, 43-56. (22) van der Spoel, D.; van Buuren, A. R.; Apol, E.; Meulenhoff, P. J.; Tielman, D. P.; Sijbers, A. L. T. M.; Hess, B.; Feenstra, K. A.; LIndahl, E.; van Druen, R.; Berendsen, H. J. C. GROMACS User Manual version 3.1.1; Nijenborgh 4, 9747 AG: Groningen, The Netherlands, 2002.

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Figure 2. Individual chains on the SAM surface with different functionalization: (A) CH3 terminated; (B) OH terminated; (C) COOH, COO- terminated; (D) NH2, NH3+ terminated; (E) trans OEG; (F) gauche OEG (torsional angles set as: C-O-C-C ) 70°, C-C-O-C ) 70° , O-C-C-O ) 60°).28,29

proteins, and it is freely available from the GROMACS homepage Internet site (www.gromacs.org) with accompanying program documentation and an e-mail-based user support group. The GROMACS MD program is also very fast with parallel computing capability and provides flexible tools for data analysis. Simulations were run on dedicated processors (two CPUs per simulation) with a calculation time of about 5-7 days per nanosecond of simulation for the selected protein-surface system. GROMACS program tools were used for both running the MD simulations and data analysis. The initial molecular models were prepared using Web Lab Viewer Pro and the Builder Module in InsightII 2000.1 (Accelrys, San Diego). VMD software23 was used for visualization of the trajectories generated by GROMACS. Molecular Models of Materials. The crystal structure of a 30 kDa C-terminus γ-chain fragment of fibrinogen (γFg) was obtained from the Protein Data Bank (PDB ID# 1FID)6 and further processed in preparation for our simulations, which involved the removal of noncovalently bonded heterogeneous atoms (e.g., oxygen atoms from bound water molecules) and the addition of hydrogens to complete valence requirements of the crystal structure’s heavy atoms. In addition, because this is a protein fragment, the downloaded structure had an incomplete terminal residue (leucine, #402), which was also removed. In its final form, the γFg model had a net charge of -3 e. This protein model is particularly relevant for these studies because it contains only two disulfide cross-links between adjacent cysteine residues. Thus, its tertiary structure is predominantly stabilized by secondary bonding interactions, which the functional groups of an adsorbent surface will compete with to potentially induce protein unfolding and spreading on the surface, with possible exposure of the P1-P2 epitopes. Surfaces for γFg adsorption were modeled to represent alkanethiol self-assembled monolayers (SAMs) with varying surface chemical functionalities. These surfaces were derived from molecular models of S-(CH2)15-CH3 alkanethiol SAMs on a simulated gold (111) surface plane modeled by Latour and co-workers in previous studies investigating midchain peptide residue adsorption to SAM surfaces.24-27 To vary the surface chemistry, the terminal (23) Humphrey, W.; Dalke, A.; Schulten, K. J. Mol. Graphics 1996, 14, (1), 33-38. (24) Basalyga, D. M.; Latour, R. A. J. Biomed. Mater. Res. 2002, 64A, 120-130. (25) Latour, R. A.; Rini, C. J. J. Biomed. Mater. Res. 2002, 60, 564577. (26) Latour, R. A.; Hench, L. L. Biomaterials 2002, 23, 4633-4648. (27) Wilson, K.; Stuart, S. J.; Garcia, A.; Latour, R. A. J. Biomed. Mater. Res. 2004, 69A, 686-698.

Table 1. Characteristic Functionalities of the SAM Surfaces functionality

terminal group (R)

charge state

hydrophobic neutral hydrophilic positively charged negatively charged nonadhesive control

CH3 OH NH2/NH3+ COOH/COOOEG

neutral (nonpolar) neutral (polar) neutral (polar)/+1 neutral (polar)/-1 neutral (polar)

Table 2. Predefined Atom Types Used To Define the New Atom Types Needed To Represent the SAM Surfaces in GROMACS atom name

mass (amu)

atom type

O OM OA N NT NL C C1 C2 C3 HO

15.9994 15.9994 15.9994 14.0067 14.0067 14.0067 12.011 12.011 12.011 12.011 1.008

CARBONYL OXYGEN (CdO) CARBOXYL OXYGEN (COs) HYDROXYL OXYGEN (OH) PEPTIDE NITROGEN (N OR NH) TERMINAL NITROGEN (NH2) TERMINAL NITROGEN (NH3) BARE CARBON (PEPTIDE,CdO,CsN) ALIPHATIC CH-GROUP ALIPHATIC CH2-GROUP ALIPHATIC CH3-GROUP HYDROXYL HYDROGEN

methyl groups of the alkanethiol molecules were replaced by other selected functional groups, namely, -OH, -NH2/ NH3+, -COOH/COO-, or -(O-CH2-CH2)2-OH (OEG). The lower portion of the alkanethiol molecules was then truncated so as to provide an overall SAM surface layer that was about 10 Å thick. In this way surfaces with five different surface chemistries were generated that had the chemical characteristics as presented in Table 1. Individual chains that were used to form the functional unit of each SAM surface are shown in Figure 2. Each chain had a structure CH3-(CH2) 8-R, where R represents the specific terminal function group shown in Table 1. To represent these surfaces in GROMACS, new residue types corresponding to the individual chains of each type of SAM had to first be defined in the GROMACS residue topology files (.rtf files) using predefined atom types in the atom type parameter (.atp) file. Table 2 lists the predefined atom types that were used for defining these new residue types. All hydrogens connected to alkane chains were included with the parent carbons as united atoms, and only hydrogens connected to the polar or charged functional groups, i.e., in (OH, NH2, NH3+, COOH, and OEG), were modeled explicitly, consistent with the principles behind the GROMACS potential and the guidelines provided in the GROMACS documentation.22 Starting configurations of the OEG-terminated residue chains were

