and N-Terminus Cysteine Modified Cecropin P1 Chemically

Article pubs.acs.org/JPCB

Molecular Structures of C- and N‑Terminus Cysteine Modified Cecropin P1 Chemically Immobilized onto Maleimide-Terminated Self-Assembled Monolayers Investigated by Molecular Dynamics Simulation Zunliang Wang,†,‡ Xiaofeng Han,† Nongyue He,*,† Zhan Chen,*,‡ and Charles L. Brooks, III*,‡ †

State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Si Pai Lou 2, Nanjing 210096, China ‡ Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States ABSTRACT: Biosensors using peptides or proteins chemically immobilized on surfaces have many advantages such as better sensitivity, improved stability, and longer shelf life compared to those prepared using physically adsorbed biomolecules. Chemical immobilization can better control the interfacial conformation and orientation of peptides and proteins, leading to better activity of these biomolecules. In this research, molecular dynamics (MD) simulations were employed to systematically investigate the structure and dynamics of surface-tethered antimicrobial peptide cecropin P1 (CP1) modified with a cysteine residue at the C- (CP1c) or N-terminus (cCP1). Such CP1c and cCP1 molecules were chemically immobilized onto a silane-EG4-maleimide selfassembled monolayer (SAM) surface by forming a thio-ether bond between the cysteine group in CP1c or cCP1 and the surface maleimide group. The simulation results showed that the immobilized cCP1 (via the N-terminus) tends to bend and gradually lie down onto the SAM surface, due to the large structural fluctuation of the C-terminus induced by unfavorable interactions between the hydrophobic C-terminal residues and water. Differently, the tethered CP1c (via the C-terminus) more or less stands up on the surface, only tilting slightly even after 60 ns. The simulation results can be well correlated to the recent experimental results obtained from sum frequency generation (SFG) vibrational spectroscopic study. The current simulation data provide more atomic level details on how the hydrophobicity difference in the C-terminus and N-terminus of the amphiphilic peptide can lead to different structures of the same peptide tethered to the surface via different termini. This knowledge can be used to rationally design chemically immobilized peptides to achieve desired structure and functionality.

1. INTRODUCTION Biosensors have been widely applied in many important research areas and practical applications.1−13 The performance of a biosensor (such as sensitivity, selectivity, detection limit, precision, accuracy, reproducibility, working life, and shelf life) is largely determined by interactions between the biosensor probe molecules and the target molecules. Such interactions are mediated by the molecular structure of the biological molecules immobilized/adsorbed on biosensing interfaces. Thus, for a peptide or protein-based biosensor, improved structural stability and optimized surface orientation of the peptide or protein are quite important for the rational design of the biosensor.14,15 For example, when tethered to the surface, the protein or peptide must adopt a stable conformation and a “correct” orientation so that its “active” domain can be easily accessed by targeting molecules. Currently, antibody-based biosensors are widely used to detect a variety of biological molecules and various organisms including bacteria. However, such biosensors have some disadvantages including instability in harsh environments, lack © 2014 American Chemical Society

of batch-to-batch consistency, high cost, and low specificity with the presence of background interference. Also, it is required to have at least one binding pair for every target detected.3 Antimicrobial peptides (AMPs) have naturally evolved into integral components of the immune system of many animals, which have a broad range of biological activity and affinity toward microbial targets and are very stable under harsh environments and adverse conditions.1,2,16−19 They can selectively bind to microbial cell surfaces and disrupt target microbial membranes to exert their antimicrobial functions.3 Due to the above superior characteristics, AMP based microarrays can be used to rapidly detect bacterial and other important microbial pathogens, and have the potential to replace antibody-based biosensors. Received: March 7, 2014 Revised: May 4, 2014 Published: May 6, 2014 5670

dx.doi.org/10.1021/jp5023482 | J. Phys. Chem. B 2014, 118, 5670−5680

The Journal of Physical Chemistry B

Article

adsorbed or immobilized on the surface. Therefore, to observe such a conformational change of the peptide on the SAM surface, ideally the MD simulation should start with a random coil peptide structure. However, simulation of such a peptide folding process on a SAM surface requires covering a very long time scale (on the order of microseconds to milliseconds), which is not feasible.69 Therefore, the starting structure of CP1c used in this work was generated as an α-helix with the cysteine-modified C-terminus covalently bonded to the maleimide group of the SAM surface, with the helix principle axis tilting at ∼10° vs the surface normal. For comparison purposes, we also used the same starting structure for Nterminus immobilized cCP1. Both initial structures of CP1c and cCP1 were constructed with the CHARMM program,70−72 each of which consists of 31 amino acid residues from CP1 (SWLSKTAKKL-ENSAKKRISE-GIAIAIQGGPR), adding a cysteine residue at the C- or N-terminus, respectively. Both the CP1c and cCP1 were considered to have positively and negatively charged N-terminal NH3+ and C-terminal COO− groups, respectively. Lys(K) and Arg(R) residues are positively charged, Glu(E) is negatively charged, and other residues were kept neutral, giving each of the CP1c and cCP1 a total charge of +5. The SAM was constructed with a monolayer of 457 silaneEG 4 -maleimide [(OH) 3 Si(CH 2 ) 2 NH−CONH−EG 4 − (CH2)2N(CO)2C2H2] chains closely packed on a silica substrate at a high density, roughly 4.5 chains/nm2, which corresponds well to the experimental range of 4−5 chains/nm2 for SAM fully covered on silica substrate.73−75 The initial structure of the SAM was built using the CHARMM program.70−72 The maleimide group in the EG4-SAM and the immobilized peptide were modeled using the CHARMM27compatible force field parameters, which were recently developed by Petra Imhof and co-workers.76 The force field parameters for each EG4 unit were directly adopted from the CHARMM27 force field.77,78 All the silicon atoms and the hydroxylated α-quartz(011) slab used for the silica support were modeled using the silica force field developed by Lopes et al.79 This force field has been parametrized to be compatible with the CHARMM27 force field.77,78 Each peptide−SAM system was solvated by a TIP3P80 water box including 23 257 explicit water molecules with a margin of at least 26 Å from the top edge of the water box to the immobilized peptide. The solvated systems were then neutralized by adding 5 Cl ions. Additionally, 2 K+ and 2 Cl ions were added to yield a final concentration of Cl ions of 16 mM, which matches the SFG experimental conditions. The resulting peptide−SAM systems were subjected to an energy minimization procedure to remove unfavorable contacts. This procedure first involved solvent minimization using 100 steps of the steepest descent (SD)70 and 1000 steps of adopted basis Newton−Raphson (ABNR)70 algorithms, with the silicon atoms fixed and the heavy atoms of the solutes (peptide and SAMs) restrained with a harmonic force constant of 40 kcal/mol/Å2. This was followed by five rounds of the SDABNR minimizations, during which the harmonic restraints on the heavy atoms of the peptide−SAM system were then gradually reduced to zero. 2.2. Simulation Protocol. After energy minimization, all simulation systems were then gradually heated from 0 to 300 K in increments of 25 K for every 5 ps, while harmonically constraining the atoms of the peptide backbone and the SAM to their initial positions. This heating process initially relaxed

