Imaging Carbon Nanotube Interaction with Nucleobases in Water

Jun 25, 2012 - Imaging Carbon Nanotube Interaction with Nucleobases in Water Using ... Molecules by the Molecular Integral Equation Theory: Approachin...
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Imaging Carbon Nanotube Interaction with Nucleobases in Water Using the Statistical Mechanical Theory of Molecular Liquids Takeshi Yamazaki* and Hicham Fenniri* Department of Chemistry and Department of Biomedical Engineering, University of Alberta, and National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, AB T6G 2M9, Canada ABSTRACT: Nanoparticles (NPs) become specifically or nonspecifically coated with biomolecules upon contact with biological fluids. The nature of this coating determines the final biological identity of the NP. Therefore, predictive information about the interactions between biomolecules and NPs in solution is essential for materials design and engineering. However, the lack of detailed structural information about NP−biomolecule complexes in biological systems does not facilitate our understanding of the nature of the interactions and the mechanisms leading to their formation. With the aim of establishing a theoretical framework to study NP−biomolecule complexes in biological fluids, we show how 3D-RISM theory could be utilized to probe single-walled carbon nanotube interactions with nucleobases in water.

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INTRODUCTION With the rapid growth of nanotechnology the likelihood of nanomaterials coming into contact with humans and the environment is increasing. The evaluation of nanomaterials properties and safety in biological systems is thus indispensable for a harmonious coexistence of nanotechnology and our environment. Upon contact with biological fluids, nanoparticles (NP) become specifically or nonspecifically coated with biomolecules, and the nature of this coating determines the final biological identity of the NP.1,2 Unfortunately, very little is known about the mechanisms of interactions between biomolecules and nanomaterials because detailed structural information for NP−biomolecule complexes in biological fluids is not readily accessible. Information about the interactions between biomolecules and nanomaterials in solution has been thus far based mainly on infrared spectroscopy, circular dichroism, fluorescence spectroscopy, and other methods that can monitor relatively global structural changes.3−6 Although recent studies suggest that NMR spectroscopy could identify protein−NP interactions at the primary sequence level in solution,7 it has not yet resulted in three-dimensional information about the molecular structure of the NP−biomolecule complex in solution. The present article introduces statistical mechanical theory of molecular liquids (i.e., 3D-RISM theory8,9) as an effective method to probe the 3D molecular structure of NP− biomolecule complexes and their interactions in biological fluids. Starting from the atomistic solute−solvent molecular interactions, 3D-RISM theory directly yields the 3D density distribution of solvent around the solute macromolecule (the 3D solvation structure).10−12 Therefore, by regarding the constituent species of the biological fluid (water, biomolecules such as amino acids, hormones, proteins, and nucleic acids) as solvent molecules for the solute (i.e., NP), we are able to predict the structure of biomolecules around the NP. Because © 2012 American Chemical Society

3D-RISM theory works at an ensemble of solvent configurations in the entire phase space, the resulting solvation structure includes the solvent configuration occurring on large space and time scale, which is usually not accessible from conventional molecular simulations, such as equilibrium solvent configuration in the confined space of a protein cavity.13 The resulting solvation structure also includes the conformation (position and orientation) of biomolecules within the NP− biomolecule complex. The 3D density distribution can provide us with not only the adhesion conformation between the NP and the biomolecule but also the corresponding potential of mean force, which is the average work needed to bring the biomolecule from infinite separation to the adhesion conformation. The latter is equivalent to the adhesion strength between the NP and biomolecule in biological fluids. With the aim of establishing a theoretical framework to study NP−biomolecule complexes in biological fluids, here we show how 3D-RISM theory could be utilized to probe single-walled carbon nanotube (CNT) interactions with nucleobases in water. The interaction between CNT and nucleobases has received considerable attention because CNT wrapped with single-stranded DNA holds a great potential for technological applications such as CNT solubilization and sorting,14−16 chemical and biological sensing,4,17−19 and DNA sequencing.20 At present the exact knowledge of the 3D structure of the CNT−DNA complex is unknown,21 although various experimental studies based on spectroscopic techniques4,14,15,22−25 have attempted its characterization. For example, a recent study reported that the UV absorbance changes following binding of DNA homopolymers to CNTs are associated with preferred Received: March 20, 2012 Revised: June 22, 2012 Published: June 25, 2012 15087

