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Density Functional Theory Study of the Interaction of ArginineGlycine-Aspartic Acid with Graphene, Defective Graphene, and Graphene Oxide Ya-nan Guo,† Xiong Lu,*,† Jie Weng,† and Yang Leng‡ †

Key Lab of Advanced Technologies of Materials, Ministry of Education, School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, P. R. China ‡ Department of Mechanical Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong, P. R. China S Supporting Information *

ABSTRACT: This study investigated the interaction between carbon nanostructures, including pristine graphene, defective graphene with monovacancy, graphene oxide (GO), and tripeptide arginine-glycineaspartic acid (RGD), by density functional theory. The results from the adsorption energy analysis show that the strongest adsorption is observed when RGD is parallel to graphene surfaces, in which graphene interacts with all three functional groups of RGD, including NH3+, COO−, and guanidine. The interaction of NH3+···π was stronger than that of guanidine−NH2···π and COO−···π. The vacancy improves the ability of graphene to attract RGD because of active dangling C atoms. GO has a stronger interaction with RGD than the pristine and defective graphene because of O-containing groups. The comparison of the GO model with the OH, epoxy, and mixed OH/epoxy groups reveals that various O-containing groups have distinguishing binding abilities with RGD. Water molecules strengthen the interactions between graphene and RGD, whereas they weaken the interaction between GO and RGD. The results provide useful guidance in designing optimal carbon nanomaterial surfaces with specific characteristics that could satisfy the demand for diverse applications of carbon nanomaterials in biomedical fields.

1. INTRODUCTION Graphene is a monolayer of carbon atoms that is tightly packed into a two-dimensional honeycomb lattice. It is under extensive exploration for applications in drug delivery,1 sensors,2 hydrogen storage, and solar cells3 because of its fascinating mechanical and electronic properties.4,5 Graphene oxide (GO) is a chemically modified graphene that has oxygen-containing functional groups on the graphene basal plane, such as hydroxyl, carbonyl, epoxy, and carboxyl groups.6 Thus, GO is easily dispersed in aqueous solution and is functionalized by various methods.7 Studies have paid considerable attention to the biomedical applications of graphene and GO. Wang et al.8 studied the biofunctionalization of graphene and the applications of functionalized graphene for living cell detection, drug delivery, and cell imaging. Nayak et al.9 investigated the influence of graphene on the behavior of human mesenchymal stem cells (HMSCs), and they found that graphene accelerates the specific differentiation of HMSCs into bone cells. Lee et al.10 studied stem cell growth and its differentiation on graphene and GO and demonstrated that different degrees of π−π stacking and electrostatic and hydrogen bonding induce stem cell differentiation toward different lineages. Sun et al.11 and Yang et al.12 investigated the loading and controlled release of doxorubicin on GO and revealed that GO has a high drug loading rate and has potential applications as drug carriers and biosensors. © 2013 American Chemical Society

Understanding the mechanism of the interaction between graphene and proteins/peptides is crucial in designing graphene-based biomedical materials and devices successfully. However, the interaction between biomolecules and graphene is still far from fully understood, which hinders the future development of graphene-based nanomaterials in biomedical applications. Molecular modeling is an effective way to study the interactions between biomolecules and carbon nanomaterial surfaces and provide information at the atomic and electronic level. Density functional theory (DFT) has been employed to investigate the interaction between various amino acids and graphene or carbon nanotube (CNT) surfaces. Rajesh et al.13 studied the interaction of phenylalanine, histidine, tyrosine, and tryptophan molecules with graphene and single-walled CNTs and revealed that π−π interaction is important in amino acid adsorption. Cazorla14 found that the binding of glycine, proline, and hydroxyproline to the graphene surface depends on amino acid orientation. Roman et al.15 demonstrated that there are strong interactions between the carboxyl group of glycine and CNT. The behavior of a large peptide on material surfaces is more complicated and might not be predicted from a single amino acid. Molecular dynamics simulation has been employed Received: October 12, 2012 Revised: January 20, 2013 Published: February 27, 2013 5708

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to study the interaction between peptide and carbon nanostructures. Chiu et al.16 studied the peptide/single-walled carbon nanotube (SWNT) complex, and they revealed that all hydrophobic residues of the peptide interact with the SWNT and are sequestered from water. Gao et al.17 simulated the translocation of DNA through CNTs, and they demonstrated that van der Waals and hydrophobic forces are the most important interactions in the insertion process of DNA into a CNT. Gianese et al.18 studied the adsorption of short polypeptides on carbon surfaces, and they found that isoleucine and tryptophan are the most strongly bound residues to carbon surfaces. Tomasio et al.19 investigated the interaction between peptides and CNTs, and they revealed that the aromatic sequence is essential in binding the peptide on CNTs. These simulation studies provide useful insight into the interactions between amino acids/peptides and carbon nanostructures, such as molecular configurations, dominating interaction sites, and binding types. Arginine-glycine-aspartic acid (RGD) is a tripeptide that widely exists in several extracellular matrix proteins. RGD is recognized as one of the effective peptide sequences that stimulates cell adhesion on material surfaces.20 Sawyer et al.21,22 reported that RGD-coated hydroxyapatite has better cell adherence than uncoated substrates. Zhang et al.23 demonstrated that the immobilization of RGD in amphiphilic block copolymers could enhance cell adhesion. The interaction of RGD with material surfaces has also been theoretically studied. Chen et al.24 investigated the adsorption mechanism of RGD on perfect and grooved rutile TiO2(110) surfaces, and they revealed that RGD binds to surface Ti atoms through carboxyl or carbonyl groups. Chen et al. also found out that RGD remains at the anchoring sites and undergoes limited hingebending motions. Zhang et al.25 studied the influence of aqueous environments and surface defects on RGD adsorption on TiO2 surfaces, and they reported that atomic step edges greatly affect the adsorption of RGD and that water limits the interaction between RGD and surfaces. These previous studies indicate that the interaction mode between RGD and material surfaces is quite complicated. However, a detailed understanding of RGD interaction with graphene-based materials at the molecular level remains unavailable. This study aims to investigate the adsorption mechanism of RGD on graphene-based nanostructures using DFT. The study includes four parts: (i) the adsorption of RGD on a pristine graphene sheet; (ii) the effects of vacancy on the adsorption of RGD; (iii) the adsorption of RGD on GO; (iv) the role of water in RGD adsorption on graphene and GO.