The activity of surface immobilized AMPs depends on the peptide immobilization method. Mello and her co-workers found that cecropin P1 (CP1) molecules physically adsorbed or chemically immobilized via the C-terminus exhibited very different killing efficiencies against E. coli.20 This difference in activity was believed to be related to the different peptide surface structures induced by different immobilization methods. It was also found that the immobilized CP1 through the Cterminus tethered to the EG4 maleimide SAM has much better LPS binding ability than that bound via the N-terminus, possibly due to different peptide structures.21 The detailed structural differences need to be characterized, since such information is important for understanding the structure− function relationship of immobilized peptides on surfaces, which will be extremely helpful for rational design of biosensors with improved performance in bacterial capturing and killing. A number of studies have been performed to characterize the interfacial structures of immobilized peptides by using circular dichroic (CD) spectroscopy,19 X-ray photoelectron spectroscopy (XPS),19,23 scanning tunneling microscopy (STM),22 electrical impedance spectroscopy (EIS),23 and Fourier transform infrared (FTIR) spectroscopy.19,23 Although these techniques can provide important structural information on immobilized peptides, it is difficult to describe the detailed conformational behaviors of surface-immobilized peptides at the solid/liquid interface at the molecular level and in situ. Recently, sum frequency generation (SFG) vibrational spectroscopy has been developed into a powerful analytical tool with submonolayer sensitivity for investigating molecular structures of various surfaces and interfaces,24−41 including several important biomolecular structures on surfaces and at interfaces.42−48 We have successfully employed SFG to deduce orientations of various peptides and proteins including magainin 2, fibrinogen, GRK2, melittin, alamethicin, and tachyplesin I on various surfaces and interfaces.49−57 Using SFG, we have investigated the molecular structure of CP1 immobilized on EG4 SAM terminated with a maleimide group via C- or N-terminus.58 To ensure chemical immobilization via different termini, each CP1 molecule was modified with a cysteine amino acid at the C-terminus (CP1c) or N-terminus (cCP1), which can form a chemical bond with a maleimide group on the EG4 SAM. We found that the immobilized CP1c exhibited a strong α-helical SFG amide I signal, while the immobilized cCP1 generated a very weak SFG amide I signal.58 The different SFG spectra demonstrated that the surface immobilized CP1c and cCP1 have different structures. However, it is still unclear why immobilization via different termini leads to the varied structures for the essentially same peptide. Molecular dynamics (MD) simulation can offer atomic-level resolution to examine structures of proteins and peptides.59 Extensive theoretical and computational research has been focused on the peptide/protein−surface interactions,60−68 but a clear understanding of how immobilization via different termini can impact the structure of the immobilized peptides is still largely unknown. Here, using all-atom MD simulations, we aim to elucidate in detail the correlation between the peptide structure and the immobilization method, utilizing CP1c and cCP1 peptides as examples.

2. METHOD 2.1. System Setup. It is believed that CP1 has a random coil structure in solution and can form an α-helix after it is 5671



Article

water molecules surrounding each peptide−SAM system. Following this, a full MD run of 60 ns was performed on each simulation system without any restraints on the peptide. All MD simulations in this work were performed with NAMD2.8,81 using the CHARMM27 force field.77,78 Periodic boundary conditions82 were performed on each simulation system. In the two sets of simulations (for the CP1c-SAM and cCP1-SAM systems), the size of each simulation box was approximately 90 × 90 × 128 Å3, and each system contained around 108 080 atoms. All of the MD trajectories were generated using the NVT ensemble at 300 K. During all MD simulations, all silicon atoms were fixed, and all covalent bonds involving hydrogen atoms were constrained using the RATTLE83 method. The velocity Verlet84 method was used to integrate Newton’s equations with a time step of 2.0 fs. The short-range VDW interactions were calculated by the switch function with a cutoff range between 12 and 14 Å. The longrange electrostatic interactions were calculated by the forceshifting function at a cutoff distance of 14 Å. 2.3. Data Analysis. In this work, the coordinates and velocities of the MD trajectories were saved every 2 ps for the MD trajectory analysis. The root-mean-square deviations (RMSDs) of the peptide backbone atoms were used to quantitatively probe the peptide overall structural changes versus its initial structure on surfaces during the entire MD simulation. Here, the RMSD can be calculated by

Figure 1. Orientation angle definition of a peptide immobilized on a SAM surface. A pair of angles, tilt (τ) and rotation (ρ) angles, are used to characterize the peptide orientation. τ is the angle between the molecular principal axis (h) of the peptide and the SAM surface normal, which is the z-axis. ρ is used to denote the rotation of the whole peptide around the surface normal, which is defined as the anticlockwise rotation angle of the current principal-axis vector (h′) of the peptide relative to its starting position (h) around the surface normal.

N

∑i = 1 (ri , t − ri ,0)2

RMSD =

where the principal axis vector h is calculated as the eigenvector with the smallest eigenvalue of the inertia tensor of the peptide Cα atoms and ẑ is the unit vector along the z-axis direction.85,86 ρ denotes the overall peptide rotation around the SAM surface normal, which is defined as the anticlockwise rotation angle of the current principal-axis vector (h′) of the peptide relative to its starting position (h) around the surface normal.85,86 In order to further monitor the vertical movement of CP1c and cCP1 versus the SAM surface, we also calculated the peptide standing height versus the SAM surface, which was defined as the vertical distance of the center of mass (COM) of the backbone atoms from the surface terminal maleimide layer.