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Figure 3. Illustration of the amine-terminated alkanethiol SAM surface constructed using a mix of 95% NH2 and 5% NH3+ terminated carbon chains. Color code: white ) hydrogen; green ) carbon; blue ) nitrogen. Total of 525 chains. Dimensions: 103 Å × 95 Å × 12 Å.

represented in both a trans conformation and a gauche (helical) conformation as shown in structures E and F of Figure 2, respectively, for reasons explained below. The trans structure represents the lowest energy configuration of the OEG chain in a vacuum as represented by the GROMACS force field equation, while evidence suggests that helical conformations may actually be more stable in aqueous solution.28,29 To create charged surfaces with set pK values, two types of residues were created. For the positively charged surface, one residue had an NH3+ terminal group with a charge of +1 e and the other had a NH2 terminal group that was neutral. Similarly, to create the negatively charged SAM, one residue with a COO- end group and a charge of -1 e was created, and another was created with an uncharged COOH end group. Charged surfaces were then constructed using a mix of these two residues such that 1 out of every 20 chains had a charged terminal group. This protonation/deprotonation ratio was selected based on work by Creager et al.30 and represents surface pK values of 8.7 and 6.1 for the COOH and NH2 surfaces, respectively. Partial charges for the SAM residues, except for the (-O-CH2-CH2-) segment of OEG, were based on amino acid definitions with similar side-chain functional groups, while the partial charges for the (-O-CH2-CH2-) segment of OEG, which were not available in GROMACS, were obtained from the AMBER force field.31 AMBER was selected as an appropriate force field for this designation because it is a class I force field like GROMACS with similar functional form and parametrization.32 Table 3 provides the parameters for the terminal groups of the individual SAM residues. The single chains thus obtained were iteratively expanded as shown in Figure 3 to create SAM surfaces with sufficiently large surface area to model the adsorption behavior of the γFg protein fragment. We anticipated that the OEG chains initially positioned in the trans configuration would transition to the helical configuration during the simulation as the OEG groups became solvated with water. In preliminary studies, however, this transition was not observed to occur; rather the OEG chains maintained their trans configuration throughout the simulations with only relatively moderate torsional angle fluctuations about this state. A separate set of simulations was then conducted with the OEG chains initially positioned in the helical conformation. In this (28) Wang, R. L. C.; Kreuzer, H.; Grunze, M.; Pertsin, A. J. Phys. Chem. Chem. Phys. 2002, 2, 1721-1727. (29) Rigby, D.; Sun, H.; Eichinger, B. E. Polym. Int. 1997, 44, 311330. (30) Creager, S. E.; Clarke, J. Langmuir 1994, 10, 3675-3683. (31) Weiner, S. J.; Kollman, P. A.; Case, D. A.; Singh, U. C.; Ghio, C.; Alagona, G.; Profeta, J. S.; Weiner, P. J. Am. Chem. Soc. 1984, 106, 765-784. (32) MacKerell, A. D. J. In Encyclopedia of Computational Chemistry; Schleyer, P. v. R., Ed.; John Wiley & Sons: New York, 1998; Vol. 3 M-P, pp 2191-2200.

Table 3. Details of Terminal Groups of SAMs residue name

partial charges based on

COH

serine SER

COM

aspartic acid (unprotonated) ASP aspartic acid (protonated) ASPH

COA

CN3

lysine (protonated) LYSH

CN2

lysine (unprotonated) LYS serine amber force field

OEG

atom name

atom type

charge on atom

charge group

OA HO C2 O O1 C1 O HO O1 C1 N H1 H2 H3 C2 N H1 H2 C9 O1 C10 C11 O2 C12 C13 O3 H1

OA HO C2 OM OM C2 OA HO O C2 NL H H H C2 NT H H C2 OM C2 C2 OM C2 C2 OA HO

-0.548 0.398 0.150 -0.635 -0.635 0.270 -0.548 0.398 -0.380 0.530 0.129 0.248 0.248 0.248 0.127 -0.830 0.415 0.415 0.200 -0.400 0.200 0.200 -0.400 0.200 0.263 -0.566 0.303

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 8 8 9 9 9 10 10 10

case, the OEG chains were observed to transition back to the trans conformation within about 100 ps, with the trans conformation then maintained for the rest of the simulation. Protein adsorption behavior was unexpectedly predicted to occur differently for these two different starting OEG conformations, and results are presented for both of these starting OEG conformations to demonstrate these differences in the simulated behavior. This behavior illustrates one of the limitations of the use of a protein force field to represent a system that it was not previously parametrized to represent (i.e., protein adsorption to an OEG-functionalized SAM surface). An alternative to this would have been to combine force field potentials that were specifically developed to represent alkanethiol SAM surfaces33,34 and OEG functional groups35,36 with the GROMACS potential then still used for the protein in solution in a single simulation. However, unless specifically balanced to function together, the use of different force field potentials to represent different phases in the same simulation can also be expected to have problems in accurately representing molecular (33) Hautman, J.; Bareman, J. P.; Mar, W.; Klein, M. L. J. Chem. Soc., Faraday Trans. 1991, 87 (13), 2031-2037. (34) Mar, W.; Klein, M. L. Langmuir 1994, 10, 188-196. (35) Smith, G. D.; Jaffe, R. L.; Yoon, D. Y. J. Phys. Chem. 1993, 97, 12752. (36) Smith, G. D.; Borodin, O.; Bedrov, D. J. Comput. Chem. 2002, 23, 1480-1488.