Figure 1. Molecular structure of tripeptide RGD. The main chain and side chain are defined by the arrows. Color code: C, gray; O, red; N, blue; H, white.

thickness of 25 Å was added to avoid interactions among adjacent cells (Figure 2). Five configurations of RGD were

Figure 2. Graphene surface model. Ten carbon atom rings are along the x-axis and twelve rings along the y-axis.

2. THEORETICAL METHODS 2.1. Model Building. RGD. The RGD sequence consists of the following three amino acid residues: arginine (Arg), glycine (Gly), and aspartic acid (Asp). Figure 1 shows the three functional groups in RGD, namely, the guanidine, amino, and carboxyl groups. These functional groups are the main active sites when RGD approaches graphene. The zwitterionic RGD model was utilized because the zwitterionic form has a strong interaction with carbon nanostructures.15,26 RGD on Pristine Graphene. The pristine graphene surface that consists of 240 carbon atoms was built with 10 carbon atom rings along the x-axis and 12 rings along the y-axis. The surface area is 24.600 Å × 25.565 Å. The C−C bond length in the carbon atom ring is 1.42 Å. A periodic boundary condition was employed to model this surface, and a vacuum slab with a

investigated on pristine graphene. The investigation considered the different functional groups of RGD as the active sites during adsorption. These configurations are described as follows (G stands for graphene): (a) G-RGD-lying model: Both the main chain and the side chain of RGD were parallel to the graphene surface (Figure 3a). (b) G-RGD-standing-GC model: RGD was perpendicular to the graphene surface with the guanidine and carboxyl group approaching the surface (Figure 3b). (c) G-RGD-standing-N model: RGD was perpendicular to the graphene surface with the amino group of RGD approaching the surface (Figure 3c). (d) G-RGD-main-chain model: The main chain of RGD was parallel to the graphene surface (Figure 3d). 5709

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Figure 3. Five configurations of RGD on graphene surfaces: (a) G-RGD-lying model; (b) G-RGD-standing-GC model; (c) G-RGD-standing-N model; (d) G-RGD-main-chain model; (e) G-RGD-side-chain model.

Figure 4. Top view of RGD on defective graphene surfaces with monovacancy: (a) V-NH3+-RGD model, NH3+ interacts with the vacancy; (b) Vguanidine-RGD model, guanidine interacts with the vacancy; (c) V-COO−-RGD model, COO− interacts with the vacancy. The vacancies are highlighted in ball-and-stick style.

molecules were placed near the functional groups of RGD. Therefore, they were able to interact effectively with RGD (Figure 6). The GO-RGD-lying-H2O model was built in the same manner (Figure 7). 2.2. Simulation Parameters. The simulation was performed by the DFT program Dmol3 in Materials Studio (Accelrys, San Diego, CA) wherein the physical wave functions were expanded in terms of numerical basis sets.27,28 The DNP double numerical basis set, which was comparable to the 631G** basis set, was utilized during the simulation. The core electrons were treated with DFT semicore pseudopotentials.29 The exchange-correlation energy was calculated using the Perdew−Burke−Ernzerhof generalized gradient approximation.30 Special point sampling integration over the Brillouin zone was employed using the Monkhorst−Pack schemes with a 2 × 2 × 1 k-point mesh.31 A Fermi smearing of 0.005 Ha (1 Ha = 27.211 eV) and a global orbital cutoff of 5.2 Å were employed. The convergence criteria for the geometric optimization and energy calculation were set as follows: (a) a self-consistent field tolerance of 1.0 × 10−6 Ha/atom; (b) an energy tolerance of 1.0 × 10−5 Ha/atom; (c) a maximum force tolerance of 0.002 Ha /Å; and (d) a maximum displacement tolerance of 0.005 Å. Dmol3 produces highly accurate results while keeping the computational cost fairly low. The optimized geometry of the pristine graphene surface shows a C−C bond length of 1.42 Å. This finding was in good agreement with previous reports.13,32,33 The bond lengths and bond angles of RGD from Dmol3 and from the experiments were thoroughly compared.34−39 These parameters were important to characterize the structure of RGD (Supporting Information, Figure 1 and Table 1). The reproducibility of previous reported data validates the applicability of Dmol3 to the present systems.