N

where ri is the current position of atom i at time t and ri,0 is its initial position at time t = 0 after eliminating the rotational and translational movements of the peptide backbone; N denotes the total number of atoms in each simulation system. The peptide initial position was taken from the starting structure in the MD simulation. The radius of gyration (Rg) of the peptide backbone was used in this work to measure the compactness of peptide overall structure, which is defined as the root-mean-square distance from the center of mass of the peptide to every backbone atom:

3. RESULTS AND DISCUSSION In this research, molecular dynamics simulations have been performed to monitor the structural change of chemically immobilized cecropin P1 via different termini as a function of time. Figure 2 shows several snapshots of CP1c and cCP1 immobilized on the SAM terminated with maleimide groups at different simulation times. Figure 2 shows clearly that the immobilized CP1c and cCP1 exhibit markedly different behaviors, indicating that the same peptide immobilized via different termini on the surface can have different structures, which may imply different activities. For CP1c, the peptide maintains an α-helical structure, even after 60 ns of MD simulation. The orientation of the immobilized CP1c does not vary substantially with the simulation time. It more or less stands up on the surface. Differently, for cCP1, the linear helical structure gradually changed into a bent helix, moving toward the surface with some unwinding. More details on the structural changes of cecropin P1 immobilized on the surface via different termini can be revealed using the detailed data analysis presented below. 3.1. Conformational Dynamics of the Immobilized Peptides on the SAM Surface. In the present simulation, the initial peptide structure for each system is an extended α-helical

N

Rg =

∑i = 1 mi(ri − rCOM)2 N

∑i = 1 mi

where N is the number of atoms, mi and ri denote the mass and position of the backbone atom i, respectively, and rCOM is the center-of-mass position of the peptide. To evaluate the exposure of the overall peptide structure to water, we calculated the solvent accessible surface area (SASA) of the peptides using a probe of radius 0.14 nm. To further characterize the local exposure of each peptide to water, the average solvent accessible area of every peptide residue was also calculated. The orientational behavior of immobilized peptides on the SAM surface can be characterized by a pair of orientational angles, tilt (τ) and rotation (ρ) angles, as illustrated by Figure 1. τ is the angle between the principal axis (h) of the peptide structure and the SAM surface normal (which is along the zaxis), and this angle is defined by τ = cos−1

h·ẑ |h| 5672



Article

that the structural deviation of each peptide was largely correlated with its immobilization terminus, which is in agreement with the final state of the peptide in the simulation as presented in Figure 2. To further examine the local conformational change of each amino acid residue in both CP1c and cCP1, the residue-based root-mean-square fluctuations (RMSFs) of the backbone Cα atoms were calculated, which were averaged over the last 20 ns in the simulation, as shown in Figure 4. It can be clearly seen

Figure 4. Root mean square fluctuations (RMSFs, a measure of the average atomic mobility) of the backbone Cα atom of each amino acid residue in CP1c (green) and cCP1 (red) immobilized on the SAM surface, averaged over the last 20 ns of MD simulation time.

Figure 2. Snapshots of (a) C-terminus immobilized CP1c and (b) Nterminus immobilized cCP1on maleimide terminated SAM surface at 0 ns (left panel) and 60 ns (right panel), respectively. In each peptide, every hydrophobic amino acid residue is colored in red and every hydrophilic (polar) amino acid residue is colored in green; water and ions have been omitted for clarity. Data visualization is done using VMD1.9.87

that both CP1c and cCP1 show smaller RMSFs for the residues near the immobilized end (C-terminus in the case of CP1c and N-terminus in the case of cCP1). Relatively larger fluctuations for the free end residues were observed, as shown in Figure 4. This indicates that the free end residues are much more flexible than the residues near the immobilized end. Differently, the central residues (ENSAKKRISE) in cCP1 exhibited much larger RMSFs compared to those in CP1c, suggesting that cCP1’s central residues underwent a much larger conformational change. Meanwhile, this result also implies that the major contribution to the conformational change of immobilized cCP1 comes from its free C-terminal and central segment. Moreover, from the average RMSF curve, we clearly found that the free terminal of cCP1 (C-terminal, GIAIAIQ) exhibits more structural flexibilities than that of CP1c (N-terminal, SKTAKKL), due to its much stronger hydrophobic interaction, while its immobilized terminal (N-terminal, WLSKTA) shows more structural stabilities than that of CP1c (C-terminal, AIQGGP), due to its more balanced hydrophobic−hydrophilic interaction. Through the above comparison of the RMSD and RMSF evolutions for CP1c and cCP1, we can conclude that (i) the surface immobilization strategy can affect the conformational dynamics of the immobilized peptide. For example, the Cterminus immobilized peptide (CP1c) more likely adopts an extended α-helical conformation on the SAM surface compared to cCP1, and (ii) the overall conformational change is primarily determined by the movements of the free terminal and the central segment of the peptide. The above results obtained from molecular dynamics simulation are well correlated to our recent SFG experimental observations.58 The SFG spectra collected from immobilized CP1c show a strong α-helical signal, while no SFG amide I signal was detected from immobilized cCP1, which is believed to adopt a random coil conformation or a helical structure with a lying down or bent conformation. The dynamical behavior of

conformation as described in the system setup. In order to quantitatively monitor the global conformational change and structural stability of CP1c and cCP1 immobilized via different termini, we show the time evolutions of the root-mean-square deviations (RMSDs) of the backbone atoms in both CP1c and cCP1 in Figure 3. It can be seen that the structural deviation of

Figure 3. Time evolutions of the root-mean-square deviations (RMSDs) of the backbone atoms in CP1c (green) and cCP1 (red) with respect to their initial structures in the MD simulation.

each peptide was clearly related to its immobilization terminus. As shown in Figure 3, CP1c does not exhibit substantial RMSD change during the entire 60 ns MD simulation time, indicating that it experiences relatively small conformational changes, and keeps its initial extended conformation on the SAM surface throughout the 60 ns simulation. In contrast, the RMSD of cCP1 sharply increased to 12 Å after ∼27 ns, indicating that it underwent substantial conformational changes on the SAM surface in the 60 ns MD simulation time. This result indicates 5673



Article

3). The time evolution of SASA for the cCP1 shows a similar trend with the Rg curve during the time period of 20−35 ns, indicating that the exposure of the peptide to water also decreased with its structure gradually becoming more compact. In contrast, both the size and water exposure of CP1c remain relatively stable during the entire 60 ns MD simulation time, which is also well correlated to its higher conformation stability described above. When immobilized onto a surface, the water exposure of an antimicrobial peptide has an impact on the activity of the peptide, since it may be related to the fact of whether the peptide can be easily accessible by target molecules, which has been proved to be a key factor for biosensor application.16 Therefore, the above observations on entire peptide dynamic changes further imply that the antimicrobial activity of the immobilized peptide is related to its immobilization strategy. The differences in average SASA values per residue between the CP1c and cCP1 along the surface normal are shown in Figure 6. In the free end, the SASA values of the amino acid residues (C-terminus) of cCP1 are smaller than those of the amino acid residues (N-terminus) of CP1c, indicating that the free end amino acid residues of cCP1 are much more hydrophobic with a much more compact structure compared to CP1c. Conversely, in the immobilized end, the SASA values of the amino acid residues (N-terminus) of cCP1 are larger than those of the amino acid residues (C-terminus) of CP1c, indicating that the amino acid residues of CP1c are much more hydrophobic with a more compact structure. These results indicate that, for CP1, choosing different immobilization termini can lead to different hydrophobic and hydrophilic effects on the free end and the immobilized end of the immobilized peptide. 3.2. Orientation Preferences of the Immobilized Peptide on the SAM Surface. As mentioned above, there could be a significant difference in the dynamic behavior of immobilized CP1c and cCP1. Therefore, it is interesting to further examine the detailed movement of the two peptides immobilized via different termini. Analysis of the orientation and the distance between the immobilized peptide and the