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Figure 4. Schematic representation of the fibrinogen molecule.6 The R, β, and γ chains are indicated, as well as their N and C termini. (Adapted from ref 6, with permission).

behavior, especially at the interface between the separate phases. This represents an inherent problem with empirical force field methods. Given this situation, we elected to simulate protein adsorption behavior using a single force field potential with minimal modifications for both the protein solution and the adsorbent surface phases and to evaluate the results to identify possible inaccuracies in the simulated molecular behavior. These studies thus represent first steps toward the eventual development of molecular simulation methods that will enable protein adsorption behavior to be accurately simulated for a wide range of functionalized surfaces. Computational Methods. Orientation of Protein on Surface. The initial orientation of the γ chain of Fg on the surface was determined in a qualitative manner by considering how the γ chain fragment of Fg would likely be positioned on the surface when part of an adsorbed whole Fg protein. This was decided based on the molecular structure of chicken Fg (PDB ID 1EI3),37 which was manually positioned on a surface plane in a manner that was judged to maximize surface contact between both the entire Fg macromolecule and the γ chain segment at one end of the protein. Figure 4 illustrates the location of the γ chain segment with respect to the entire Fg molecule.6 Simulation Details. The GROMACS all-hydrogen force field, ffgm2,22 and the SPC water model22,38 were used for all simulations. The assembly of the protein and surface was modeled with periodic boundary conditions with the following cell size given as X × Y × Z, where the X and Z axes are parallel to the surface plane and Y is normal to the surface plane: for the methyl, carboxyl, hydroxyl, and amine surfaces, 107 Å × 80 Å × 105 Å; for the OEG surfaces, 107 Å × 90 Å × 105 Å; for the γ chain fragment of Fg alone in saline without the surface, 55 Å × 55 Å × 65 Å. To represent a physiological saline solution, sodium (Na+) and choride (Cl-) ions were added to the system using the genion tool in GROMACS to approximate the salt concentration of blood plasma, which is about 150 mM.39 Figure 5 shows the entire assembly of γFg and the SAM surface in the periodic unit cell with explicitly represented solvent. Once constructed, the solvated as(37) Yang; Z.; Mochalkin; I.; Veerapandian; L.; Riley; M.; Doolittle; R. F Proc. Natl. Acad. Sci. U.S.A. 2000, 97, 3907-3912. (38) Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; Hermans, J. In Intermolecular Forces; Pullman, B., Ed.; Reidel: Dordrecht, 1981; pp 331-342. (39) West, J. B. In Best and Taylor’s Physiological Basis of Medical Practice, 11th ed.; Williams & Wilkins: Baltimore, MD, 1985; pp 441442.

sembly was subjected to energy minimization for 1000 steps using the steepest descent integrator to prepare the system for subsequent MD simulations. No constraints were used for this equilibration. Following equilibration, MD simulations were performed using the leapfrog integrator. All bond lengths were constrained during the MD simulations, which allowed for a 2.0 fs time step to be used.40 The simulations were performed in the NVT ensemble at a temperature of 300 K using a Berendsen thermostat with the update time set at 0.1 ps. For the calculation of nonbonded interactions, cutoffs of rvdW ) 1.0 nm for the van der Waals interactions and rCoulomb ) 1.7 nm for the electrostatic interactions were used. Periodic boundary conditions were used in each direction. All atoms of the SAM surface except for the terminal functional groups, i.e., CH3, OH, NH2/ NH3+, COOH /COO-, and OEG, were rigidly constrained during the simulations in order to maintain the structure of the SAM surface and minimize CPU time. The van der Waals interactions with these constrained atoms, however, were still included. In all, six 5.0 ns simulations were run: five γFg-SAM models with the protein and a functionalized SAM surface and one system that served as a control with just γFg alone in solvent without the presence of a SAM surface. The trans model was used for the 5.0 ns simulation of the OEG SAM surface. In addition, a shorter 1.0 ns simulation was carried out for γFg over the gauche OEG surface for comparison with the trans OEG SAM surface. Data Analysis Techniques. Various tools available in the GROMACS program suite were used for data analysis. The trajectories were analyzed for structural changes in the protein by looking at the root-mean-square deviation (RMSD) of the protein structure compared to the energyminimized crystal structure and the change in solvent accessible surface area (SAS) of the protein. The translational and rotational motions of the protein over the surface were also analyzed by (1) tracking the vertical surface separation distance (SSD) between the center of mass (COM) of the protein and the COM of the surface; (2) tracking the planar movement of the COM of the protein parallel to the surface; and (3) tracking the rotational motions of the protein over the surface. These analyses were accomplished as follows. RMSD of the Protein. These plots were obtained using the “g_rms” tool in GROMACS.22,41 This command com(40) Kandt, C.; Chlitter, J.; Gerwert, K. Biophys. J. 2004, 86, 705717. (41) Maiorov, V. N.; Crippen, G. M. Proteins 1995, 22, 273-283.