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representative adsorption conformations. From a simple geometrical consideration, it is clear that the conformations that are parallel to the CNT surface (if they do exist) would be included in this spatially limited solvation space. However, the adsorption conformation is not necessarily limited to this space because the association between NP and biomolecules is a dynamic process.2 Therefore, while the adsorption structure is expected to fluctuate over time, the difference in interaction strength between MPM-A and MPM-S was found to be small (vide inf ra), indicating that the association conformation of nucleobase can fluctuate between these two modes. As a result, whether we consider MPM-A or MPM-S, the outcome of our analysis is essentially the same. The grid search was carried out based on the Lamarckian genetic algorithm in Autodock4.240 with the grid maps of SIPMF for the nucleobase obtained by the 3D-RISM calculation. The size of the grid map used is 384 × 384 × 480 points, and the grid point spacing is 0.25 Å as in the case of 3D-RISM calculation. The parameters for the genetic algorithm were set to the default values recommended by the program. A total of 2000 runs were launched, and the MPM was obtained in each grid search run. Because of the cylindrical symmetry of CNT, the MPM from each grid search run eventually forms the cylindrical cluster around the CNT surface as shown below. RISM and 3D-RISM Theories. A general description of RISM and 3D-RISM theories is documented elsewhere.41 A brief outline of the calculations is presented here. First we solve the RISM equation (eq 1) for the solvent system to obtain the solvent−solvent correlation functions (expressed by the superscript “vv”) starting with the potential functions of the solvent molecules and with the density and the temperature of the solvent system

orientations assumed by each of the four bound nucleotides with respect to the nanotube’s long axis.5 The role and nature of CNT−nucleobase interactions in the formation of a stable CNT−DNA complex has been investigated experimentally and computationally.5,20,26−37 The interaction energy between CNT and nucleobases was consistently estimated in the range of 6−10 kcal/mol. However, a consensus has not been reached yet with regard to the affinity trend of the nucleobases. Adsorption isotherms analysis between nucleobases and graphite,26 density functional theory (DFT) calculations with the local density approximation for nucleobases and graphene31 and nucleobases and CNT,32 and molecular dynamics simulations for DNA−CNT33 and nucleobase−CNT34 complexes have shown the following affinity trend: guanine (G) > adenine (A) > thymine (T) > cytosine (C). Ab initio MP2 calculation for nucleobases and a fragment of CNT29 suggested that the trend is G > A > C ≈ T. Yet, another study of the specific nucleobase dissociation temperature of DNA homopolymer and CNT complex30 and DFT calculation with the hybrid meta generalized gradient approximation for nucleobase and CNT36 have presented the following trend: G > C > A > T. Discrepancy among these results points to the challenges associated with quantitatively analyzing the interaction strength between NPs and biomolecules in water. Such interaction is determined by a subtle balance between (a) the adhesion of the biomolecule on the NP surface, (b) the solvation of the NP, and (c) the solvation of the biomolecule. To overcome this challenge, we hypothesized that by treating the biomolecule as one of the solvent species, 3D-RISM theory could appropriately take into account these three phenomena with the same level of theoretical description and provide a quantitative evaluation of the interaction strength.

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vv hαγ (r ) =

METHODS Outline of the Imaging Procedure. In order to identify the structural (position, orientation) and thermodynamic (association strength) aspects of the adhesion process between CNTs and our target biomolecules, we followed Imai’s procedure for ligand mapping on protein surfaces.38,39 This procedure consists of two steps: Step 1. The 3D density distribution functions gγ(r) of the nucleobase sites γ on the 3D grid points are calculated by 3DRISM theory for the systems in which the solute CNT is solvated in the water−nucleobase mixture. Step 2. Probable conformations of the nucleobase are reconstructed from the 3D density distribution functions gγ(r) of the nucleobase sites γ using a grid search algorithm. Most probable mode (MPM) is defined as the conformation (position and orientation) that has the most preferable siteintegrated potential of mean force (SI-PMF),38,39 or equivalently adhesion strength in the present context, than any other probable conformation generated in the grid search run. We define the MPM of the solvation (MPM-S) as the MPM searched from the entire solvation space and define the MPM of the adhesion (MPM-A) as the MPM searched from the solvation space spatially limited on the CNT surface within 4.5 Å. Because earlier computational studies29,31,32,34,36 considered the conformations of nucleobases that are parallel to the CNT surface as the adsorption conformations, and in order to be able to compare our results to these studies, we spatially limited the solvation space to see if we can extract such conformations (i.e., parallel to the CNT surface) and considered them (MPM-A) as