the cCP1 may be primarily due to the unfavorable interaction between the hydrophobic C-terminal residues and the aqueous environment. To characterize the dynamic changes of the entire peptide, we displayed the time evolution of the radius of gyration (Rg) and SASA of CP1c and cCP1 obtained from our MD simulation in Figure 5 (a) and (b), respectively. As shown in

Figure 5. Time evolutions of (a) the radius of gyration (Rg) of the backbone atoms and (b) the solvent accessible surface area (SASA) of CP1c (green) and cCP1 (red).

Figure 5, both Rg and SASA decrease with increasing simulation time for cCP1, indicating that cCP1 tends to form a more compact peptide structure in water. For cCP1, a rapid decrease in size in the 20−35 ns time range is significant and consistent with the sharp jump that occurred in the RMSDs (see Figure

Figure 6. Residue-based average SASAs of the CP1c (left panel, green line) and cCP1 (right panel, red line), averaged over the last 20 ns of the MD simulation. 5674



Article

indicates that the bottom side of cCP1 is less dynamic than that of CP1c. This result further confirms the much smaller RMSFs in the bottom side of cCP1, as shown in Figure 4. Figure 8 shows the time evolutions of the distance between the SAM surface and center of mass of the backbone atoms

SAM surface can provide the movement details of CP1c and cCP1 immobilized on the SAM surface. In the present MD simulation, the orientation of an immobilized peptide can be well characterized by giving a pair of orientation angles {τ, ρ}the tilt and rotation angles with respect to the SAM surface normal (see the Data Analysis section and Figure 1). Figure 7a shows the time evolution of the peptide tilt angle with respect to the SAM surface normal during the entire 60 ns

Figure 8. Distances between the SAM surface and the center of mass (COM) of the backbone atoms as a function of time for CP1c (green) and cCP1 (red) during the MD simulation.

along the surface normal (the z-axis) for cCP1 and CP1c. As shown in Figure 8, for cCP1, the distances between the peptide and the SAM gradually decreased to ∼14 Å from 30 Å between 5 and 53 ns, and finally, the distance remained at 14 Å steadily until the end of the 60 ns simulation time, indicating that the cCP1 changed its initial upright orientation, and moved toward the SAM surface during this period of time. Differently, the CP1c primarily remained at a constant distance of ∼30 Å with a small fluctuation of 2.5 Å during the entire 60 ns simulation time (Figure 8, green line). This observation suggests that cCP1 tends to tilt away from the surface normal and move toward the SAM surface. This leads to the change of its upright orientation during the entire MD simulation time, while the CP1c does not exhibit substantial tilt toward the surface. Overall, the relatively stable orientational behavior of CP1c on the SAM surface can be largely attributed to the effect of the hydrophobic−hydrophilic balance from its amphiphilic Nterminal segment. The bending and lying down preference of cCP1 on the SAM surface could be interpreted by the strong hydrophobic interaction of its free end C-terminal residues. Thus, the C-terminal segment tended to adopt a more energetically favorable orientation in order to avoid unfavorable exposure of its hydrophobic sides to water. The resulting overall structure and orientation were accordingly adjusted to accommodate the free end C-terminal hydrophobic fluctuation, and thus finally oriented toward the surface. This MD simulation result indicates that both CP1c and cCP1 have their preferred orientations, due to the different free end hydrophobic interaction when immobilized onto the surface via different termini. Therefore, we believe that immobilization of peptides via different termini significantly impacts the immobilized peptide orientational changes on the SAM surface, which are mainly due to the different hydrophobicities between the peptide’s C- and N-terminal segments with different amino acid compositions. 3.3. Comparison of the Secondary Structure of the Immobilized Peptides. For both CP1c and cCP1, since the C-terminal movement can result in peptide structural and orientational change of the peptide immobilized on the SAM surface, it is also interesting to examine the dynamic variations of the local secondary structure of the peptide on SAM. Figure

Figure 7. Time evolutions of the orientation angles of CP1c (green line) and cCP1 (red line) relative to the surface normal deduced from the MD simulation data.

MD simulation time. For cCP1, τ fluctuated around 10° with a small amplitude of ∼5° within the first 5 ns, then it increased up to 40° with a large fluctuation of ∼20° between 5 and 41 ns; after 41 ns, it sharply increased to 85° between 41 and 51 ns, and finally, it remained at 85° with a slight fluctuation along the remaining MD simulation time (Figure 7a, red line). This indicates that cCP1 reoriented away from its original upright state and finally lied down onto the SAM surface. For CP1c, however, τ appears to be quite stable, fluctuating around 10° with a relatively small amplitude of ∼10° (Figure 7a, green line), indicating that the orientation of immobilized CP1c primarily remains in its initial upright orientation with respect to the SAM surface during the entire 60 ns MD simulation time. These orientation analysis results of CP1c and cCP1 are also consistent with the snapshots shown in Figure 2. Figure 7b shows the time evolution of the peptide rotation angle ρ around the surface normal vector during the 60 ns MD simulation time. It can be clearly observed that the C-terminus immobilized CP1c exhibits a much stronger rotation with a large fluctuation range of 180° around the SAM surface normal, mainly due to the C-terminal hydrophobic fluctuation after the peptide was immobilized via the C-terminus. In contrast, the Nterminus immobilized cCP1 rotated about the SAM surface normal only slightly with a small amplitude fluctuation of 5° away from the SAM surface, due to its more stable bottom segment (N-terminus). This observation from our simulation 5675



Article

9 shows the fraction of the α-helical contents (here defined as α-helicity) in the entire and different segments of CP1c and

segment; however, for cCP1, the large structural changes occurred not only in its C-terminal segment but also in its central segment; (ii) α-helical structure is still the dominant structure for both CP1c and cCP1 after immobilization, but the entire helicity of CP1c is higher than that of cCP1; (iii) during the entire MD simulation time, both CP1c and cCP1 may also adopt other secondary structures such as random coiled or turn-like structure. Therefore, in order to observe the detailed changes of the peptide secondary structures, the fraction of the turn structures formed in CP1c and cCP1 was calculated as a function as time (Figure 10). It can be seen that the fraction of