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Figure 5. Illustration of γFg on the amine-terminated SAM. The system is solvated with SPC type water molecules with Na+ and Cl- ions added to represent a 150 mM saline solution.

putes the RMSD of a structure by comparing its atom coordinates with a specified reference structure. Here, the reference structure was the starting energy-minimized structure of γFg prior to beginning the MD simulations. RMSD values were calculated over the course of the simulation to characterize the change in protein structure over time or the opening of protein folds to expose previously buried residues. In this study, all atoms of the protein, including the hydrogens, were used for computing the RMSD. Change in Solvent Accessible Surface Area. “g_sas” is a tool available in GROMACS (v. 3.2) to calculate the change in solvent accessible surface area.42 This command computes the hydrophobic, hydrophilic, and total solvent accessible surface areas (SAS) of a given solute as if it were represented alone in bulk solvent. Thus a decrease in SAS would not represent contact between the protein and surface with the subsequent exclusion of water but rather a compaction of the protein’s structure with a reduction in its surface area. An increase in SAS would represent the unfolding of the protein to expose previously buried residues. Surface Separation Distance (SSD). The g_dist tool in GROMACS was used to track the vertical distance between the COM of the protein and the COM of the SAM surface over the period of 5 ns relative to the protein’s initial position over the surface. Positive values of SSD thus indicate that γFg’s COM translated further away from the surface compared to its initial position, while negative values of SSD indicate translation closer to the surface plane. Each simulation was initiated with the COM of the protein 25 Å away from the COM of the surface, which provided about a 7 Å solvent-filled gap between the protein and the surface plane as can be seen in Figure 5. Tracking Planar Movement. To track the planar motion of γFg over the SAM surface, the coordinates of the COM of the protein, (x, y, z), were first extracted from the trajectory file from the MD simulation. The net displacement of the protein in the surface plane was then calculated as r ) (dx2 + dz2)1/2, where dx ) xt - x0 and dz ) zt - z0, where t indicates time and x0, y0, and z0 (42) Eisenberg, D.; McLachlan, A. D. Nature 1986, 319, 199-203.

represent the initial position of the protein, with x and z being orthogonal axes parallel to the surface plane. This parameter thus provides an indication of the translational motion of the protein parallel to the surface. Tracking Rotational Motion of γFg. To track the rotational motion of the protein over the surface, three Euler angles, θ, φ, and ψ,43 were defined that describe the angular orientation of γFg with respect to the position of the surface plane. These angles, which are illustrated in Figure 6, specify the rotation of the protein’s internal local coordinate system (x, y, z) relative to the global coordinate system (X, Y, Z), with X and Z being parallel to the SAM surface plane and Y being normal to the surface. The angle φ represents the rotation of the protein about the Y axis (Figure 6A). This rotates the x and z axes in the X-Z plane to then define the intermediate position of the local coordinate axes as x′ and z′. The angle θ represents the angle of rotation of the protein about the z′ axis (Figure 6B). This then changes the orientation of y to y′ and x′ to x′′. Finally, ψ represents the angle of rotation about the y′ axis, which rotates the x′′ and z′ axes in the x′′-z′ plane to give the local axes their final orientations given by x′′′, y′, and z′′ (Figure 6C). To define the local coordinate system for the protein, two mutually perpendicular vectors, B h and C h , were defined to represent the rotated local y′ and z′′ axes of the protein. The coordinates of the COM (x1, y1, z1) and two other selected atoms (x2, y2, z2) and (x3, y3, z3) near the protein’s outer surface were used to define these mutually perpendicular vectors as shown in Figure 6D. The coordinates of these atoms were extracted from the MD trajectory file in order to calculate θ, φ, and ψ. Accordingly, vectors B h and C h were defined as

B h ) (x2 - x1)ıˆ + (y2 - y1)jˆ + (z2 - z1)kˆ C h ) (x3 - x1)ıˆ + (y3 - y1)jˆ + (z3 - z1)kˆ (43) Goldstein, H.; Poole, C. P.; Safko, J. L. In Classical Mechanics, 2nd ed.; Addison-Wesley Publ. Co.: San Francisco, CA, 2002; pp 150154.

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Figure 6. (A-C) Depiction of the three Euler angles (θ, φ, and ψ) used to track the rotational motion of the protein on the surface (adapted from Goldstein).43 (D) Illustration of the COM of γFg and two atoms located in the highlighted residues near the surface of the protein. These atoms were selected to describe two mutually perpendicular vectors originating at the COM of the protein, which were then used to define the orientation of the local coordinate system of the protein with respect to the global coordinate system defined by the position of the SAM surface.

where ıˆ, ˆj, and kˆ represent unit vectors in the local x, y, z system, respectively. Simple trigonometric formulas then yield the following relationships to calculate θ, φ, and ψ:

[

θ ) -cos-1

2

2 1/2

((x2 - x1) + (y2 - y1) + (z2 - z1) )

[

|φ| ) cos-1

[

x2 - x1

]

((x2 - x1)2 + (z2 - z1)2)1/2

φ ) -|φ| if z2 - z1 > 0, |ψ| ) cos-1

]

y2 - y1 2

φ ) |φ| if z2 - z1 < 0

-(x3 - x1) sin φ + (z3 - z1) cos φ

]

((x3 - x1)2 + (y3 - y1)2 + (z3 - z1)2)1/2

ψ ) -|ψ| if y3 - y1 > 0,

ψ ) |ψ| if y3 - y1 < 0

It should be noted here that Euler angles are derived for rotations of rigid bodies. In this case, though, the protein is not a rigid body because it undergoes internal motion during the MD run. Such motions are sources of noise or inaccuracy for the calculation of “rigid” body motions. This noise is maximized when θ ) 0° and minimized when θ ) (90°. Accordingly, to minimize such effects, the initial position of the local coordinate system of the protein was defined to be oriented with respect to the global coordinate system such that φ ≈ -90°, θ ≈ -90°, and ψ ≈ 90°. On the basis of the conditions described above, simulations of each protein-surface system were run for a period of 5 ns, and the resulting conformational, translational, and rotational responses of the protein were analyzed. The RMSD and SAS were monitored to assess changes in