∑ ωααvv ′∗cαvv′ γ′∗(ωγvv′ γ (r) + ρhγvv′ γ (r)) α′γ′

(1)

where h, c, and ω are the total, direct, and intramolecular correlation functions, respectively; ρ is the number density of solvent; the subscripts (α, α′, γ, γ′) indicate site labels of solvent; the asterisk denotes a convolution integral. h is equivalent to g − 1, where g is the solvent distribution function. The vv correlation functions are required when solving 3DRISM equation (eq 2) for the solute−solvent system to obtain the 3D density distribution functions of solvent molecules around the solute molecule (expressed by the superscript “uv”). hγuv (r) =

∑∫

cγuv′ (r′){ωγvv′ γ (|r′ − r|) + ρhγvv′ γ (|r′ − r|)}

γ′

dr′

(2)

We prepared the four solvent systems water−A, water−C, water−G, and water−T mixtures in which the nucleobase is dissolved at dilute concentration (ca. 0.06 M) under ambient conditions. We solved RISM equation coupled with KH closure42 to obtain the vv correlation functions for water− water, water−nucleobase, and nucleobase−nucleobase. To obtain the solvation structure (3D density distribution) of nucleobases around the CNT, the vv correlation functions were used to solve 3D-RISM equation coupled with KH closure for the solute−solvent system in which the finite length of CNT (35 Å) is dissolved in the water−nucleobase mixtures. From the uv resulting 3D density distribution function guv γ (r) = hγ (r) + 1 the SI-PMF of nucleobase at the orientation Ω is defined by 15088

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on nucleobase

W (Ω) = −kBT

∑ γ

ln gγuv (r(Ω))

(3)

We utilized the 3D rectangular grid of 384 × 384 × 480 in a supercell of size 96 Å × 96 Å × 120 Å that is large enough to accommodate the solute CNT with sufficient solvation space (a margin of more than 40 Å on each side of the cube). We examined CNT(7,0), CNT(11,0), and CNT(15,0) to see how the adhesion strength changes depending on the CNT diameters (the diameters are 5.5, 8.6, and 11 Å, respectively). AMBER9943 force field was used to model nucleobases according to the previous computational study,34 and the TIP3P model44 was used for water. The carbon atoms of CNT were modeled as uncharged sp2 carbons from AMBER99 force field. The solution density of water−nucleobase mixture was estimated by molecular dynamics simulation with Amber 1045 using the same force field parameters.

Figure 2. MPM-As of adenine around CNT(15,0) (A) and the representative MPM-As (B−E).

that the adhesion propensity of A is stronger than that of T. However, calorimetric measurements46 of the association energy with larger diameter CNTs (14 Å) showed the opposite trend. Indeed, the channel diameter of CNT(15,0) investigated here with a smaller inner diameter (11 Å) was found to be large enough to accommodate the nucleobases. Thus, since an even larger diameter could accommodate nucleobases inside its channel (especially the smaller pyrimidine type T) the discrepancy observed may be attributed to an interaction inside of CNT channel. Figure 2B−E shows four representative orientations of MPM-As on the CNT surface. They have the same adhesion strength although their orientation is different. It is particularly interesting to see that the orientation of A shown in Figure 2B is the orientation suggested from the UV optical absorption measurement for the DNA homopolymer−CNT system.5 We carried out similar analyses for other CNTs and summarized the MPM-S and MPM-A for each nucleobase in Table 1. For CNT(7,0) and CNT(11,0), we found that the

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RESULTS AND DISCUSSION Figure 1A shows the 3D density distribution of A around CNT(15,0) obtained by 3D-RISM. For clarity, the 3D density

Figure 1. 3D solvent distribution of adenine around CNT(15,0) obtained by the 3D-RISM theory (A) and the resulting MPMs of adenine around the CNT (B). For clarity, the 3D distributions of only two atomic sites of adenine, one of the nitrogen atoms (blue) and one of the carbon atoms (cyan), are presented. The lower half part of CNT is shown.

