Probing the Salt Concentration Dependent Nucleobase Distribution in

Dec 30, 2015 - Telephone: + 91-022-2576 7152. ... The hybrids of single-walled carbon nanotube (SWCNT) and single stranded DNA (ssDNA) are novel ...
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Probing the Salt Concentration Dependent Nucelobase Distribution in a Single-Stranded DNA−Single-Walled Carbon Nanotube Hybrid with Molecular Dynamics Soumadwip Ghosh, Nisheet Patel, and Rajarshi Chakrabarti* Department of Chemistry, Indian Institute of Technology, Powai, Mumbai, 40076, India S Supporting Information *

ABSTRACT: The hybrids of single-walled carbon nanotube (SWCNT) and single stranded DNA (ssDNA) are novel nanoscale materials having remarkable applications in nanotechnology. The absorption of nucleobases on the surface of a SWCNT depends strongly on the ionic strength of the medium. In this paper, using atomistic molecular dynamics we have shown that at low salt concentration ssDNA wraps on the surface of SWCNT through hydrophobic π−π stacking between the DNA bases and the sp2-hybridized carbon atoms of the carbon nanotube. At high salt concentration, however, the DNA molecule adopts a partially folded structure and the ssDNA− SWCNT wrapping gets weakened significantly due to the self-stacking of the DNA bases. Our study can find relevance in CNT mediated gene delivery processes where subsequent unwrapping of the gene from its carrier is anticipated across the cell membrane regulated by an existing salt concentration gradient.

I. INTRODUCTION ssDNA−SWCNT hybrids possess unique physical properties and have been the focus of many research groups over the past few decades because of their applications in nanotube sorting,1 DNA-based nanodevices for gene therapy,2 and biomedicines.3 Zheng et al. reported the first experimental evidence of SWCNT−ssDNA hybrid formation in 2003 and also proposed a theoretical model demonstrating the adhesion of nucleic acids on the surface of carbon nanotubes.4 Initially, the purpose of studying such hybrids was limited to the enhancement of water solubility of carbon based nanomaterials.5 Soon, its unique structural and physicochemical properties caught the attention of the researchers ultimately leading to its widespread applications in the fields of chemical sensing6 and biomedicines.7 Among some of these applications, SWCNT-based field effect transistors (FETs) were shown to be capable of sequence dependent DNA recognition8 and it was proposed that DNA− CNT hybrids could potentially be useful for ultrafast DNA sequencing.9 Ito el al. has shown that dried DNA−SWCNT hybrids exhibit intense photoluminescence.10 Experimentally, the interaction between CNT and DNA has been studied by surface-enhanced infrared absorption spectroscopy with special reference to the A−B conformational change of the DNA molecule.11 In addition to experimental techniques, molecular dynamics (MD) was used extensively for detailed atomistic level interpretation of the interaction between DNA and CNT. Johnson et al. reported the pattern and the energetics of selfassembly of DNA oligonucleotides on CNT surfaces using MD simulations under fully hydrated conditions.12 They highlighted the influence of electrostatic and torsional interactions within the sugar−phosphate backbone on the helical wrapping of © 2015 American Chemical Society

DNA around CNT. An optimal helical wrapping geometry of a DNA−CNT hybrid was suggested by Manohar et al. using a combination of scaling analyses, MD simulations and a simple analytical model in the limit of low ionic strength of the medium.13 The same group determined the binding energy of ssDNA by peeling off the nucleotides from the surface of graphite using atomic force microscopy.14 Yarotski et al. dealt with the topographic imaging of a DNA−CNT hybrid using scanning tunnelling microscopy.15 The stability of a designed peptide−SWCNT hybrid was examined by dispersing the same in binary mixtures containing nucleic acids and surfactants.16 Replica exchange molecular dynamics were performed to calculate the free energy landscape of six distinctly different conformation adopted by the ssDNA adsorbed on the singlewalled carbon nanotube.17 A combined study on the selfassembly of short DNA duplexes on both graphene and CNT arrays within a very short simulation time was also reported by Zhao.18 DNA base sequence and the structural attributes of the CNT are critical in measuring the stability of DNA−CNT hybrids in aqueous solutions. This was demonstrated by Xiao et al. using MD and thermodynamic analyses.19 Neihsial et al. analyzed the binding mechanism of ssDNA and various chiral CNTs and provided evidence for the existence of stable ssDNA−CNT hybrids with a larger HOMO−LUMO gap.20 Spontaneous insertion of ssDNA into the core of CNTs with sufficiently large diameters was related to large van der Waals and hydrophobic driving forces by Gao and co-workers.21 The Received: December 9, 2015 Revised: December 30, 2015 Published: December 30, 2015 455