Figure 9. α-Helicity of the residues of (a) the entire peptide, (b) the C-terminal sequence (GIAIAIQGGPR), (c) the central sequence (ENSAKKRISE), and (d) the N-terminal sequence (SWLSKTAKKL) in cCP1 (left panel, red line) and CP1c (right panel, green line) as a function of time. Here, the α-helicity is defined as a fraction of αhelical content in each peptide structure.

cCP1 on the SAM surface as a function of simulation time, calculated by the STRIDE program in VMD 1.9.87 For the two simulation systems, as shown in Figure 9a, the α-helicity of CP1c (right, green line) appears to be much higher than the cCP1 (left, red line), indicating its α-helical structure is more stable than that of cCP1. The N-terminal segment of each peptide primarily retained a higher value of α-helicity (within 0.8−1.0), indicating the α-helical content in the N-terminal segment was well maintained for both CP1c and cCP1 during the entire 60 ns MD simulation time, as shown in Figure 9d. Meanwhile, Figure 9b shows that the C-terminal segment αhelicity of each peptide displayed a much larger fluctuation after 10 ns, indicating that the conformational transitions occurred near the C-terminus, which is mainly caused by its strong hydrophobic movements. As shown in Figure 9c, the α-helicity of the central residues of cCP1 rapidly decreased to 0.2 with large fluctuations between 0.2 and 0.8 after 27 ns of simulation, while the central segment of CP1c remained almost a perfect αhelical structure. For cCP1, the large variation of the α-helicity of the central segment is mainly due to its free end C-terminal hydrophobic interaction, which could lead to the overall conformational change. This simulation result suggests that the free end C-terminus hydrophobic interaction in cCP1 has a much larger impact on the secondary structure of the central segment than that in CP1c, since the free end C-terminus in cCP1 has a much higher conformational freedom. The difference of the α-helical contents in the central segment of the two peptides is consistent with the comparative result of the central part RMSFs, as shown in Figure 4. Overall, the comparison of the α-helical contents for CP1c and cCP1 reveals that (i) the relative large structural fluctuations in CP1c are only confined in its C-terminal

Figure 10. Fraction of the turn content in the (a) entire sequence, (b) C-terminal sequence (GIAIAIQGGPR), (c) central sequence (ENSAKKRISE), and (d) N-terminal sequence (SWLSKTAKKL) of cCP1 (left panel, red line) and CP1c (right panel, green line) as a function of time during the MD simulation.

the turn structures formed on both structures of the cCP1 and CP1c peptides is small during the entire 60 ns simulations, as shown in Figure 10a. Meanwhile, from Figure 10b to d, we further found that the turn structure was mainly formed in the C-terminal and central segment for cCP1, while the turn structure mainly occurred in the C-terminal segment for CP1c. This result also indicates that, in the case of cCP1, turn structure formed at the C-terminus and the central segment can lead to a distinct decrease in the α-helicity. In the case of CP1c, the decreased α-helicity is only related to the C-terminal turn structure. To better gain insight into the local secondary structural changes, we illustrated the time evolution of the backbone dihedral angles φ and ψ versus each amino acid residue position, excluding the three terminal amino acid residues (the Ser1, Arg31, and modified Cys), averaged over the entire 60 ns MD simulation in Figure 11. In the case of CP1c, regardless of the C-terminal sequence QGGP, the overall average dihedral angles are φ = −59° and ψ = −40°, which is within the angle range for an α-helix, indicating that the local α-helical content of CP1c was well retained except for the C-terminal residues. This result is consistent with the previous analysis on the overall secondary structure. In the case of cCP1, the peptide structure exhibited a similar backbone dihedral angle 5676



Article

dihedral angle ψ for the Ser13 and Glu20 residues of cCP1 in parts a and b of Figure 12, respectively. It can be seen that the ψ values of the residue Ser13 at the first 27 ns fall in the α-helical angle region (−70° < ψ < −15°), indicating that the residue remains α-helical during this period. Between 27 and 55 ns, the ψ value shifted outside of the α-helical angle region, indicating that the Ser13 tends to adopt a different structure (turn structure) during this period of time. The ψ temporarily returned to the α-helical angle region at 57 ns. Finally, the ψ moved away from the α-helical region again. This result reveals that the residue Ser13 is not in helix but retains a turn-like structure after 30 ns of MD simulation time. The residue Glu20 also experienced similar structural changes as Ser13 after 30 ns of MD simulation. The structural changes of Ser13 and Glu20 can also be demonstrated by the snapshots from the MD simulation (Figure 12c). It can be seen that the big turns formed at Ser13 and Glu20 caused the cCP1 overall structure to become bent gradually toward the SAM surface. For both CP1c and cCP1, the free end terminal segment greatly impacts the structure of the entire immobilized peptide on the SAM surface. For the N-terminus immobilized cCP1, driven by the strong movement of the hydrophobic C-terminus, the central segment bent toward the SAM surface, leading to its local α-helical content decreasing sharply after 27 ns. For CP1c, its overall structure retains a much larger α-helical content (compared to cCP1), although the bottom immobilized Cterminus fluctuation can also lead to the temporary loss of αhelical contents (Figure 10), but its effect is local. Therefore, the α-helical contents of CP1c and cCP1 could be reduced by their strong C-terminal hydrophobic motion, but in different degrees.

Figure 11. Time evolution of the dihedral angles (a) φ and (b) ψ versus each amino acid residue position along the backbones of CP1c (green) and cCP1 (red), averaged over the whole MD simulation time duration.

distribution with CP1c for most amino acid residues. However, it displayed distinctly different backbone dihedral angles for its two central amino acid residues, Ser13 (φ = −84.9°, ψ = −3.6°) and Glu20 (φ = −96.8°, ψ = −2.8°), which are out of the angle range for an α-helix, indicating that the turn structure can be formed by these two residues. To further observe the local structural variations of the two residues, we showed the time evolution of the backbone

4. CONCLUSION In the present work, by using all-atom molecular dynamics simulation, we systematically studied the effects of different termini immobilization methods on the structure and

Figure 12. Backbone dihedral angle ψ (a measure of the N−N distance between two neighboring amino acids) of (a) Ser13 and (b) Glu20 residues in cCP1 as a function of time. The allowed α-helical region for the selected amino acid residues is taken to be −70° < ψ < −15°. The bottom panel (c) shows the representative turn configurations from the MD simulations for cCP1, rendered by VMD1.9.87 In each peptide structure, the residues Ser13 and Glu20 are colored in blue, the hydrophobic amino acid residues are in red, and the hydrophilic (polar) amino acid residues are colored in green. 5677