(e) G-RGD-side-chain model: The side chain of RGD was parallel to the graphene surface (Figure 3e). It should be pointed out that there are many other possible initial configurations of RGD on graphene surfaces. The present models only represent the typical interaction modes between RGD and graphene with reference to the roles of the functional groups of RGD in the adsorption process. Four carbon atoms in the corner of the cell were fixed, whereas RGD and other atoms on the surface were allowed to relax during the optimization process. RGD on Defective Graphene. The defective graphene with monovacancy was created by removing a single carbon atom from the surface of pristine graphene (Figure 4). The following three models were built to investigate the interactions between the vacancy and the three functional groups of RGD: V-NH3+RGD, V-guanidine-RGD, and V-COO−-RGD. In the V-NH3+RGD model, the vacancy was near the NH3+ of RGD (Figure 4a). The other two models were built in the same way (Figure 4b and 4c). RGD on GO. The GO model had three C8O2(OH)2 units that interacted with three functional groups in RGD. The C8O2(OH)2 units were uniformly distributed on the carbon sheet and formed an equilateral triangle (Figure 5a). Each C8O2(OH)2 unit contained two para-epoxy groups (para-O) at opposite sides of the carbon plane and two para-hydroxyl (paraOH) groups at the upside of the carbon plane (Figure 5b). RGD was parallel to the surface with the main functional groups approaching the C8O2(OH)2 units (Figure 5c). Thus, RGD could interact with both OH and epoxy groups. The model was named as GO-RGD-lying. Water Models. Ten water molecules were added into the GRGD-lying model to investigate the effect of a water environment on RGD adsorption on graphene surfaces. This model was named as the G-RGD-lying-H2O model. The water 5710

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Figure 5. (a) Top view: the GO model with three C8O2(OH)2 units on the carbon plane. The dotted lines show the equilateral triangle formed by three C8O2(OH)2 units. (b) Side view: a typical C8O2(OH)2 unit after geometric optimization, which contains two para-epoxy (para-O) groups at the opposite side of the carbon plane and two para-OH groups at the upside of the carbon plane. (c) Side view: RGD on GO surfaces with hydrogen bonds between RGD and O-containing groups of GO, as indicated by arrows.

2.3. Adsorption Energy. The adsorption energy (Eads), which indicates the intensity of interaction between RGD and graphene surfaces, was derived according to the following equation Eads = E RGD + GS − (E RGD + EGS)

alanine or L-leucine. Thus, RGD has more interaction sites with carbon surfaces. The results show that various RGD configurations on graphene surfaces lead to various adsorption energies. The configuration of the absorbent affects the interaction between the absorbent and material surfaces, which has been reported by previous studies.41,42 This is because the configuration determines different active sites or recognition groups of peptides/proteins that interact with materials and, therefore, guides specific reactions.43−46 Thus, understanding the interactions between the active functional groups of RGD and graphene surfaces is important. In the following sections, the G-RGD-lying model was used as the standard model to analyze RGD interaction with graphene. The G-RGD-lying model has the largest adsorption energy (−1.206 eV), which indicates that the parallelism of RGD to graphene surfaces is the most stable configuration. In the lying model, all three functional groups of RGD, including NH3+, COO−, and guanidine, interact with graphene. Figure 8a shows that NH3+ points to the hexagonal center and interacts with the π electron cloud of the graphene surface.40 The distance between the H atom of NH3+ and the hexagonal center is 2.649 Å (Figure 8b). Guanidine-NH2 has a similar orientation and has a distance of 3.044 Å (Figure 8c). The O atoms of COO− are oriented toward the two hexagonal centers, and the distances between the O atoms and the hexagonal centers are 3.360 and 3.205 Å, respectively (Figure 8d). These distances are comparable with those in previous reports on the interaction between amino acids and CNT/graphene. Rajarajeswari et al.47

(1)

where ERGB+GS, ERGD, and EGS represent the total energy of the adsorption system, the energy of RGD, and the energy of graphene, respectively. A negative Eads corresponds to a stable adsorption. A more negative Eads results in a more stable adsorption system. Table 1 shows the adsorption energies of various systems.

3. RESULTS AND DISCUSSION 3.1. RGD on Pristine Graphene. The adsorption energies (Eads) of five configurations are negative. This result indicates that the RGD adsorption on graphene surfaces is thermodynamically favored in all five cases (Table 1). Rajarajeswari et al.40 investigated the noncovalent interaction between alanine and CNT, and they revealed that the adsorption energy varies from −0.15 to −0.95 eV, depending on the configuration. Wu et al.41 studied L-leucine adsorption on graphene, and they showed that L-leucine is physically adsorbed on graphene with a low adsorption energy (−0.17 to −0.31 eV). In the present study, the adsorption energy of RGD on graphene (−1.206 eV) was slightly larger than that in previous studies. This could be ascribed to two reasons. First, RGD contains more functional groups. Second, it has a longer molecular chain than that of 5711

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investigated the adsorption mechanism of guanine and thymine on a single-walled CNT, and they revealed that the intermolecular distances between the CNT and the nucleic acid bases vary between 2.46 and 3.26 Å. Rajesh et al.13 studied the interaction of aromatic amino acids with graphene, and they concluded that the average interplanar distances are 3.21, 3.33, 3.34, and 3.50 Å for histidine, phenylalanine, tyrosine, and tryptophan, respectively. Ma et al.48 investigated the adsorption of a cysteine molecule on graphene, and they revealed that the G-cysteine distances are between 3.28 and 3.96 Å. The distances in the present study follow the noncovalent NH···π, OH···π interaction criteria, which suggests a weak interaction between RGD and graphene.49,50 The investigation of the electron density of the G-RGD-lying model revealed the interaction between RGD and graphene . Figure 9 shows the electron density isosurface mapped with the electron density difference of the G-RGD-lying model. The electron density difference reveals the change of electron density during adsorption, which is calculated by subtracting the electron density of the isolated RGD (ρRGD) and the graphene surface (ρGS) from the total electron density of the system (ρ(RGD+GS)), as follows Δρ = ρ(RGD + GS) − ρRGD − ρGS

(2)