Table 1. Predicted Binding Strength of MPM-S and Adhesion Strength of MPM-A (kcal/mol); Δ Is the Difference between the Binding Strength of MPM-S and Adhesion Strength of MPM-A

distributions of only two atomic sites of A, one of the nitrogen atoms (blue) and one of the carbon atoms (cyan), are presented. We can see that the CNT is solvated by A not only on its surface but also in its channel. We ran Autodock4.2 to extract the MPM from the 3D density distribution, and the MPMs of A are presented in Figure 1B. The MPMs form a circular cluster around the CNT because of its cylindrical symmetry. Analysis of the MPMs in the entire solvation space showed that the MPM-Ss are distributed in the CNT channel (as shown in Figure 1B) with a binding strength of 14.5 kcal/ mol. CNT(15,0) has a relatively large channel diameter that can accommodate nucleobases within. On the other hand, analysis of the solvation space (excluding the inner CNT channel) showed that the MPMs correspond to the conformations surrounding the CNT (as shown in Figure 1B) and have a binding strength of ca. 7.9 kcal/mol. Furthermore, from the analysis of MPMs in the adhesion space, the MPM-As were determined as shown in Figure 2A, and their adhesion strength was calculated to be ca. 7.7 kcal/mol. These interaction strengths are about half of the binding strength of MPM-S, indicating that the encapsulation of the nucleobase inside the CNT channel could complicate the interpretation of experimental measurements. For example, earlier studies suggested

CNT(7,0) MPM-S MPM-A Δ CNT(11,0) MPM-S MPM-A Δ CNT(15,0) MPM-S MPM-A Δ

A

C

G

T

7.08 6.83 0.25

6.08 5.60 0.48

7.88 7.62 0.26

6.60 6.00 0.6

7.69 7.56 0.13

6.63 6.17 0.46

8.60 8.40 0.20

7.14 6.70 0.44

14.45 7.73 6.72

11.92 6.32 5.6

15.31 8.53 6.78

13.43 6.84 6.59

MPM-Ss are distributed around the CNT surface, and there was no MPM found inside the channels due to their small diameters. Representative orientations of MPM-S and MPM-A of G in the case of CNT(11,0) (Figures 3A and 3B, respectively) show that MPM-S is not completely parallel to the CNT surface with its carbonyl oxygen sticking out to interact with water and other Gs in solution. This observation suggests that the adsorption process is indeed determined by a subtle balance of interactions between the CNT, the nucleobases, and the solvent. 15089

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nucleobase complex was constructed using the MPM-A predicted above. Figure 4A shows the 3D density distribution of G around the CNT(11,0)-G complex. The G of the complex is colored in orange, and the 3D density distributions of only two atomic sites of G are presented for clarity (one of the nitrogen atoms in blue and one of the carbon atoms in cyan). By analyzing the density distributions in the entire solvation space, we determined the MPM-Ss of G as shown in Figure 4B. Our results show that all MPM-Ss interact with the precomplexed G, and because of this interaction, the binding strength was found to be ca. 9 kcal/mol, which is larger than the binding strength of MPM-S of G for the system in which CNT(11,0) was dissolved in the water−G mixture (Table 1). This observation suggests that the nucleobase adhered to the surface could facilitate additional nucleobase adhesion in solution, thereby suggesting that nucleobase adhesion to CNT(11,0) is a cooperative process. When examining the MPM-Ss, we found that the cluster of MPM-Ss actually included the G orientation that is parallel to the CNT surface (Figure 4C). This was never observed when we analyzed the MPM-Ss for the system in which CNT was solely solvated by water−nucleobase mixtures. Even though the difference between the binding strength of MPM-S and the adhesion strength of MPM-A was very small as shown in Table 1, such parallel conformation was not found in the MPM-S cluster. This observation may be indicating that the fluctuation in the adhesion conformation of nucleobase becomes smaller as the surface coating progresses, and eventually it may form relatively rigid nanocomposite material. From the present analysis we have found that all MPM-S of G interact with the G adhered on the surface, however, there was no G found that stacks on the G adhered on the CNT surface. Our result is consistent with the theoretical findings that Watson−Crick as well as several nonWatson−Crick base pairs lying on a graphene surface are more stable in water than a π−π−π-stacked graphene−base−base assembly.35 Table 2 summarizes the adhesion strength of MPM-S for A, C, G, and T adsorbing onto the surface of CNT−A, CNT−C, CNT−G, and CNT−T complexes, respectively, and the difference in adhesion strength relative to MPM-A for each nucleobase adsorbing onto to the bare CNT surface. While these results show that the affinity trend of the nucleobases did not change (G > A > T > C), the difference in association strength between precomplexed CNT and bare CNT is not uniform, suggesting that the affinity trend could eventually change after several steps in the adhesion process. This conclusion is reasonable since the interaction between

Figure 3. Representative orientations of MPM-S (A) and MPM-S (B) of guanine around CNT(11,0).