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nanotube (diameter = 2.15 nm, length = 7 nm) using the nanotube builder utility of VMD 1.9.2.35 We choose the CNT large enough to ensure sufficient sliding length for the ssDNA before attaining the optimal bound state. The carbon atoms of the nanotube are modeled as uncharged Lennard-Jones particles using sp2 parameters from the standard force field directory as reported in the literature.36 Initially the centers of mass (COMs) of ssDNA and the SWCNT are placed 5 nm apart inside a cubic box with dimensions of 10 × 10 × 10 nm3 with the nanotube axis and the DNA helix axis being nearly parallel to each other. Subsequently, the entire simulation box is filled with 32363 TIP3P water molecules and 11 Na+ ions are added for the charge neutralization of the DNA phosphate backbone. This corresponds to the salt concentration of the system to be 18 mM roughly. We carry out a separate MD simulation in the presence of 150 mM NaCl, i.e., the physiologically realistic concentration level of NaCl in living cells.37 For this purpose, we introduce a total number of 90 Na+ and 79 Cl− ions randomly in the system containing 32144 water molecules prepared in the same way as mentioned above. Each of the simulations was carried out at a physiologically relevant temperature of 310 K. The protocols and algorithms for performing molecular dynamics simulations of both the systems are as follows. First, we employ 1000 steps of steepest descent38 energy minimization in order to remove steric clashes between solvent molecules. Next a position-restrained dynamics is carried out on the system at constant volume and temperature (NVT) for 500 ps where the temperature of the system is slowly raised to 310 K using weak 20 kcal/mol Å2 harmonic constraints on the solutes in the initial structure. The system is then equilibrated at constant pressure (1 bar) and temperature (NPT) performed at a temperature of 310 K for 5 ns (0.5 ps time constant for heat bath coupling and 0.5 ps pressure relaxation time). Properties such as pressure, cell volume and density converge to their desired values within this period of equilibration. The NPT step is carried out using a Parrinello−Rahman barostat,39 and the V-rescale thermostat40 is used to keep the temperature of the system constant at 310 K and the system configuration is updated using the leapfrog integrator.41 After that, the production MD run is started for 60 ns. The entire production MD is carried out with a time step of 2 fs, and the informations regarding trajectory, velocity, and energy is stored after each 2 ps for analysis. The minimum image convention42 is used to calculate the short ranged Lennard−Jones interactions. The spherical cutoff distance for both electrostatic as well as van der Waals forces is kept at 1 nm. The SHAKE43 algorithm is used to impose a holonomic constrain on the equilibrium bond distance of the TIP3P water molecules. The long-range electrostatic interactions are calculated using the particle mesh Ewald (PME) method.44 The specific base pairs of interest are tagged as energy groups while starting each MD run. Snapshots for visualizing the trajectories are rendered using VMD.35 Each simulation has been repeated twice for error estimation and the reproducibility of data. An overview of the simulated systems (at 310 K temperature and 1 bar pressure) at two different salt concentrations can be found in Table T1 (Supporting Information).