The Journal of Physical Chemistry B orientation of the immobilized antimicrobial peptide cecropin P1 on the SAM surface. Our MD simulations of the CP1c and cCP1 monomers immobilized on the SAMs via C-terminus and N-terminus respectively showed that CP1c largely retained an upright standing orientation relative to the SAM surface with a stable α-helical conformation during the entire 60 ns of simulation. Differently, the cCP1 lost the original upright orientation and tended to bend and gradually laid down onto the SAM surface. The different behaviors of CP1c and cCP1 indicate that immobilization via different termini can lead to different peptide structures and orientations on the SAMs. We have performed similar simulations on the peptide with a perpendicular starting orientation on surfaces at different temperatures of 310, 320, 350, and 400 K, all of which showed similar peptide behavior as that deduced from the MD runs at 300 K. We believe that these simulations are sufficient to confirm that our result obtained from the simulations carried out at 300 K is reliable. This MD simulation result can be well correlated to our recent SFG experimental observation that the CP1c displayed a very strong α-helical SFG signal which reflected an upright orientation with an ∼35° incline versus the surface normal deduced from its spectral fitting results. The cCP1 adopts a different structure, evidenced by its very weak SFG spectra signal. MD simulations can provide more details regarding the immobilized peptide structures and underlined mechanisms. Our MD simulation results revealed that the preferred structural and orientational behaviors of the CP1c and cCP1 are mainly driven by the different interactions of the peptide free end (N-terminus or C-terminus) with water because of their different amino acid sequences. For cecropin P1, the Cterminus is much more hydrophobic than the N-terminus. Thus, when immobilized via the C-terminus, the free Nterminal segment has a more balanced hydrophobic−hydrophilic interaction with water, resulting in a much higher structural stability. In contrast, when immobilized via the Nterminus, the structure and orientation of cCP1 are easily changed driven by the unfavorable interactions between the free C-terminal end and water. Moreover, the C-terminal segment of cCP1 shows an overwhelming influence on the central helical region. Our findings obtained from the previous SFG experiments indicate that the peptide immobilized via different termini has varied structures, resulting in different function and activity.58 MD simulations presented here not only can support our current SFG experimental observations but also can provide an atomic-level description for structural dynamics of CP1 peptide immobilized onto surfaces via different termini. The simulation result will contribute to enhance our understanding on how immobilization strategy can affect peptide structure and behavior on surfaces. Such information will aid in the rational design and development of immobilized peptides with desired structure and activity.

■

■

ACKNOWLEDGMENTS

■

REFERENCES

Article

The research was supported by the National Key Program for Developing Basic Research of China (2010CB933903 and 2014CB744501), the National Natural Science Foundation of China (61271056 and 21303015), the Priority Academic Program Development of Jiangsu Higher Education Institutions (1107037001), and U.S. Army Research Office (W911NF-111-0251). We also acknowledge Shanghai Supercomputer Center for providing computing resources.

(1) Kulagina, N. V.; Anderson, G. P.; Ligler, F. S.; Shaffer, K. M.; Taitt, C. R. Antimicrobial Peptides: New Recognition Molecules for Detecting Botulinum Toxins. Sensors 2007, 7, 2808−2824. (2) Kulagina, N. V.; Shaffer, K. M.; Anderson, G. P.; Ligler, F. S.; Taitt, C. R. Antimicrobial Peptide-based Array for Escherichia Coli and Salmonella Screening. Anal. Chim. Acta 2006, 575, 9−15. (3) Kulagina, N. V.; Lassman, M. E.; Ligler, F. S.; Taitt, C. R. Antimicrobial Peptides for Detection of Bacteria in Biosensor Assays. Anal. Chem. 2005, 77, 6504−6508. (4) Ulevitch, R. J. Therapeutics Targeting the Innate Immune System. Nat. Rev. Immunol. 2004, 4, 512−520. (5) North, S. H.; Wojciechowski, J.; Chu, V.; Taitt, C. R. Surface Immobilization Chemistry Influences Peptide-based Detection of Lipopolysaccharide and Lipoteichoic Acid. J. Pept. Sci. 2012, 18, 366−372. (6) Mannoor, M. S.; Zhang, S.; Link, A. J.; McAlpine, M. C. Electrical Detection of Pathogenic Bacteria via Immobilized Antimicrobial Peptides. Proc. Natl. Acad. Sci. U.S.A. 2010, 107, 19207−19212. (7) Nakayama, H.; Manaka, T.; Iwamoto, M.; Kimura, S. Vertical Orientation with a Narrow Distribution of Helical Peptides Immobilized on a Quartz Substrate by Stereocomplex Formation. Soft Matter 2012, 8, 3387−3392. (8) Johnson, S.; Evans, D.; Laurenson, S.; Paul, D.; Davies, A. G.; Ko Ferrigno, P.; Wälti, C. Surface Immobilised Peptide Aptamers as Probe Molecules for Protein Detection. Anal. Chem. 2008, 80, 978−983. (9) Houseman, B. T.; Huh, J. H.; Kron, S. J.; Mrksich, M. Peptide Chips for the Quantitative Evaluation of Protein Kinase Activity. Nat. Biotechnol. 2002, 20, 270−274. (10) Zaytseva, N. V.; Goral, V. N.; Montagna, R. A.; Baeumner, A. J. Development of a Microfluidic Biosensor Module for Pathogen Detection. Lab Chip 2005, 5, 805−811. (11) Kato, R.; Kaga, C.; Kunimatsu, M.; Kobayashi, T.; Honda, H. Peptide Array-based Interaction Assay of Solid-bound Peptides and Anchorage-dependant Cells and its Effectiveness in Cell-adhesive Peptide Design. J. Biosci. Bioeng. 2006, 101, 485−495. (12) Shriver-Lake, L. C.; North, S. H.; Dean, S. N.; Taitt, C. R. In Designing Receptors for the Next Generation of Biosensors; Piletsky, S. A., Whitcombe, M. J., Eds.; Springer-Verlag: Berlin, Germany, 2013; pp 85−104. (13) Lesaicherre, M. L.; Uttamchandani, M.; Chen, G. Y.; Yao, S. Q. Developing Site-Specific Immobilization Strategies of Peptides in a Microarray. Bioorg. Med. Chem. Lett. 2002, 12, 2079−2083. (14) Ivanov, I. E.; Morrison, A. E.; Cobb, J. E.; Fahey, C. A.; Camesano, T. A. Creating Antibacterial Surfaces with the Peptide Chrysophsin-1. ACS Appl. Mater. Interfaces 2012, 4, 5891−5897. (15) Nowinski, A. K.; Sun, F.; White, A. D.; Keefe, A. J.; Jiang, S. Sequence, Structure, and Function of Peptide Self-Assembled Monolayers. J. Am. Chem. Soc. 2012, 134, 6000−6005. (16) Gregory, K.; Mello, C. M. Immobilization of Escherichia coli Cells by Use of the Antimicrobial Peptide Cecropin P1. Appl. Environ. Microbiol. 2005, 71, 1130−1134. (17) Zhang, L.; Falla, T. J. In Antimicrobial Peptides: Methods and Protocols; Giuliani, A., Rinaldi, A. C., Eds.; Methods in Molecular Biology, Vol. 618; Humana: New York, 2010; pp 303−327. (18) Mello, C. M.; Soares, J. In Membrane selectivity of antimicrobial peptides. in Microbial Surfaces; Camesano, T. A., Mello, C. M., Eds.;