The charge accumulation and charge depletion are represented by red and blue, respectively. On the graphene surface, a charge accumulation occurs in the area that interacts with the NH3+ and guanidine group, and a charge depletion occurs in the area that interacts with COO−. The electron density is low in the intermedial area of graphene and RGD, as shown in the slices passing through RGD and surface atoms. This finding reveals that the interactions of NH3+···π, guanidine−NH2···π, and COO−···π are weak noncovalent bonds (Figure 8b, 8c, and 8d). The results from the electron structure analysis on the basis of density of states (DOS) further indicate the nature of the interaction between the adsorbed RGD and graphene surfaces. The overlap of partial density of states (PDOS) shows the atom hybridization between the adsorbent and the substrate.51−54 Figure 10 shows that the PDOS of graphene and RGD overlap at −5.7, −4.2, and −0.2 eV relative to Ef. This finding reveals the weak hybridization between RGD and graphene. Naderi et al.55 employed a DFT-based method to study the interaction between glycine and graphene. However, this interaction was very weak. Ma et al.48,51 showed that cysteine is weakly adsorbed on the graphene surface. Rajesh et al.13 reported that the interaction between aromatic amino acids and graphene was noncovalent. Hu et al.56 demonstrated that noncovalent interactions exist between proteins and CNTs by experimental methods. In the present study, the results are in agreement with the previous studies, which further confirm the existence of weak interactions between RGD and graphene surfaces. One interesting finding is that the adsorption energy of the G-RGD-standing-N model (−0.833 eV) is larger than that of the G-RGD-standing-GC model (−0.465 eV). This finding could be attributed to the strong interaction of NH3+ with graphene. Figure 3c shows that only NH3+ interacts with graphene in the G-RGD-standing-N model. However, both guanidine and COO− interact with graphene in the G-RGDstanding-GC model (Figure 3b). Ganji26 investigated the adsorption of glycine, histidine, cysteine, and phenylalanine on CNT and showed that the interaction between −NH2 and the CNT is stronger than the interaction between −COOH and CNT. Rajarajeswari et al.40 revealed that the NH···π

Figure 6. G-RGD-lying-H2O model. (a) Top view: ten H2O molecules interact with the functional groups of RGD through intermolecular hydrogen bonds. (b) Side view: water molecules interact with graphene surfaces through H2O···π interaction. The distance unit is Å. The water molecules are presented in ball-and-stick style in (a) and stick style in (b). The hexagonal centers are marked by green balls.

Figure 7. GO-RGD-lying-H2O model. (a) Top view: C8O2(OH)2 units on GO surfaces are presented in line style; H2O molecules are presented in ball-and-stick style; RGD is presented in stick style. (b) Side view: C8O2(OH)2 units are presented in ball-and-stick style; H2O molecules are marked by yellow; the dotted lines refer to intermolecular hydrogen bonds.

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Table 1. Adsorption Energy of RGD on Pristine Graphene, Defective Graphene, and Graphene Oxide (Unit: eV) models

Etotal

Esurface

ERGD

Eads

G-RGD-lying G-RGD-standing-GC G-RGD-standing-N G-RGD-main-chain G-RGD-side-chain V-NH3+-RGD V-COO−-RGD V-guanidine-RGD GO-RGD-lying GO-OH-RGD GO-O-RGD G-RGD-lying-H2O GO-RGD-lying-H2O G-RGE-lying V-COO−-RGE GO-RGE-lying

−282716.533 −282716.486 −282716.983 −282717.059 −282717.589 −281673.217 −281672.486 −281672.922 −307347.548 −307347.395 −307347.271 −282714.070 −307343.519 −283785.701 −282741.647 −308415.418

−248716.732 −248716.741 −248716.742 −248716.738 −248716.740 −247672.687 −247672.735 −247672.735 −273344.420 −273344.625 −273344.623 −248716.736 −273344.194 −248716.740 −247672.748 −273344.886

−33998.595 −33999.280 −33999.408 −33999.394 −33999.845 −33998.374 −33998.613 −33998.402 −33998.718 −33999.091 −33999.438 −33995.622 −33996.294 −35067.967 −35067.966 −35067.648

−1.206 −0.465 −0.833 −0.926 −1.004 −2.156 −1.139 −1.785 −4.410 −3.679 −3.209 −1.713 −3.031 −0.993 −0.932 −2.884

Figure 8. (a) Top view of three functional groups of RGD interacting with graphene in the G-RGD-lying model. Electron density slices pass through (b) the NH3+ and graphene; (c) the guanidine-NH2 and graphene; (d) the COO− and graphene.

strong interactions between NH3+ and carbon structures during the peptide/amino acid interaction with carbon surfaces. 3.2. RGD on Defective Graphene. The defective graphene has various imperfections in the crystal lattice. These imperfections include point defects and substitution atoms.57−60 These defects are the centers of chemical activity and can influence the chemical properties of graphene.61−63 Vacancy defects are one of the most common types of point

interaction is stronger than the COOH···π interaction in an alanine−CNT system. Leenaerts et al.42 studied the adsorption of small molecules on graphene surfaces, and they showed that the interaction between NH3 and graphene is much larger than that between CO and graphene. This finding could be another piece of evidence for the strong interaction of the NH−G system. The results in the present study further proved the 5713