diameter selectivity of the dynamic encapsulation of ssDNA in multiwalled carbon nanotubes was explored by Cheng and Zhao using steered molecular dynamics.22 Classical as well as quantum mechanical simulations were performed by Santosh et al. to study the unzipping of small interfering RNA (siRNA) by pristine SWCNT.23 Recently, Manna and Pati have also conducted an interesting study highlighting the influence of ssDNA assembly and elongated networks on the stability of DNA−graphene composite materials.24 Because of their high propensity to cross phospholipid cell membranes, carbon based nanomarials are considered as potential candidates for targeted drug25,26 and gene27 delivery. SWCNTs are more suitable in this regard due to the easier internalization and lower toxicity as compared to materials like fullerenes.28 However, the architecture and the ionic environment of the intra and extracellular regions are quite different and the binding of the substrate (ssDNA) and the carrier (SWCNT) are expected to vary according to factors like the salt concentration gradient across the cell membrane. The lesser extent of siRNA unzipping was observed by Santosh et al. at high salt concentration regime where the nucleic acid−CNT binding efficiency was lost significantly due to the higher magnitude of stretch modulus of the siRNA at higher salt concentration.23 However, a detailed atomic level understanding of the interaction between SWCNT and ssDNA at varying ionic strength of the medium still remains elusive. In this paper, we attempt to probe the distributions of nucleobases in a SWCNT−ssDNA hybrid at two different salt concentrations and investigate how they contribute to the change in CNT−DNA binding efficiencies on changing the ionic strength of the medium. We primarily address two issues. First, using fully atomistic MD simulations, we show that the noncovalent interactions (van der Waals and π-stacking) between DNA bases and the graphitic carbon atoms of the SWCNT become reduced, presumably due to the ssDNA molecule adopting a partially folded conformation at a higher salt concentration of the medium. Second, we show how the self-stacking of DNA bases reduces their affinity for sp2-hybridized carbon atoms of the SWCNT at high salt concentration. At a different ionic strength of the medium, the nucleobase−CNT stacking and the ssDNA self-stacking compete and influence the dynamics of a flexible ssDNA chain in the presence of a rigid carbon nanotube. The paper is arranged as follows: In section II, we present the simulation and molecular modeling details, and section III deals with the simulation results. The paper ends with the conclusions in section IV.

II. COMPUTATIONAL DETAILS All the molecular dynamics simulations are performed using GROMACS 5.0.529 with the all atom CHARMM30 force field with CMAP corrections for improved dihedrals of proteins. For our study, we take the well-known DNA sequence 5′CGCGAATTCGCG-3′ (Dickerson Drew dodecamer)31 and the explicit TIP3P water model32 is used to solvate the DNA. The Protein data bank (PDB) file containing the initial coordinates of the DD dodecamer is downloaded (PDB ID 436D) from Brookhaven protein data bank.33 The base sequence of the DNA oligomer is then obtained by separating the complementary B chain from the A chain and capping the 5′ and 3′ phosphate end groups. Hydrogen atoms are then inserted in the initial DNA configuration using the freely available package 3DNA.34 We build the initial periodic structure of a (15 × 15) armchair single-walled carbon

III. SIMULATION RESULTS AND DISCUSSIONS The above snapshots provide primary evidence for the adsorption of the DNA strand on the surface of the carbon nanotube at the end of the production MD run in this study. 456

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Figure 1. VMD35 screenshots of the (a) initial simulation system with ssDNA and SWCNT centers-of-mass (COMs) 5.0 nm apart, (b) structure of ssDNA−SWCNT hybrid after 60 ns of simulation in the presence of 18 mM NaCl, and (c) structure of ssDNA−SWCNT hybrid after 60 ns of simulation in the presence of 150 mM NaCl at 310 K. Both the DNA and the CNT are represented by Licorice models. DNA counterions and water molecules are removed for clarity.

The initial components of the simulations with the ssDNA and the CNT molecule COMs 5 nm apart from each other have been represented in Figure 1a. It is apparent from the above figures that at low salt concentration ssDNA utilizes the maximum accessible surface of the CNT to wrap helically around it (Figure 1b) while at higher salt concentration the ssDNA wraps around the CNT in such a fashion that most of its constituent nucleobases stay away from the surface of the CNT molecule (Figure 1c). A. Formation of Stable Hybrids between ssDNA and SWCNT. To reveal the microscopic picture of the hybrid formation we calculate the time evolution of the center-of-mass (COM) distance (RS) between ssDNA and SWCNT at both salt concentrations. It immediately follows from Figure 2a that ssDNA makes initial contacts with the more rigid SWCNT atoms within 8−9 ns of the simulation at low ionic strength of the medium (black line). The DNA−CNT hybrid formation is initiated around 10 ns of the sampling time when the COM distance approaches approximately 1 nm from the initial separation of 5 nm between the two species. Apparently, the two species reach an optimal bound state within 10 ns and stay there throughout the rest of the simulation (Figure 2a, black line). The situation is slightly different at a higher ionic strength