protein conformation, and X, Y, Z translations and θ, φ, and ψ rotations were monitored to assess the movement of the protein over the SAM surface. Results RMSD Analysis. The RMSD results are presented in Figure 7. Figure 7A shows the RMSD of γFg in just the saline solution without any surface to influence its behavior. The plot shows that an initial rapid change in RMSD occurred, reflecting the mobility of the residues on the protein’s surface. The RMSD stabilized at about 3 Å within about 3 ns of simulation time. The overall structure of the protein did not change during the simulation. The other systems with γFg over a SAM surface exhibited similar behavior to that of the control, thus reflecting similar effects. Relatively minimal further changes in structure occurred due to specific interactions between functional groups on the protein’s surface and the SAM surface, with the RMSD increasing to about 4 Å on most of the surfaces. It is unclear whether γFg actually reached a stable configuration on a given surface, or if RMSD would continue to increase with longer simulation times. SAS Analysis. Figure 8 presents the changes in solvent accessible surface area (SAS). No significant change is seen in the SAS for any of the systems. This indicates that none of the SAM surfaces caused the protein to unfold and/or spread out over the surface during the course of the simulation. These plots also indicate that the changes in RMSD values reflect only relative motion about a stable core protein structure as opposed to any substantial changes in the overall protein configuration. Adsorption Behavior on Charged SAMs. Translational Motion Analysis. Figure 9 shows the surface separation distance (SSD) between the COM of γFg and the COM of the two charged surfaces, relative to the

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Figure 7. RMSD values of γFg in saline solution (A), over amine-terminated SAM (B), over carboxyl-terminated SAM (C), over trans-OEG-terminated SAM (D), over methyl-terminated SAM (E), and over hydroxyl-terminated SAM (F).

Figure 8. Change in SAS of Fg fragment in saline solution (A), over amine-terminated SAM (B), over carboxyl-terminated SAM (C), over trans-OEG-terminated SAM (D), over methyl-terminated SAM (E), over hydroxyl-terminated SAM (F).

Figure 9. Surface separation distance (SSD) between the COM of γFg and the amine-terminated SAM surface (A) and the carboxyl-terminated SAM surface (B).

starting SSD. These SSD plots indicate that γFg was attracted toward each surface from its starting position. For the amine-terminated SAM, this was expected because the protein and surface are oppositely charged, which should provide a net electrostatic force of attraction between the protein and surface. But obviously electrostatic force is not the only contributing factor because the negatively charged carboxyl-terminated SAM attracted the protein as well. We looked carefully at the functional group interactions that occurred during the course of the simulation in attempts to identify the specific interactions responsible for the protein’s functional groups being

preferentially attracted to the surface compared to the water molecules for both of these systems. The types of functional group interactions observed to occur between the peptide residues and these SAM surfaces are shown in Figure 10. For the NH2/NH3+ SAM surface (Figure 10A), the predominant interaction holding the protein to the surface was not found to be the attraction of oppositely charged residues, as expected. Instead, the NH3+ groups from lysine and arginine residues on the protein’s surface interacted strongly with noncharged NH2 groups on the SAM surface to form three simultaneous hydrogen bonds that effectively tethered the protein to

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Figure 10. Snapshot of a typical molecular configuration from the MD simulations with lower case letters indicating the designated type of functional group interaction. (A) NH2/NH3+ SAM surface. Hydrogen bonding occurred between lysine (a) and arginine (b) and three neighboring NH2 groups of the SAM surface; electrostatic interactions occurred between the NH3+ SAM groups and carboxylate groups of the C-terminus (c), aspartic acid, or glutamic acid; and hydrophobic interactions occurred between hydrophobic residues (d) and subsurface CH2 groups of the SAM surface that were exposed when surface functional groups happened to separate. (B) COOH/COO- SAM surface. Electrostatic interactions occurred between COO- SAM groups and protonated amine functional groups of lysine (a) and arginine (b), and hydrophobic interactions were observed between hydrophobic residues (c) and subsurface CH2 groups of the SAM that were exposed when the surface functional groups happened to separate. The water molecules are not shown for clarity.

Figure 11. A schematic representation of the tricoordinated hydrogen bonding configuration observed to form between NH3+ groups from lysine and arginine with neighboring noncharged NH2 groups on the NH2/NH3+ SAM. These interactions were extremely stable and, once formed, persisted for the rest of the simulation, effectively tethering the protein to the surface.

the surface (see Figure 11). Electrostatic attraction between the positively charged NH3+ groups on the NH2/ NH3+ SAM and negatively charged residues of γFg, such as aspartic acid and glutamic acid, were also observed, but this type of bonding occurred with intervening water molecules and was not as stable as the hydrogen bonded complexes formed by the amine groups. Hydrophobic interactions were also observed between hydrophobic residues and the CH2 segments of the SAM surface that were exposed when amine surface groups occasionally separated during the simulation. Although it appears from the SSD plot that the protein moved away from the amine surface after 3 ns (Figure 9A), close inspection of the trajectory file shows that the hydrogen bonds between the amine groups of γFg and the SAM continued to tether