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The adsorption energy of the V-COO−-RGD model (−1.139 eV) is not larger than that of the G-RGD-lying model (−1.206 eV). This finding could be attributed to the weak interactions between COO− and the vacancy. After geometric optimization, the distance between COO− and the vacancy is larger than 3.500 Å, whereas the distance between CH2 and the vacancy is 2.980 Å. Thus, in the V-COO−-RGD model, RGD interacts with the vacancies to a particular extent through CH2 (Supporting Information, Figure 3c). Al-Aqtash et al.63 reported that the binding energy of the COOH group to the defective graphene is larger than to pristine graphene, which could be attributed to the chemical environment of COOH. Unlike COOH, the COO− in RGD is not only attracted by the vacancies on graphene surfaces but also affected by intramolecular interactions of other functional groups in RGD. The current study reveals that the behavior of peptides on material surfaces is complicated. Thus, the behaviors may not be simply predicted from the calculations of small molecules that have similar partial chemical structures of peptides. 3.3. RGD on Graphene Oxide. Before investigating the interactions of RGD and GO, the construction of GO models posed a great challenge because of their nonstoichiometric chemical composition. Individual GO can be viewed as graphene being decorated with O-containing functional groups on both sides and at the edges of the plane.65,66 A large amount of hydroxyl and epoxy groups are generally on the basal plane of GO, whereas few other O-containing groups, such as carboxyl, carbonyl, phenol, and lactone, exist at the edge of the GO sheet.67 Thus, C8O2(OH)2 units that contain O and OH are considered in the present study. These C8O2(OH)2 units have been widely recognized as the stable unit on fully oxidized GO structures.61 Note that the arrangement of O and OH groups in the C8O2(OH)2 units is controversial. Lahaye et al.7 studied the fully oxidized GO structures and found that the two para-OH are adjacent to para-O, and all O are at one side and all OH at the opposite side of the carbon plane. Ghaderi et al.68 demonstrated that the two para-OH at the same side of the carbon plane have the lowest energy. Tang et al.69 reported that two para-OH at the same side of the carbon plane are adjacent to the epoxy groups, and the epoxy groups could be either at the same side or at the opposite side of OH. In our models, two para-OH are at the same side of the carbon plane, and two para-epoxy groups are at the opposite side of the carbon plane (Figure 5b). Geometric optimization results indicate that this model is stable. One OH points to the ortho epoxy oxygen, and the other OH points to the hexagonal center of the carbon ring. The C−O bond lengths in the above model are about 1.5 Å, and the O−H bond lengths are about 1.0 Å. These bond lengths are comparable with those in refs 70−72. The adsorption energy of RGD on GO (−4.410 eV) is almost four times of that of RGD on pristine graphene (−1.206 eV, Table 1). This finding demonstrates that the O-containing groups on GO contribute to the adsorption of RGD. The electron density isosurface mapped with the electron density difference shows that electron transfer mainly happens on the O-containing groups (Supporting Information, Figure 4). The following hydrogen bonds are formed between the functional groups of RGD and O-containing groups in different C 8 O 2 (OH) 2 units: COO − interacts with OH (O 247 − H252···O300; O248−H249···O295), NH3+ interacts with epoxy-O (N259−H283...O255), and guanidine interacts with OH (N268− H279...O244) (Figure 5). The electron density slices of these hydrogen bonds are shown in Supporting Information, Figure

Figure 9. Electron density isosurface mapped with electron density difference of the G-RGD-lying model. The isovalue is 0.05 e/Å3. The charge accumulation and charge depletion are represented by red and blue, respectively.

Figure 10. DOS for the G-RGD-lying model, graphene, and RGD. The dotted line represents the Fermi energy, which is assigned a value of zero.

defects observed in graphene. The vacancy defect sites are reactive because of the presence of dangling bonds.64 The monovacancy is considered in this study (Figure 4). Adsorption energies of the V-NH3+-RGD and V-guanidineRGD models (−2.156, −1.785 eV) are larger than that of the G-RGD-lying model (−1.206 eV). This finding indicates that RGD interacts with the defective graphene more intensively than with pristine graphene (Table 1). This finding could be attributed to the dangling C atoms in the vacancy, which are reactive and have strong interaction with RGD. The bond lengths and bond angles around the dangling C atoms change during the RGD adsorption process (Supporting Information, Figure 2). The dangling C atoms are pulled out of the carbon plane with a displacement of ∼0.02 Å (Supporting Information, Figure 3). This phenomenon also appears when atoms and small molecules interact with graphene surfaces.58,63 The distances between RGD and dangling C atoms in V-NH3+RGD and V-guanidine-RGD are 1.780 and 1.998 Å (Supporting Information, Figures 3a and 3b), respectively. These distances are shorter than the distances of NH3+···π and guanidine···π in the G-RGD-lying model (2.649 Å, Figure 8b; 3.044 Å, Figure 8c) . 5714

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molecular structure of RGE is shown in Supporting Information Figure 8. In this study, RGE interactions with the pristine graphene (Supporting Information Figure 9), defective graphene (Supporting Information Figure 10), and graphene oxide (Supporting Information Figure 11) were investigated. The adsorption energy of RGE on pristine graphene and defective graphene (−0.993, −0.932 eV) is comparable with that of RGD (−1.206, −1.139 eV). The adsorption energy of RGE on the graphene oxide surface is −2.882 eV, which is smaller than that of RGD (−4.410 eV). In summary, RGE shows similar behavior to RGD on different carbon nanostructures.