of the medium. We observe that the initiation of contact formation between the two species is delayed and the RS arrives at the minima around 20 ns of the simulation time (Figure 2a, red line). Moreover, it seems that RS keeps on fluctuating after reaching the optimal bound state for the rest of the simulation time (Figure 2a, red line) indicating a less efficient binding interaction between DNA and CNT in the limit of high ionic strength of the medium. We calculate the average root-mean-square deviation (RMSD) for estimating the conformational deviation of each nucleobases from their native structures. The estimated RMSD covers the whole simulated trajectory excluding hydrogen atoms. Usually, the conformational fluctuations of the bases belonging to an ssDNA increases with increase in salt concentration45 but in the present study the conformational fluctuations of DNA bases are attributed to both their interactions with the graphitic carbon atoms of the CNT as well as the salt present in the system. From our simulations, the average RMSD values for most of the DNA bases are found out to be higher at low salt concentration (Figure 2b, black histograms) since a conformationally flexible ssDNA interacts more strongly with the SWCNT (section III.B) surface while at higher salt concentration of the system majority of the 457

DOI: 10.1021/acs.jpcb.5b12044 J. Phys. Chem. B 2016, 120, 455−466

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Nc(t ) =

∑ ∑ i=1

j=1

∫r

i

ri + 5Å

δ(r(t ) − rj(t ))dr (1)

Where NSWCNT and NssDNA are the total number of atoms in CNT and DNA respectively, and, rj is the distance of the jth atom of the DNA from the ith atom of the CNT. Figure 2c clearly indicates that the close contacts between the two species keep on increasing stepwise throughout the simulation at both the ionic concentrations under study. However, the initiation of contact formation is slower and the DNA takes longer time to bind with the CNT when the salt concentration of the medium is higher. B. Salt concentration dependent interaction energy of DNA segments with CNT. It is well-known that the dynamics of a ssDNA is sensitive toward its ionic environment.46 Similarly, it was shown previously that a combined effect of various noncovalent forces and the electrostatic repulsion between the negatively charged phosphate backbones is responsible for the binding of ssDNA on the surface of SWCNT in the limit of low ionic strength of the medium.13 The above two factors compete with each other at a higher concentration of salt and make the dynamic picture complicated. In order to estimate the feasibility of the interactions between the two species under study we calculate the short-range interaction energies (Eint) between each base residue and CNT averaged over the entire trajectory (Figure 3a). Eint is determined using the electrostatic and van der Waals cut-offs already mentioned in section II. The van der Waals counterpart of the Eint is a sum of dispersive π−π stacking as well as the hydrophobic forces. In order to understand the overall relative binding affinity of DNA and CNT at varying salt concentration we estimate the free energy of binding, F(r) as a function of the intermittent distance between the COMs of DNA and CNT throughout the entire trajectory at two different concentrations (Figure 3b). We employ the following equation to calculate F(r) F(r ) = − kBT ln P(r )

(2)

Where, P(r) is the probability of finding the ssDNA at a given position r from the CNT. Here, r is the distance between the COMs of the DNA and CNT respectively, kB is the Boltzmann constant and T is the temperature of the system. It is to be noted here that we have used the same tools eq 2 used by Mogurampelly et al. for estimating the binding free energy of nucleosides to a graphene substrate47 as more accurate methods for estimating binding free energy such as free energy perturbation48 would be computationally expensive for a large system like ours and is beyond the scope of the present study.Flexible ssDNA molecule adopts different conformations in aqueous solutions depending on the ionic strength of the medium.49 It is evident from Figure 3a that at low salt concentration limit most of the nucleobases are in close proximity of the SWCNT surface and consequently most of the average Eint values are highly negative suggesting a better noncovalent interaction between the two species. However, at 150 mM NaCl concentration the absolute values of Eint are less negative indicating the unwillingness of the nucleobases to participate in interacting with the atoms of the SWCNT strongly. Figure 3b further confirms the weakening of SWCNT− ssDNA interactions in the limit of high salt concentration as the contact pair minima at a distance of around 1.5 nm are −9.1730

Figure 2. (a) Time evolution of the COM distances (RS) between SWCNT and ssDNA and (b) average RMSD for individual base residues of the ssDNA with respect to its native conformation at both concentrations of NaCl. (c) Number of close contacts (Nc) of ssDNA atoms within a cutoff of 5 Å from the CNT surface at both concentrations of NaCl.

nucleobases exhibit lower deviations from its native state (Figure 2b, red histograms) since they prefer to undergo selfstacking (section III.C) induced by a partially compact state adopted by the ssDNA molecule in the limit of excess salt concentration. We corroborate the above observations further with the comparative structural deformations of the ssDNA molecule at two different concentrations of ions by calculating the number of ssDNA atoms that come close to the CNT surface within a specified distance cutoff (Figure 2c). The number of contacts formed between the ssDNA and the SWCNT (Nc) has been computed by imposing a cutoff of 5 Å according to the following expression.23 458

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Figure 3. (a) Average nonbonded interaction energy of individual nucleobases with CNT and (b) the free energy of DNA−CNT binding as a function of the separation between their COMs, respectively.