the protein to the surface during the entire simulation. It should be noted that the SSD represents the change in the distance between the COM of the protein and the COM of the SAM and not the distance between the residues on the protein’s surface and the SAM. Thus, as the protein rotates over the SAM surface, the COM of γFg may move slightly away from the surface while the residues on the protein’s surface remain close to the SAM due to the nonspherical shape of the protein. The interactions between the protein’s residues and the COOH/COO- SAM surface were different than the NH2/ NH3+ SAM surface (Figure 10B). The primary bonding events for this system were electrostatic interactions between positively charged residues such as arginine and lysine and the COO- groups of the carboxyl SAM. As with the amine surface, these electrostatic interactions always involved intervening water molecules, thus indicating that the charged groups maintained their hydration layers during these types of interactions. Stable hydrogen bonds were not formed between residue functional groups and the COOH/COO- SAM surface, indicating that water molecules were able to out-compete the residues’ functional groups for these types of interactions. As with the amine surface, interactions between hydrophobic residues and exposed CH2 groups below the COOH/COO- surface groups were also observed. The movement of the protein parallel to the plane of the surface was different for each of the charged surfaces (Figure 12). On the amine-terminated SAM (Figure 12A) the protein appeared to reach a metastable orientation following an initial translation of 5 Å and then exhibited an additional amount of translational motion over about 10 Å between 3 and 5 ns. On the carboxyl-terminated SAM, the COM of the protein exhibited about 10 Å of planar motion in the first 500 ps after which it remained at one fixed site. Rotational Motion Analysis. The rotational motions of γFg over the charged SAM surfaces are presented in Figure

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Figure 12. Planar motions of the COM of γFg over the surface plane of the amine-terminated SAM (A) and the surface plane of the carboxyl-terminated SAM (B).

Figure 13. Rotational motions of the COM of γFg over the amine-terminated SAM surface (A-C) and the carboxyl-terminated SAM surface (D-F).

Figure 14. Translational motions of the COM of γFg on the methyl-terminated SAM surface: (A) change in surface separation distance (SSD); (B) motion parallel to the surface plane.

13. As shown, the protein undergoes relatively large rotational motion over these SAM surfaces during the course of the 5.0 ns simulations, with θ, φ, and ψ varying by about 20-50°. From the MD trajectory files, it was apparent that the rotational motions of γFg reflected a rolling of the protein over the SAM surface, which also resulted in the translational motions of the COM of γFg as shown in Figure 12. Adsorption Behavior on the Hydrophobic MethylTerminated SAM. Translational Motion Analysis. Figure 14A shows the separation distance between the protein segment’s COM and the methyl-terminated SAM surface relative to the starting separation distance. The protein exhibited some initial movement away from the surface but then was attracted more closely to the surface, and after about 3 ns it attained a relatively stable orientation that was closer to the surface than the starting position. Figure 14B shows the planar motion of the protein on the methyl-terminated SAM with the COM of the protein translating over the surface, again primarily due to the rolling motion of the protein over the surface.

Rotational Motion Analysis. As previously noted, the RMSD plot shown in Figure 7E clearly indicates that γFg did not unfold on the methyl-terminated SAM during the 5 ns simulation as might be expected on a hydrophobic surface. Instead, an analysis of the trajectory file shows that during this time period γFg only rotated over on the surface, apparently toward some local minimum energy position while forming various hydrophobic interactions between the hydrophobic side chains of the protein’s residues and the terminal methyl end groups of the SAM surface, as illustrated in Figure 15. Initially, the protein residues close to the SAM surface were primarily hydrophilic in nature, and thus they retained their hydration layers instead of adsorbing to the hydrophobic surface groups. The protein then rolled over the surface until it oriented itself with several hydrophobic residues facing the surface. The position of the protein then stabilized with the side chains of hydrophobic residues, like alanine and valine, lying close to the surface forming stable hydrophobic interactions with CH3 terminal groups of the SAM surface (Figure 16). Only the hydrophobic portions

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Figure 15. Illustration of the γ chain rolling on the hydrophobic SAM: (A) the protein at 0.50 ns; (B) the protein at 1.25 ns. The degree of rotation can be judged qualitatively by the change in the position of the random loop of the C-terminus of γFg that extends out from the left side of the protein.

Figure 16. Trajectory snapshot of the protein segment over the methyl-terminated SAM surface with the hydrophobic side chains of various peptide residues forming hydrophobic interactions with the terminal CH3 groups of the SAM surface: (a) side chains of alanine residues; (b) CH2 groups of the side chain of a lysine residue. Note that hydrophilic functional groups of the protein residues remain hydrated and positioned away from surface.

Figure 17. Rotational motions of the COM of γFg over the methyl terminated SAM surface.

Figure 18. Translational motions of the COM of γFg on the hydroxyl-terminated SAM surface: (A) change in initial surface separation distance (SSD); (B) motion parallel to the surface plane.

of the side chains of the protein were observed to interact strongly with the methyl surface, whereas the hydrophilic functional groups of the protein residues remained hydrated and well separated from the surface. Plots for the rotational motions of γFg on the methyl SAM surface are presented in Figure 17, with the largest rotation represented by a θ rotation of 50°. As shown in Figure 17, γFg exhibited an initial rolling motion that was most pronounced between 0 and 1.25 ns. After this initial rolling, it attained a more stable orientation and began settling down on the SAM surface with relatively

little rotational motion exhibited for the rest of the simulation. Adsorption Behavior on Hydrophilic HydroxylTerminated SAMs. Translational Analysis. Figure 18A shows the separation distance between the protein segment’s COM and the hydroxyl-terminated SAM surface relative to the starting separation distance. As is apparent from this plot, the protein is not attracted to the surface, but slowly moves away from the SAM surface over the course of the 5 ns simulation. Detailed analysis of the trajectory indicates that while some initial hydrogen

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Figure 19. Trajectory snapshot of the protein segment over the hydroxyl-terminated SAM surface. Several layers of water molecules (not shown for clarity) are present between the protein and the surface due to the water molecules exhibiting stronger interactions with the OH functional groups of the SAM surface than the functional groups of the protein, thus inhibiting protein adsorption.