5, which reveals the electron distribution of the bonds. In summary, the O-containing groups are beneficial for RGD adsorption.73 The following two GO models were built to further analyze the role of OH and O separately: (1) the GO-OH-RGD model, only OH is at the upside of the carbon plane and interacts with RGD (Supporting Information, Figure 6); (2) the GO-O-RGD model, only epoxy groups interact with RGD (Supporting Information, Figure 7). The adsorption energy of RGD on GOOH (−3.679 eV) is larger than that of RGD on GO−O (−3.209 eV), which reveals that OH has a stronger binding ability with RGD than the epoxy groups. The adsorption energy of the GO-RGD-lying model is larger than those of both GOOH-RGD and GO-O-RGD models. Note that the GO-RGDlying model has mixed OH and epoxy groups at the upside of the carbon plane, and therefore both OH and epoxy groups interact with RGD simultaneously. The comparison of the GO model with the OH, epoxy, and mixed OH/epoxy groups reveals that various O-containing groups have distinguishing binding abilities with RGD. This result suggests that RGD binding with carbon nanostructures could be tuned by the ratio of different O-containing groups on the carbon plane. 3.4. Water Effects. G-RGD-Lying-H2O Model. The adsorption energy of RGD on the graphene surface in water (−1.713 eV) is higher than that in vacuum (−1.206 eV, Table 1). This result could be explained in two ways. First, the H2O molecules function as stabilizers that reinforce the interaction between RGD and graphene surfaces. Figure 6a shows that the surrounding water molecules interact with the functional groups of RGD through intermolecular hydrogen bonds. These water molecules also interact with graphene surfaces through H2O···π interaction.68 Therefore, the adsorption of RGD on graphene is strengthened. The distances between the hexagonal centers of graphene and H2O are in the range of 2.5−3.5 Å (Figure 6b). These distances are comparable with the result of Voloshina et al.74 Thus, physisorption occurs between H2O and graphene. Second, H2O molecules inhibit the cyclization of RGD. Figure 8a shows that without water RGD has a tendency to cyclize. The cyclization of RGD has been reported by previous studies.75 The addition of water interferes with the interaction of NH2 and COO−. Therefore, water prevents the cyclization of RGD (Figure 6a). Thus, the backbone of the RGD molecule is flexible enough to be easily adsorbed on the graphene surface by adopting a favorable configuration that strengthens the binding of RGD on graphene. GO-RGD-Lying-H2O System. The adsorption energy of RGD on GO in water (−3.031 eV) is lower than that in vacuum (−4.410 eV). This result occurs because the H2O molecules cap the adsorption sites on GO. Therefore, RGD cannot directly interact with GO surfaces. Figure 7 shows that two H2O molecules occupy the two hydroxyl sites to form hydrogen bonds with OH (dO−H = 1.346, 1.920 Å). Thus, the COO− of RGD can only interact with the water molecules. The hydrogen bonds of RGD−GO in vacuum (Figure 5b, O247− H252···O300 and O248−H249···O295) could not form with the presence of water. In addition, the interaction between NH3+, guanidine, and GO became weaker with larger N−H···O distances of 1.921 and 2.934 Å (Figure 7), respectively. 3.5. RGE Interaction with Graphene. Arginine-glycineglutamic acid (RGE) is commonly used as a control of RGD. It has a similar structure to RGD, whereas it has different biological activity to cell behavior.76,77 The three-dimensional

4. CONCLUDING REMARKS The current study investigates the interaction of RGD and various carbon nanostructures. The main conclusions are summarized in the following sections. These conclusions provide useful guidance for the design of optimal carbon nanomaterial surfaces for selective protein and peptide binding. (i) A weak noncovalent interaction occurs between RGD and pristine graphene. This interaction is attributed to NH3+···π, guanidine−NH2···π, and COO−···π interactions. Various RGD configurations on graphene surfaces lead to different adsorption energies. The G-RGD-lying model has the largest adsorption energy. The interaction of NH3+···π is stronger than those of guanidine−NH2···π and COO−···π. RGD also interacts with graphene through CH2 to a particular extent. (ii) The defective graphene with vacancies has a stronger interaction with RGD than pristine graphene. This finding is attributed to the interactions between the dangling C atoms with NH3+ and guanidine. (iii) GO has a stronger interaction with RGD than the pristine and the defective graphene because of O-containing groups. The O-containing groups are able to form hydrogen bonds with the functional groups of RGD. The comparison of RGD on the GO model with OH, epoxy, and mixed OH/epoxy groups reveals that different O-containing groups have distinguishing binding ability with RGD. (iv) Water molecules strengthen the interactions between graphene and RGD. However, water molecules weaken the interactions between GO and RGD. In the pristine graphene model, water molecules interact with the graphene surface through H2O···π interaction and also interact with the functional groups of RGD through intermolecular hydrogen bonds. Therefore, water molecules reinforce the interaction between RGD and graphene. In the GO model, water has a strong interaction with the O-containing groups of GO and occupies the active site of GO, which hampers the approach of RGD to GO surfaces. On the basis of the aforementioned conclusions, carbon nanomaterials with specific characteristics could be designed to satisfy the demand for diverse applications of carbon nanomaterials in biomedical fields. When a weak peptide and material interactions are desired, the defective structures on carbon nanomaterials should be avoided. When a strong binding between peptides/proteins and carbon surfaces is pursued, the O-containing groups on carbon nanomaterials could be introduced. The intensity of binding between peptides and carbon surfaces could be tuned by an elaborately designed ratio of the O-containing groups, such as OH and epoxy groups. When biomolecules are expected to bind with carbon nanomaterials, more NH groups could be grafted to 5715