Figure 4. . Variation of (a, c) the center of mass distance (RS) and (b, d) the interaction energy (Eint) between two nonsequentially stacked base pairs at both the concentrations of NaCl under study.

(±0.0752) and −8.0612 (±0.0413) kJ mol−1 for the black and the red curves, respectively. Standard deviations are calculated from two independent simulations at each salt concentration of the medium. From the above discussion it can be understood that while the nucleobases exhibit very high affinity for CNT usually, in the high salt concentration limit the distribution of DNA bases becomes more heterogeneous restricting the ssDNA to from a stable hybrid with the SWCNT. The contrast in the distribution pattern of nucleobases at two different salt concentrations has been discussed in the next section (section III.C) in detail.

C. Distribution of Nucleobases at Two Different Salt Concentrations. Depending on the charge of the counterion an ssDNA molecule undergoes various conformational changes in aqueous medium.49 In an earlier study, it was shown by Chackraborty et al. that in the presence of salt ssDNA adopts a collapsed coil like state where the DNA bases experience selfstacking or nonsequential stacking, and the lifetime of such selfstacked motifs increases monotonously with increasing salt (NaCl) concentration.50 The dynamics of an ssDNA in the presence of a rigid SWCNT at high salt concentration is not that straightforward as certain nucleobases can alternatively 459

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Figure 5. . Variation of (a, c) the center of mass distance (RS) and (b, d) the interaction energy (Eint) between two sequentially stacked base pairs at both the concentrations of NaCl under study.

more compact or a partially folded state. These self-stacked motifs contribute appreciably to the overall stabilization (both electrostatic as well as van der Waals energies) of the ssDNA (Figure 4, parts b and d) in the high salt concentration limit. It can easily be observed from the above figures that selfstacking of nucleobases is dominant at 150 mM salt concentration as the base pair C1 and G4 gets stacked for almost 33% and C9 and G12 remains stacked for almost 50% of the total simulation time respectively (Figure 4, parts a and c). The corresponding average interaction energy contributions come out in the range of −12.2620 (±0.7441) kJ mol−1 for the pair C1/G4 and −13.0043 (±1.1821) kJ mol−1 for the C9/G12 pair (Figure 4, parts b and d). However, the emergence of such self-stacked motifs does not come into the picture when the salt concentration is low. This is presumably because 18 mM concentration of NaCl is too low to induce the DNA chain compaction and the helical wrapping of ssDNA around the SWCNT seems plausible. It is to be noted that the majority of other nucloebases prefers to undergo self-stacking (e.g., G10G12, and A5-T8) in the presence of 150 mM NaCl but since they exhibit stacking for a very small duration of the simulation they have not been displayed here. As a consequence, interactions of most of the individual nucleobases with the CNT surface gets weakened significantly when higher number of DNA counterions is around (Figure 3a). The sequential connectivity of ssDNA bases is supposed to be affected as well due to its neighboring bases get either absorbed on the surface of SWCNT at a low concentration of salt or they experience self-stacking when the salt concentration is sufficiently high. Thus, the probing of nucleobase distribution

stack with the graphitic carbon atoms of CNT as well as with another nucleobase from the same DNA chain. Both of these interactions are driven by dispersive π−π stacking and are hydrophobic in nature. Additionally, if the DNA bases start getting self-stacked in a compact state of ssDNA the stacking between the sequentially connected base pairs is also expected to be disrupted. Therefore, it is extremely important to probe the distribution of nucleobases appropriately at both concentrations. For this purpose, we monitor the variation of the center of mass distance (RS) between any two base residues, considering only ring atoms. We define two base residues to be stacked (sequentially or nonsequentially) if the calculated RS is ≤0.5 nm.51 It is worth mentioning that by “stacking” we imply the close proximity of two DNA aromatic bases which is only an approximation of the π−π stacking in a true sense since classical force fields cannot take into account factors like electron polarizability and thus underestimate the actual magnitude of π−π stacking. Despite this, efforts have been made to extract π−π stacking accurately by combining nonbonded energy terms (van der Waals) predicted by classical force fields (CHARMM 27 and 36)52,53 with that of quantum mechanical (QM) calculations.54 Therefore, we assume that the nonbonded interaction energies can provide fair approximations to the real π−π stacking, at least qualitatively. In this study, we scanned through all possible combinations of base pairs that do not obey the native DNA sequence connectivity and among them the ones which get stacked prominently throughout the trajectory have been displayed here in Figure 4, parts a and c. We observe that self-stacking typically occurs at 150 mM concentration of NaCl where the ssDNA remains in a 460