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. Phone: 86-25-83790885. *E-mail: [email protected]. Phone: 1-734-615-4189. *E-mail: [email protected]. Phone: 1-734-647-6682. Notes

The authors declare no competing financial interest. 5678



Article

(41) Rao, Y.; Comstock, M.; Eisenthal, K. B. Absolute Orientation of Molecules at Interfaces. J. Phys. Chem. B 2006, 110, 1727−1732. (42) Fu, L.; Ma, G.; Yan, E. C. Y. In Situ Misfolding of Human Islet Amyloid Polypeptide at Interfaces Probed by Vibrational Sum Frequency Generation. J. Am. Chem. Soc. 2010, 132, 5405−5412. (43) Fu, L.; Xiao, D.; Wang, Z.; Batista, V. S.; Yan, E. C. Y. Chiral Sum Frequency Generation for In Situ Probing Proton Exchange in Antiparallel β-Sheets at Interfaces. J. Am. Chem. Soc. 2013, 135, 3592− 3598. (44) Weidner, T.; Breen, N. F.; Li, K.; Drobny, G. P.; Castner, D. G. Sum Frequency Generation and Solid-state NMR Study of the Structure, Orientation, and Dynamics of Polystyrene-adsorbed Peptides. Proc. Natl. Acad. Sci. U.S.A. 2010, 107, 13288−13293. (45) Weidner, T.; Apte, J. S.; Gamble, L. J.; Castner, D. G. Probing the Orientation and Conformation of α-Helix and β-Strand Model Peptides on Self-Assembled Monolayers Using Sum Frequency Generation and NEXAFS Spectroscopy. Langmuir 2010, 26, 3433− 3440. (46) Mermut, O.; Phillips, D. C.; York, R. L.; McCrea, K. R.; Ward, R. S.; Somorjai, G. In situ Adsorption Studies of a 14-amino Acid Leucine-lysine Peptide onto Hydrophobic Polystyrene and Hydrophilic Silica Surfaces Using Quartz Crystal Microbalance, Atomic Force Microscopy, and Sum Frequency Generation Vibrational Spectroscopy. J. Am. Chem. Soc. 2006, 128, 3598−3607. (47) Roeters, S. J.; van Dijk, C. N.; Torres-Knoop, A.; Backus, E. H. G.; Campen, R. k.; Bonn, M.; Woutersen, S. Determining in Situ Protein Conformation and Orientation from the Amide-I Sumfrequency Generation Spectrum: Theory and Experiment. J. Phys. Chem. A 2013, 117, 6311−6322. (48) Li, H.; Ye, S.; Wei, F.; Ma, S.; Luo, Y. In Situ Molecular-level Insights into the Interfacial Structure Changes of Membraneassociated Prion Protein Fragment [118−135] Investigated by Sum Frequency Generation Vibrational Spectroscopy. Langmuir 2012, 28, 16979−16988. (49) Nguyen, K. T.; King, J. T.; Chen, Z. Orientation Determination of Interfacial β-Sheet Structures in Situ. J. Phys. Chem. B 2010, 114, 8291−8300. (50) Ye, S.; Nguyen, K. T.; Boughton, A. P.; Mello, C. M.; Chen, Z. Orientation Difference of Chemically Immobilized and Physically Adsorbed Biological Molecules on Polymers Detected at the Solid/ Liquid Interfaces in Situ. Langmuir 2009, 26, 6471−6477. (51) Nguyen, K. T.; Clair, S. V. L; Ye, S.; Chen, Z. Molecular Interactions between Magainin 2 and Model Membranes in Situ. J. Phys. Chem. B 2009, No. 113, 12358−12363. (52) Boughton, A. P.; Andricioaei, I.; Chen, Z. Surface Orientation of Magainin 2: Molecular Dynamics Simulation and Sum Frequency Generation Vibrational Spectroscopic Studies. Langmuir 2010, 26, 16031−16036. (53) Yang, P.; Ramamoorthy, A.; Chen, Z. Membrane Orientation of MSI-78 Measured by Sum Frequency Generation Vibrational Spectroscopy. Langmuir 2011, 27, 7760−7767. (54) Han, X.; Soblosky, L.; Slutsky, M.; Mello, C.; Chen, Z. Solvent Effect and Time-Dependent Behavior of C-Terminus-CysteineModified Cecropin P1 Chemically Immobilized on a Polymer Surface. Langmuir 2011, 27, 7042−7051. (55) Boughton, A. P.; Yang, P.; Tesmer, V.; Ding, B.; Tesmer, J.; Chen, Z. Heterotrimeric G protein β1γ2 subunits change orientation upon complex formation with G protein-coupled receptor kinase 2 (GRK2) on a model membrane. Proc. Natl. Acad. Sci. U.S.A. 2011, 108, E667−673. (56) Ye, S.; Li, H.; Wei, F.; Jasensky, J.; Boughton, A. P.; Yang, P.; Chen, Z. Observing a Model Ion Channel Gating Action in Model Cell Membranes in Real Time in Situ: Membrane Potential Change Induced Alamethicin Orientation Change. J. Am. Chem. Soc. 2012, 134, 6237−6243. (57) Nguyen, K. T.; Clair, S. V. L; Ye, S.; Chen, Z. Orientation Determination of Protein Helical Secondary Structure Using Linear and Nonlinear Vibrational Spectroscopy. J. Phys. Chem. B 2009, 113, 12169−12180.