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(18) Gianese, G.; Rosato, V.; Cleri, F.; Celino, M.; Morales, P. J. Phys. Chem. B 2009, 113, 12105−12112. (19) Tomasio, S. D. M.; Walsh, T. R. Mol. Phys. 2007, 105, 221−229. (20) Hersel, U.; Dahmen, C.; Kessler, H. Biomaterials 2003, 24, 4385−4415. (21) Sawyer, A. A.; Hennessy, K. M.; Bellis, S. L. Biomaterials 2005, 26, 1467−1475. (22) Sawyer, A. A.; Weeks, D. M.; Kelpke, S. S.; McCracken, M. S.; Bellis, S. L. Biomaterials 2005, 26, 7046−7056. (23) Zhang, Z.; Lai, Y.; Ding, J. Biomaterials 2010, 31, 7873−7882. (24) Chen, M.; Wu, C.; Song, D.; Dong, W.; Li, K. J. Mater. Sci.: Mater. Med. 2009, 20, 1831−1838. (25) Zhang, H.; Lu, X.; Leng, Y.; Watari, F.; Weng, J.; Feng, B.; Qu, S. J. Biomed. Mater. Res. A 2010, 96A, 466−476. (26) Ganji, M. D. Diamond Relat. Mater. 2009, 18, 662−668. (27) Delley, B. J. Chem. Phys. 1990, 92, 508−517. (28) Delley, B. J. Chem. Phys. 2000, 113, 7756−7764. (29) Delley, B. Phys. Rev. B 2002, 66, 155125−155133. (30) Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865−3868. (31) Monkhorst, H. J.; Pack, J. D. Phys. Rev. B 1976, 13, 5188−5192. (32) Medeiros, P. V. C.; Mascarenhas, A. J. S.; Mota, F. d. B.; Castilho, C. M. C. d. Nanotechnology 2010, 21, 485701−485708. (33) Chi, M.; Zhao, Y. Comput. Mater. Sci. 2009, 46, 1085−1090. (34) Power, L. F.; Turner, K. E. Acta Crystallogr. 1976, B32, 11−16. (35) Rao, S. T. Acta Crystallogr. 1973, B29, 1718−1720. (36) Derissen, J. L.; Endeman, H. J.; Peerdeman, A. F. Acta Crystallogr. 1968, B24, 1349−1354. (37) Bhat, T. N.; Vijayan, M. Acta Crystallogr. 1977, B33, 1754− 1759. (38) Karle, I. L.; Karle, J. Acta Crystallogr. 1964, 17, 835−841. (39) Jonsson, P. G.; Kvick, A. Acta Crystallogr. 1972, B28, 1827− 1833. (40) Rajarajeswari, M.; Iyakutti, K.; Kawazoe, Y. J. Mol. Model. 2011, 18, 771−781. (41) Wu, Q.; Li, X.; Bian, W.; Fan, X.; Qi, J. Biomaterials 2010, 31, 1007−1016. (42) Leenaerts, O.; Partoens, B.; Peeters, F. M. Phys. Rev. B 2008, 77, 125416(1)−125416(6). (43) Atala, A.; Lanza, R.; Thomson, J. A.; Nerem, R. M. Principles of regenerative medicine; Elsevier/Academic Press: Amsterdam, 2008. (44) Furth, M. E.; Atala, A.; Van Dyke, M. E. Biomaterials 2007, 28, 5068−5073. (45) Nikkhah, M.; Edalat, F.; Manoucheri, S.; Khademhosseini, A. Biomaterials 2012, 33, 5230−5246. (46) Vashist, S. K.; Zheng, D.; Pastorin, G.; Al-Rubeaan, K.; Luong, J. H. T.; Sheu, F.-S. Carbon 2011, 49, 4077−4097. (47) Rajarajeswari, M.; Iyakutti, K.; Kawazoe, Y. J. Mol. Model. 2011, 17, 2773−2780. (48) Ma, F.; Zhang, Z.; Jia, H.; Liu, X.; Hao, Y.; Xu, B. J. Mol. Struct. 2010, 955, 134−139. (49) Brandl, M.; Weiss, M. S.; Jabs, A.; Suhnel, J.; Hilgenfeld, R. J. Mol. Biol. 2001, 307, 357−377. (50) Mohan, N.; Vijayalakshmi, K. P.; Koga, N.; Suresh, C. H. J. Comput. Chem. 2010, 31, 2874−2882. (51) Zhang, Z.; Jia, H.; Ma, F.; Han, P.; Liu, X.; Xu, B. J. Mol. Model. 2011, 17, 649−655. (52) Kusama, H.; Orita, H.; Sugihara, H. Sol. Energy Mater. Sol. Cells 2008, 92, 84−87. (53) Xiao, B.; Xing, J. D.; Ding, S. F.; Su, W. Phys. B 2008, 403, 1723−1730. (54) Elsasser, C.; Elsasser, T. J. Am. Ceram. Soc. 2005, 88, 1−14. (55) Naderi, F.; Karami, A.; Naderi, B. Org. Chem. J. 2011, 2, 44−49. (56) Hu, P.; Fasoli, A.; Park, J.; Choi, Y.; Estrela, P.; Maeng, S.; Milne, W. I.; Ferrari, A. C. J. Appl. Phys. 2004, 104, 074310−074314. (57) Miwa, R. H.; Martins, T. B.; Fazzio, A. Nanotechnology 2008, 19, 155708−155714. (58) Al-Aqtash, N.; Vasiliev, I. J. Phys. Chem. C 2011, 115, 18500− 18510.

biomolecules to improve the binding between biomolecules and carbon surfaces.

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ASSOCIATED CONTENT

S Supporting Information *

Supporting figures illustrate the optimized geometry of RGD and RGE, defected graphene surfaces, the configurations of VNH3+-RGD, V-COO−-RGD, V-guanidine-RGD, GO-OHRGD, GO-O-RGD, G-RGE-lying, V-COO−-RGE, and GORGE-lying models and the electronic structures of RGD adsorption on the graphene oxide surface. The supporting table displays geometry parameters of optimized RGD. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel.: +86-28-87634023. Fax: +86-28-87601371. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This project was financially supported by the 973 Program (2012CB933602), NSFC (31070851), Program for New Century Excellent Talents in University (NCET-10-0704), Sichuan Youth Science-Technology Foundation (2011JQ0010), and Fundamental Research Funds for the Central Universities (SWJTU11CX150).