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Figure 6. Variation of (a, c, e, and g) the center of mass distances (RS) and (b, d, f, and h) the interaction energy (Eint) between two stacked base pairs at both the concentrations of NaCl under study with time in the absence of CNT. 461

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Figure 7. Variation of the total number of (a) stacked bases (either with CNT or with each other) and (b) self-stacked base pairs in the absence of CNT with time at both the concentrations of NaCl under study.

indeed represents the stacking between two carefully selected base pairs in the absence of CNT and the stacking between some of these base pairs (e.g, T7/C11 and G2/G4) is not observed when the simulations are performed in the presence of CNT. However, the argument of nucleobase stacking still remains inadequate from a standpoint of quantification and clarity. Hence we attempt to quantify the total number of bases either stacked nonsequentially (self-stacked) or to CNT as a function of simulation time at the two indicated salt concentrations. In a similar approach, we also compute the total number of nucleobases stacked to each other as a function of simulation time in the absence of CNT during control simulations. It immediately follows from Figure 7 that the adsorption of nucleobases on the CNT surface and self-stacking compete with each other at the two above salt concentrations and in turn complicates the overall dynamics. It can be seen that at the beginning of the simulation the nucleobases prefer to undergo self-stacking more than interacting with the CNT at both the indicated ionic strengths of the medium (red and pink curves, Figure 7a). This trend is reversed around 35 ns of the simulation when the stacking between CNT and the DNA bases becomes more prominent and it outweighs the propensity of self-stacking at 18 mM concentration of NaCl. As a consequence, 100% of the nucleobases get stacked to CNT while only two self-stacked base pairs remain persistent at the end of the simulation (black and red curves, Figure 7a). However, the relatively higher persistence of self-stacking restricts the number of bases stacked to CNT at a higher ionic strength of the medium. It is apparent from Figure 7a that only 67% of the constituent nucleobases experience stacking with CNT (blue curve) since a higher number of base pairs remains self-stacked (pink curve) at the end of the simulation. The number of self-stacked bases varies unambiguously with time in the absence of CNT at the two indicated salt concentrations (Figure 7b). According to our control simulations, the maximum number of self-stacked motifs comes out to be 12 at the end of the simulation at 150 mM NaCl, which is higher than that observed at a lower salt concentration of the medium where the ssDNA molecule retains a more flexible conformation. F. Spatial Density Distribution Functions. We calculate the spatial density distribution functions (SDF) of the ssDNA around the time−averaged SWCNT at each salt concentration

at different ionic strength of the medium would be incomplete without addressing the dynamics and energetics of sequentially stacked DNA bases (Figure 5). It is quite obvious that the sequential stacking interaction between any two given ssDNA bases gets disrupted in the vicinity of an SWCNT with the concentration of salt in the system playing a vital role toward the stability of such interactions. From the above figures it immediately follows that at 150 mM concentration of NaCl consecutive base pairs such as C3-G4 and C11-G12 do not exhibit stacking almost throughout the whole trajectory (red lines, Figure 5, parts a and c). Destabilization of such sequentially stacked bases might apparently be a combined penalty for the nucleobases having high probability for both self-stacking as well as interacting weakly with the CNT surface and as a result consecutive base pairs hardly exhibit stacking with each other in the limit of high ionic strength of the medium. However, at low concentration of the salt only the strong SWCNT−ssDNA interactions (Figure 3) appear to be responsible for the weakening of the sequentially stacked base pairs and hence the relative persistence of such motifs is energetically more favorable as compared to a system with higher concentration of ions (Figure 5, parts b and d). D. Distribution of Nucleobases in the Absence of CNT. We carry out two additional control simulations of the DNA in the absence of CNT at the two indicated salt concentrations. The purpose of doing so is to compare between the nucleobase distributions with and without CNT and thus making the overall dynamic picture more transparent. We monitor the time evolution of the COM distances (RS) and the corresponding stacking interaction energies (Eint) between two base pairs (sequential or non sequential) in Figure 6 using the same protocols as mentioned in section III.C. The different types of average interaction energy values at different salt concentrations have been tabulated in Table T2 (Supporting Information) for better interpretations and comparisons. E. Quantifying the Population of Stacked Nucleobases. It is apparent from the control simulations that the distribution of the nucleobases is such that they prefer to undergo self-stacking when the salt concentration is sufficiently high irrespective of the presence of the swCNT in the system. However, in the absence of CNT self-stacking is expected to be more dominant since the nucleobases do not see a CNT surface in their vicinity to wrap around anymore. Figure 6a−f 462