Figure 20. Rotational motions of the COM of γFg over the hydroxyl-terminated SAM surface.

bonding was evident between the side chains extending from the protein and the OH end groups of the SAM, it was not strong enough to keep the protein tethered to the surface, with the water molecules being successfully able to out-compete the γFg functional groups for these same hydrogen bonds. A snapshot from the trajectory file at about 3 ns is presented in Figure 19, which shows a relatively large separation between the residues at the periphery of γFg and the SAM surface. The planar movement over the hydroxyl surface is shown in Figure 18B. This behavior essentially represents random motion of the protein in water over the surface as the protein translates away from the surface during the first 2 ns, with the protein’s residues thus predominantly being in contact with water molecules with few direct interactions with the functional groups of the surface. Rotational Motion Analysis. The initial separation of γFg from the SAM surface and its subsequent drifting in the surrounding water were accompanied by substantial changes in θ, φ, and ψ, which are presented in Figure 20. From an inspection of the trajectory file, these motions appeared to occur in a random fashion, as would be expected, and is not directed toward some preferred orientation of γFg relative to the SAM surface. Adsorption Behavior on OEG-Terminated SAMs. Translational Analysis. γFg did not show any adsorption on the trans-OEG-functionalized surface. The surface separation distance and planar motion plots presented in Figure 21 show that the protein rapidly translated away from the surface. Analysis of the trajectory file showed that hydrogen bonds initially formed between the protein’s side chains and the terminal OH groups of the OEG surface, but these bonds were quickly displaced by water molecules. Initially, some unexpected hydrophobic interactions were also observed between hydrophobic side

chains of the protein and the -CH2-CH2- portions of the OEG surface. These interactions, however, were not sufficiently strong to hold the protein on the surface, and γFg translated away from the surface very rapidly. Surprisingly, very different behavior was observed for γFg over the gauche OEG. The surface separation distance plot, Figure 21C, shows that the protein moved closer to this surface from its starting position and actually adsorbed to the OEG SAM surface. Inspection of the functional group interactions responsible for this behavior revealed the development of relatively stable hydrophobic interactions between the hydrophobic side chains on the protein’s surface and the -CH2-CH2- portions of the OEG chain as depicted in Figure 22. In the gauche configuration, these interactions were strong enough to hold the protein close to the surface. The difference between the trans and gauche OEG surfaces is illustrated in Figure 23. When starting in the gauche configuration, the -CH2-CH2portion of the OEG is much more exposed to the solvent and this resulted in the formation of hydrophobic interactions with the hydrophobic functional groups of the protein’s surface residues early on in the simulation, which were apparently sufficiently stable to be maintained throughout the rest of the simulated time. The simulated adsorption of γFg to the gauche-OEG-terminated SAM is of concern because it is contrary to what has been observed experimentally.44 One explanation of this behavior is that specific molecular interaction mechanisms may be involved in the real system that were not represented in our simulations, such as complexation of the OEG functional groups with OH- ions in solution as proposed by Kreuzer et al.44 In our opinion, however, a more likely cause of the simulated behavior is that the force field parameters responsible for (44) Kreuzer, H.; Wang, R.; Grunze, M. J. Am. Chem. Soc. 2003, 125, 8384-8389.

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Figure 21. Translational motion of the COM of γFg on OEG terminated SAM surfaces: (A) surface separation distance (SSD) on the all-trans OEG SAM surface; (B) planar motion on the all-trans OEG SAM surface; (C) surface separation distance (SSD) on the all-gauche OEG SAM surface; (D) planar motion on the all-gauche OEG SAM surface.

Figure 22. Trajectory snapshot showing hydrophobic interactions between the hydrophobic side chains of the protein and the -CH2-CH2- segments of the gauche OEG SAM surface: (a) side chain of alanine residues; (b) CH2 groups of the side chain of a lysine residue. Note that the hydrophilic functional groups of the protein remain hydrated and positioned away from the surface.

Figure 23. Illustrations of the initial geometry of the trans (A) and the gauche (B) OEG molecular configurations as shown by top views of the SAM surfaces. Note that the helical conformation of the gauche OEG surface exposes the CH2-CH2 groups of the OEG molecules causing hydrophobic interactions to occur between the OEG and hydrophobic functional groups of the protein’s residues.

the OEG-water, peptide-water, and OEG-peptide interactions are not properly balanced. The fact that hydrophobic interactions were also observed in the simulations of the amine- and carboxyl-terminated SAM surfaces suggests that the GROMACS force field tends to overemphasize these types of adsorption mechanisms. This is not surprising since the GROMACS force field was not parametrized to represent this type of molecular system.

Rotational Motion Analysis. The rapid lift-off of the protein from the trans OEG surface and subsequent random motion in the solvent are accompanied by large orientational changes in γFg as indicated by the changes in θ, φ, and ψ, as shown in Figure 24. Although not shown, γFg did not exhibit any substantial rotation on the gauche OEG; however, the duration of this simulation was only 1 ns long.

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Figure 24. Rotational motions of the COM of γFg on the trans-OEG-terminated SAM surface.

Figure 25. (A) Schematic illustration of the adsorption free energy for a protein as a function of angular orientation, with barriers larger than kT. The arrows indicate that the protein will roll on the surface toward its nearest low-energy orientation. (B) Schematic illustration of adsorption energy for a surface designed to have only one minimum energy angular conformation for adsorbed proteins. All adsorbed proteins would then tend to position themselves on the surface in this single orientation.