The adhesion strengths predicted by 3D-RISM theory are in the range of 5.6−8.5 kcal/mol, which is in good agreement with earlier studies and justifies the definition of MPM-A in the present study. Concerning the affinity trend of nucleobases, 3D-RISM predicted that the trend of adhesion would follow G > A > T > C, which agrees well with, and substantiates, earlier experimental and computational studies.26,31−34 Considering that we have modeled CNT and nucleobases according to ref 34, the agreement with their computational result is reasonable and indicates that our procedure is robust. While the affinity trend of four nucleobases is the same for each CNT examined here, we noted that the adhesion strength increased as the CNT diameter increased, which can be ascribed to the low angle of surface curvature that is more favorable to stacking and van der Waals interactions. This is consistent with a theoretical study in which the interaction energy between a CNT fragment and C showed an increasing trend with increasing nanotube diameter.28 These results confirm that 3D-RISM theory is suitable for both the prediction of 3D molecular structure and the prediction of interaction strength of the NP−biomolecule complex. After establishing the structure and thermodynamics of nucleobase/CNT interaction, we turned our attention to the process of surface coating of the CNTs with nucleobases. In particular, we reasoned that once the first nucleobase adheres to the surface it may accelerate (cooperative), prevent (anticooperative), or not affect (noncooperative) the adhesion of additional nucleobases. It may also interact with additional nucleobases via stacking interactions. To address these questions, the CNT(11,0)−nucleobase complex was dissolved (in silico) in an aqueous solution of the same nucleobase as in the complex. The 3D molecular structure of the CNT−

Figure 4. 3D solvent distribution of guanine around the CNT(11,0)−guanine complex (A), the resulting MPM-Ss of guanine (B), and the adhesion conformation found in the MPM-S cluster (C). Guanine in the CNT−guanine complex is colored in orange. For clarity, the 3D distributions of only two atomic sites of guanine, one of the nitrogen atoms (blue) and one of the carbon atoms (cyan), are presented. The yellow dotted lines (C) indicate the possible hydrogen bonds between guanine of MPM-S and the guanine of CNT−guanine complex. 15090

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Table 2. Binding Strength of the Adhesion Conformation Found in MPM-S Cluster for the System in Which CNT(11,0)−A, CNT(11,0)−C, CNT(11,0)−G, and CNT(11,0)−T Complexes Are Solvated in Water−A, Water−C, Water−G, and Water−T Mixtures, Respectively (kcal/mol); Δ Is the Difference between the Binding Strength and the Adhesion Strength of MPM-A Obtained for CNT(11,0)−A, CNT(11,0)−C, CNT(11,0)−G, and CNT(11,0)−T (Table 1) binding strength Δ

A

C

G

T

8.15 0.6

7.38 1.2

9.30 0.9

7.92 1.2

nucleobases will depend on the nature of the precomplexed nucleobase. Needless to say, these results may not be directly relevant to a DNA oligomer because the latter’s adhesion would naturally be perturbed by the sugar and phosphate moieties and by the preorganization of the nucelobases as shown in a recent MD simulation and density functional theory calculation.47 Nevertheless, our results provide additional insight that could help rationalize the affinity trends observed. Lastly, it should be noted that the present procedure can also be useful to monitor the entire step-by-step adhesion process of nucleobases on the CNT surface. This feature will further strengthen 3D-RISM theory as a tool to probe the surface interaction of nanomaterials.

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CONCLUSION In summary, our theoretical approach unveiled the cooperative nature of the adsorption process of nucleobases on the CNT surface. We showed that 3D-RISM theory can be used as a tool to “image” the surface interaction between nanomaterials and biologically relevant molecules in water. We envision that this approach will allow us to investigate the process of selfassembly on the surface of CNTs simply from the knowledge of the constituent components of a biological fluid. This would in turn allow us to design biocompatible nanomaterials for applications in nanomedicine and drug delivery. The predicted molecular structure will also serve as a starting point for molecular dynamics and quantum chemistry, which can further expand the applications of theory and modeling in nanotechnology.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (T.Y.), hicham.fenniri@ualberta. ca (H.F.). Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was supported by Canada’s National Research Council (NRC) and Natural Science and Engineering Research Council, and the University of Alberta. This research has been enabled by the use of computing resources provided by WestGrid and Compute/Calcul Canada. The figures were generated with VMD.48

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REFERENCES

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dx.doi.org/10.1021/jp3026804 | J. Phys. Chem. C 2012, 116, 15087−15092