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The Journal of Physical Chemistry B using the g_spatial utility of GROMACS 5.0.5,29 which computes the three-dimensional density distribution of a certain species in the vicinity of the other by reading the entire trajectory. The bright green isosurfaces in Figure 8

strength of the medium. This correlates well with the outcomes of section III, parts A and B. Similarly, we compute the SDF of the DNA counterions (Na+) around the time-averaged DNA molecule using the same tools mentioned above. The violet wireframes in Figure 9 represent the SDFs of Na+ separately around the DNA (represented as van der Waals spheres) helix axis at two different salt concentrations. In this case the SDFs are drawn for equal densities (isovalue ∼100) in each case as well. It seems from parts a and b of Figure 9 that a higher number of sodium ions prefer to accumulate around the DNA and bind with it at a higher ionic concentration of the medium despite the presence of the negatively charged chloride ions. This is helpful in understanding the DNA chain compaction when higher number of DNA counterions is around. G. Radial Concentration Profiles of Sodium Ions around the ssDNA. We calculate the radial concentration of Na+ counterions, C(r) as a function of its distance from the COM of ssDNA at each concentration of NaCl according to Yooet al.46 in order to corroborate Figure 9. For computing C(r) at each salt concentration of the system, we divide the volume around DNA into cylindrical shells (r, r + Δr) while r ranges from 0 to rmax of 5 nm, i.e., half of the simulation box length. The number of ions in each shell is averaged over the entire frame of the corresponding MD trajectory. Then we obtain the corresponding cation number density distribution by dividing the number of cations in each shell by the corresponding volume element of the cylindrical cell, 2πrhΔr, where h is the height of the DNA single strand, i.e., ∼ 4.2 nm for the well-known Dickerson Drew dodecamer.55 The cation number density is then converted to radial molar concentration, C(r) as a function of location of cations within the simulation box. In Figure 10, we have provided the radial concentration values up to 3 nm since it converges well within this limit for both the concentrations. Figure 10 suggests that the counterion layer of Na+ around the DNA strand is thicker at a higher concentration of salt. Therefore, the cations are probably more efficient in screening the electrostatic repulsion between the negatively charged

Figure 8. (a and c) Horizontal and (b and d) front views of the SDF of ssDNA (green isosurfaces) around the time-averaged CNT structures (silver van der Waals sphere) at NaCl concentrations of 18 and 150 mM, respectively. The snapshots are rendered using VMD 1.9.2.35 The solvent molecules and ions are ignored for clarity.

represent the SDFs of the ssDNA around the CNT (represented as silver colored van der Waals spheres) axes. For the best display, the SDFs are drawn for equal densities (isovalue ∼50) in each case. It immediately follows from parts a−d of Figure 8 that the distribution of the nucleic acid is relatively more continuous around the carbon nanotube implying a stronger binding between the two at a lower ionic

Figure 9. (a and b) SDFs of Na+ ions (violet wireframes) around the time-averaged ssDNA structures (represented as van der Waals sphere) seen away from the DNA helix axis at NaCl concentrations of 18 and 150 mM respectively. The snapshots are rendered using VMD 1.9.2.35 Carbon nanotube, solvent molecules and the co-ions (Cl−) are ignored for clarity. 463