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REFERENCES

(1) Liu, Z.; Robinson, J. T.; Tabakman, S. M.; Yang, K.; Dai, H. Mater. Today 2011, 14, 316−323. (2) Singh, G.; Choudhary, A.; Haranath, D.; Joshi, A. G.; Singh, N.; Singh, S.; Pasricha, R. Carbon 2012, 50, 385−394. (3) Singh, V.; Joung, D.; Zhai, L.; Das, S.; Khondaker, S. I.; Seal, S. Prog. Mater. Sci. 2011, 56, 1178−1271. (4) Lee, C.; Wei, X.; Kysar, J. W.; James, H. Science 2008, 321, 385− 388. (5) Khan, U.; O Connor, I.; Gun ko, Y. K.; Coleman, J. N. Carbon 2010, 48, 2825−2830. (6) Bagri, A.; Mattevi, C.; Acik, M.; Chabal, Y. J.; Chhowalla, M.; Shenoy, V. B. Nat. Chem. 2010, 2, 581−587. (7) Lahaye, R. J. W. E.; Jeong, H. K.; Park, C. Y.; Lee, Y. H. Phys. Rev. B 2009, 79, 125435(1)−(8). (8) Wang, Y.; Li, Z.; Wang, J.; Li, J.; Lin, Y. Cell 2011, 29, 205−212. (9) Nayak, T. R.; Andersen, H.; Makam, V.; Khaw, C.; Bae, S.; Xu, X.; Ee, P.-L. R.; Ahn, J.-H.; Hong, B. H.; Pastorin, G.; et al. ACS Nano 2011, 5, 4670−4678. (10) Lee, W. C.; Lim, C. H. Y. X.; Shi, H.; Tang, L. A. L.; Wang, Y.; Lim, C. T.; Loh, K. P. ACS Nano 2011, 5, 7334−7341. (11) Sun, X.; Liu, Z.; Welsher, K.; Robinson, J. T.; Goodwin, A.; Zaric, S.; Dai, H. Nano Res. 2008, 1, 203−212. (12) Yang, X.; Zhang, X.; Liu, Z.; Ma, Y.; Huang, Y.; Chen, Y. J. Phys. Chem. C 2008, 112, 17554−17558. (13) Rajesh, C.; Majumder, C.; Mizuseki, H.; Kawazoe, Y. J. Chem. Phys. 2009, 130, 124911(1)−124911(6). (14) Cazorla, C.; Shevlin, S. A.; Guo, Z. X. Phys. Rev. B 2010, 82, 155454(1)−155454(12). (15) Roman, T.; Dino, W. A.; Nakanishi, H.; Kasai, H. Thin Solid Films 2006, 509, 218−222. (16) Chiu, C. C.; Dieckmann, G. R.; Nielsen, S. O. Biopolymers 2009, 92, 156−163. (17) Gao, H. J.; Kong, Y.; Cui, D. X.; Ozkan, C. S. Nano Lett. 2003, 3, 471−473. 5716

dx.doi.org/10.1021/jp310088e | J. Phys. Chem. C 2013, 117, 5708−5717

The Journal of Physical Chemistry C

Article

(59) Carlson, J. M.; Scheffler, M. Phys. Rev. Lett. 2006, 96, 046806− 046809. (60) Chen, L.; Hu, H.; Ouyang, Y.; Pan, H. Z.; Sun, Y. Y.; Liu, F. Carbon 2011, 49, 3356−3361. (61) Boukhvalov, D. W.; Katsnelson, M. I. Nano Lett. 2008, 8, 4373− 4379. (62) Wang, C.; Zhou, G.; Liu, H.; Wu, J.; Qiu, Y.; Gu, B.; Duan, W. J. Phys. Chem. B 2006, 110, 10266−10271. (63) Al-Aqtash, N.; Vasiliev, I. J. Phys. Chem. C 2009, 113, 12970− 12975. (64) Rossato, J.; Baierle, R. J.; Fazzio, A.; Mota, R. Nano Lett. 2005, 5, 197−200. (65) He, H.; Klinowski, J.; Forster, M.; Lerf, A. Chem. Phys. Lett. 1998, 287, 53−56. (66) Kuila, T.; Bose, S.; Khanra, P.; Mishra, A. K.; Kim, N. H.; Lee, J. H. Carbon 2012, 50, 914−921. (67) Gao, W.; Alemany, L. B.; Ci, L.; Ajayan, P. M. Nat. Chem. 2009, 1, 403−408. (68) Ghaderi, N.; Peressi, M. J. Phys. Chem. C 2010, 114, 21625− 21630. (69) Tang, S.; Cao, Z. J. Chem. Phys. 2011, 134, 004710(1)− 004710(14). (70) Jelea, A.; Marinelli, F.; Ferro, Y.; Allouche, A.; Brosset, C. Carbon 2004, 42, 3189−3198. (71) Xu, S. C.; Musaey, D. G.; Lin, M. C. J. Phys. Chem. C 2007, 111, 1355−1365. (72) Denis, P. A. J. Phys. Chem. C 2009, 113, 5612−5619. (73) Dreyer, D. R.; Park, S.; Bielawski, C. W.; Ruoff, R. S. Chem. Soc. Rev. 2010, 39, 228−240. (74) Voloshina, E.; Usvyat, D.; Schutz, M.; Dedkov, Y.; Paulus, B. Phys. Chem. Chem. Phys. 2011, 13, 12041−12047. (75) Bythell, B. J.; Csonka, I. P.; Suhai, S.; Barofsky, D. F.; Bela, P. J. Phys. Chem. B 2010, 114, 15092−15105. (76) Huebsch, N.; Arany, P. R.; Mao, A. S.; Shvartsman, D.; Ali, O. A.; Bencherif, S. A.; Rivera-Feliciano, J.; Mooney, D. J. Nat. Mater. 2010, 9, 518−526. (77) Zhang, Z.; Lai, Y. X.; Yu, L.; Ding, J. D. Biomaterials 2010, 31, 7873−7882.

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