Discussion As presented in the results, the simulations predict that the γFg protein segment is able to reorient itself on the surface over time, with surface chemistry substantially influencing how the various peptide residues interacted with each SAM surface. These types of interactions should not be specific to the particular protein segment that was modeled, but rather, because all proteins are essentially composed of the same set of the 20 naturally occurring amino acids, the predicted types of behavior on the different surfaces should be generally applicable to essentially all proteins. Differences can be expected, of course, due to the specific types of peptide residues and the secondary through quaternary structural organization that make up a given protein, with these differences influencing its final orientational and conformational state when adsorbed on a surface. It should be recognized that the 5 ns simulations presented here represent only the initial phase of this process and much longer simulation times must be performed to predict the final adsorbed state for a given protein-surface system. One of the primary reasons for being interested in the manner in which proteins adsorb to synthetic surfaces is to understand how the processes of adsorption may affect the bioactivity of adsorbed proteins. Adsorption can affect a protein’s bioactivity in two ways: either by adsorbing the protein such that its bioactive site(s) are either exposed or sterically hindered (i.e., due to adsorbed orientation) or by altering the protein’s structure such that the bioactive sites are either in the proper configuration for binding or not (i.e., due to adsorption-induced changes in conformation). In this research it has been observed that the protein does not show any significant level of structural change over the 5 ns simulation on any of the surfaces; however, the protein segment was found to undergo relatively large rotational and translational motions over this time period until establishing preferred orientations that were surface chemistry dependent. This behavior suggests that the

kinetics of orientational changes of a protein on a surface may be much faster than those of adsorption-induced conformational changes. If true, this has profound implications for surface design because it indicates that the orientation of proteins on a surface can be manipulated independently from protein conformational changes, thus providing two time-separable mechanisms to control adsorbed protein bioactivity by the manipulation of surface chemistry. While this is not a novel concept, the results of these molecular simulations support this type of behavior. If, as proposed above, the kinetics of protein orientational motions occur much faster than conformational changes, then the thermodynamic “landscape” of adsorption energy as a function of protein orientation becomes very important. Under this condition, adsorbed proteins will have the tendency to translate and rotate over the surface toward the nearest local energy wells following their initial adsorption to a surface, as illustrated in Figure 25A, with surface chemistry thus determining the final distribution of adsorbed protein orientations on the surface. Conformational changes may then occur, but only after this reorientational stage of the adsorption process has occurred. If a material surface could be designed so as to present to the adsorbing protein an energy landscape with only one thermodynamically significant minimum energy orientation, as depicted in Figure 25B, the orientation of adsorbed proteins theoretically could be controlled. Using surface chemistry in this manner to guide adsorbed proteins into desired orientations could thus potentially provide much better control over protein adsorption processes. Control over conformational changes in the protein could likewise then be achieved as a second stage in the overall adsorption process. If, on the other hand, the kinetics of conformational changes were much faster than the kinetics of reorientation, then proteins would tend to spread out over the surface in whatever orientation they happened to be in when they first

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adsorbed without time to reorient, and surface chemistry could have little effect on the orientation of adsorbed proteins. The former behavior, which is supported by this research, provides a much more desirable situation in terms of the potential to control the behavior of adsorbed proteins and their subsequent bioactivity by the rational design of surface chemistry. Conclusions This research was undertaken with the initial objective of examining the adsorption behavior γFg as a function of surface chemistry in order to investigate how adsorption may cause the P1-P2 epitopes to become exposed for possible integrin binding. The changes in RMSD and SAS over the 5 ns time scale of the simulations, however, were not found to be substantially different than those for the same protein fragment in bulk aqueous solution, thus indicating that the adsorption processes did not induce any significant levels of conformational change in the protein segment over this time scale. However, the results of these simulations do suggest that following initial adsorption, γFg undergoes substantial surface-induced rotational and translational motions until relatively stable low-energy adsorbed orientations are achieved. It must be emphasized, however, that the modeled protein segment only represents a portion of Fg and its adsorption behavior certainly can be expected to be substantially influenced by the other portions of the Fg structure, such as its R and β chains. As molecular simulation methods and computational power continue to improve over time, the entire Fg molecule should be able to be simulated and these effects should be able to be directly considered. Despite these current limitations, the observation that the kinetics that control changes in adsorbed protein orientation may be much faster than the kinetics that control adsorbed protein conformation is of great relevance because it suggests that surface chemistry may be used to control the orientation of adsorbed proteins indepen-

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dently from adsorbed conformation, thus providing two time-separable mechanisms to influence adsorbed protein bioactivity. These statements, however, must be tempered by the realization that none of the currently available force fields have been validated for the simulation of protein adsorption behavior to synthetic material surfaces. While protein adsorption simulations can and are being performed, the results of such simulations are usually so complex that they cannot be directly validated by experiment, except through very qualitative measures. Thus, at this time, the simulation results obtained from this research can only be presented as the molecular behavior predicted by the GROMACS force field. Further research is clearly needed. Most importantly, force fields must be validated for peptide-surface functional group interactions before molecular simulation can be confidently used as a predictive tool for materials surface design to control protein adsorption behavior. Our laboratory group is actively working to directly address these issues. While much development work is still needed, molecular simulations have enormous potential to complement experimental studies as we strive to understand the complexities of protein-surface interactions, and how to control them, so that the inherent bioactivity of proteins can be effectively harnessed for numerous applications in biotechnology, nanotechnology, and biomedical engineering. Acknowledgment. We thank NSF (award number EPS-0296165), the State of South Carolina, and Clemson University for providing the funding support for this project. We also thank the NSF Center for Advanced Engineering Fibers and Films (CAEFF), Ms. Corey Ferrier, and Mr. Tim Shelling at Clemson University for computer system support. LA0478346