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functions (SDFs) in section III.F are consistent with the above two findings. The radial concentration profiles of Na+ around the ssDNA also supplement the DNA chain compaction at a higher concentration of salt owing to a larger extent of cation binding to the nucleic acid (section III.G). Simulations have been carried out at two salt concentrations, one that corresponds to the charge neutralized system (18 mM) and the other corresponding to the physiological concentration of NaCl inside living cells (150 mM) keeping in mind that very high concentration of salt may lead to DNA overcharging57 and even DNA precipitation.58 Intermediate salt concentrations have not been taken into account since we believe that the calculated parameters will not change much in comparison with the ones reported here qualitatively. We have performed simulations at 310 K temperature in order to extrapolate relevance to a living cell. Our study finds relevance in the thermal annealing study on the hybrids of mixed dsDNA sequences and CNT by Noh et al. where it has been mentioned that the consideration of salt concentration is imperative for the fabrication of CNT-based biosensors.59 Recently, Zhang et al. has also demonstrated the sensitivity of surface adhesion of a benzoimidazole modified nucleotide to the ion transport through a carbon nanopore.60 Furthermore, functionalized SWCNT has also found promising applications in nonviral DNA delivery vehicles61 where the interplay of the optimal adsorption of the substrate on the carrier, the ability of the hybrid to penetrate the cell membrane and the ultimate release of the gene to the target cell is of paramount importance.62 These steps depend on the salt concentration gradient across the cell membrane, pH, and other physiological conditions.63 Our study may be helpful in understanding the functioning of such CNT-based gene delivery systems which is partly regulated by the ionic environment inside the cell.

Figure 10. Radial concentrations of Na+, C(r) as a function of its distance from the ssDNA COM at both the concentrations of NaCl under study.

phosphate backbone at a higher ionic strength of the medium during the simulation. The higher extent of cation accumulation around the DNA complements the DNA chain compaction which results in a longer lifetime of the self-stacked nucleobase pairs at a higher concentration of salt (section III, parts C and D).

IV. CONCLUSIONS In this paper, using atomistic MD simulations, we address some important factors controlling the stability of ssDNA−SWCNT hybrids at different salt (NaCl) concentrations. A preliminary evidence for weaker interaction between the two species in the limit of higher ionic strength of the medium is obtained from the optimal bound state model (Figure 2a). Subsequently, we explore the feasibility of hybrid formation from free energy calculations and the computation of nonbonded interaction energies between individual nucleobases and CNT (section III.B). We also find that the noncovalent and hydrophobic binding interactions between ssDNA and SWCNT are governed by the distributions of nucleobases which are distinctly different at the two concentrations of salt under study. At low salt concentration, the flexible ssDNA prefers to wrap around the rigid SWCNT prior to the neutralization of the negatively charged phosphate backbone of the ssDNA and thus overcoming the electrostatic repulsion between the phosphate moieties. When excess amount of salt accumulates around the ssDNA in aqueous solution it adopts a more compact/folded state where the nucleobases prefer to undergo self-stacking and thus forcing the bases to distance themselves from the binding sites on the SWCNT surface. As a consequence, the ssDNA−SWCNT interaction gets significantly weakened at high concentration of NaCl. These selfstacked base pairs contribute appreciably to the overall stabilization energies of the ssDNA in the compact state and also affects the arrangement of sequentially stacked base pairs (section III.C). These self-stacked motifs resemble the work of Roxbury et al., where hydrogen bonding between distant base pairs of a DNA oligonucleotide along with the conformational entropy of the system has been shown to be crucial in determining the equilibrium geometry of an ssDNA wrapped on the surface of a SWCNT using extensive REMD technique.56 The calculated spatial density distribution

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcb.5b12044. Brief overview of each of the simulated systems and average interaction energy values for different DNA base−CNT and base−base combinations under various simulation conditions(PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (R.C.). Telephone: + 91-0222576 7152. Fax: + 91-022-2576 7152. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We dedicate this article to Prof. K. L. Sebastian for his seminal contributions in Theoretical Chemistry. We thank the supercomputing facility in the department of Chemistry, Indian Institute of Technology Bombay for providing computer time for carrying out the present work. R.C. thanks SERB (SB/SI/ PC-55/2013), the CSIR (Project No. 01(2781)/14/EMR-II), and IIT Bombay-IRCC (Grant Number: 12IRCCSG046) for funding. SG thanks Mr. M. K. Dixit for valuable discussions. S.G also thanks the CSIR, Government of India, for a senior research fellowship. 464

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