ACS Symposium Series 984; American Chemical Society: Washington, DC, 2008; pp 52−62. (19) Dathe, M.; Wieprecht, T. Structural Features of Helical Antimicrobial Peptides: Their Potential to Modulate Activity on Model Membranes and Biological Cells. Biochim. Biophys. Acta 1999, 1462, 71−87. (20) Soares, J. W.; Kirby, R.; Morin, K. M.; Mello, C. M. Antimicrobial Peptide Preferential Binding of E. coli O157:H7. Protein Pept. Lett. 2008, 15, 1086−1093. (21) Uzarski, J. R.; Mello, C. M. Detection and Classification of Related Lipopolysaccharides via a Small Array of Immobilized Antimicrobial Peptides. Anal. Chem. 2012, 84, 7359−7366. (22) Raigoza, A. F.; Webb, L. J. Molecularly Resolved Images of Peptide-Functionalized Gold Surfaces by Scanning Tunneling Microscopy. J. Am. Chem. Soc. 2012, 134, 19354−19357. (23) Shamsi, F.; Coster, H.; Jolliffe, K. A.; Chilcott, T. Characterization of the Substructure and Properties of Immobilized Peptides on Silicon Surface. Mater. Chem. Phys. 2011, 126, 955−961. (24) Shen, Y. R. The Principles of Nonlinear Optics; WileyInterscience: New York, 1984; pp 475−504. (25) Shen, Y. R. Surface Properties Probed by Second-Harmonic and Sum-Frequency Generation. Nature 1989, 337, 519−525. (26) Williams, C. T.; Beattie, D. A. Probing Buried Interfaces with Non-Linear Optical Spectroscopy. Surf. Sci. 2002, 500, 545−576. (27) Zhuang, X.; Miranda, P. B.; Kim, D.; Shen, Y. R. Mapping Molecular Orientation and Conformation at Interfaces by Surface Nonlinear Optics. Phys. Rev. B 1999, 59, 12632−12640. (28) Lambert, A. G.; Davies, P. B.; Neivandt, D. J. Implementing the Theory of Sum Frequency Generation Vibrational Spectroscopy: A Tutorial Review. Appl. Spectrosc. Rev. 2005, 40, 103−145. (29) Perry, A.; Neipert, C.; Space, B. Theoretical Modeling of Interface Specific Vibrational Spectroscopy: Methods and Applications to Aqueous Interfaces. Chem. Rev. 2006, 106, 1234−1258. (30) Leung, B. O.; Yang, Z.; Wu, S. S. H.; Chou, K. C. Role of Interfacial Water on Protein Adsorption at Cross-linked Polyethylene Oxide Interfaces. Langmuir 2012, 28, 5724−5728. (31) Chen, P.; Kung, K. Y.; Shen, Y. R.; Somorjai, G. A. Sum Frequency Generation Spectroscopic Study of CO/Ethylene Coadsorption on the Pt(111) Surface and CO Poisoning of Catalytic Ethylene Hydrogenation. Surf. Sci. 2001, 494, 289−297. (32) Tong, Y.; Tyrode, E.; Osawa, M.; Yoshida, N.; Watanabe, T.; Nakajima, A.; Ye, S. Preferential Adsorption of Amino-terminated Silane in a Binary Mixed Self-assembled Monolayer. Langmuir 2011, 27, 5420−5426. (33) Ye, H. K.; Gu, Z. Y.; Gracias, D. H. Kinetics of Ultraviolet and Plasma Surface Modification of Poly(dimethylsiloxane) Probed by Sum Frequency Vibrational Spectroscopy. Langmuir 2006, 22, 1863− 1868. (34) Kim, J.; Cremer, P. S.; IR-Visible, S. F. G. Investigations of Interfacial Water Structure upon Polyelectrolyte Adsorption at the Solid/Liquid Interface. J. Am. Chem. Soc. 2000, 122, 12371−12372. (35) Bordenyuk, A. N.; Jayathilake, H.; Benderskii, A. V. Coherent Vibrational Quantum Beats as a Probe of Langmuir-Blodgett Monolayers. J. Phys. Chem. B 2005, 109, 15941−15949. (36) Baldelli, S. Surface Structure at the Ionic Liquid-electrified Metal Interface. Acc. Chem. Res. 2008, 41, 421−431. (37) Davis, A. P.; Ma, G.; Allen, H. C. Surface Vibrational Sum Frequency and Raman Studies of PAMAM G0, G1 and Acylated PAMAM G0 Dendrimers. Anal. Chim. Acta 2003, 496, 117−131. (38) Voges, A. B.; Al-Abadleh, H. A.; Musorrariti, M. J.; Bertin, P. A.; Nguyen, S. T.; Geiger, F. M. Carboxylic Acid- and Ester-functionalized Siloxane Scaffolds on Glass Studied by Broadband Sum Frequency Generation. J. Phys. Chem. B 2005, 108, 18675−18682. (39) Can, S. Z.; Mago, D. D.; Walker, R. A. Structure and Organization of Hexadecanol Isomers Adsorbed to the Air/Water Interface. Langmuir 2006, 22, 8043−8049. (40) Liu, J.; Conboy, J. C. Direct Measurement of the Transbilayer Movement of Phospholipids by Sum-frequency Vibrational Spectroscopy. J. Am. Chem. Soc. 2004, 126, 8376−8377. 5679



Article

(58) Han, X.; Liu, Y.; Wu, F.; Jansensky, J.; Kim, T.; Wang, Z.; Brooks, C. L., III; Wu, J.; Xi, C.; Mello, C. M.; et al. Different Interfacial Behaviors of Peptides chemically Immobilized on Surfaces with Different Linker Lengths and via Different Termini. J. Phys. Chem. B 2014, 118, 2904−2912. (59) Norberg, J.; Nilsson, L. Advances in Biomolecular Simulations: Methodology and Recent Applications. Q. Rev. Biophys. 2003, 36, 257−306. (60) Friedel, M.; Baumketner, A.; Shea, J. E. Effects of Surface Tethering on Protein Folding Mechanisms. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 8396−8401. (61) Feng, J.; Wong, K. Y.; Lynch, G. C.; Gao, X. L.; Pettitt, B. M. Peptide Conformations for a Microarray Surface-Tethered Epitope of the Tumor Suppressor p53. J. Phys. Chem. B 2007, 111, 13797−13806. (62) Feng, J.; Wong, K. Y.; Lynch, G. C.; Gao, X.; Pettitt, B. M. Salt Effects on Surface-Tethered Peptides in Solution. J. Phys. Chem. B 2009, 113, 9472−9478. (63) So, C. R.; Kulp, J. L., III; Oren, E. E.; Zareie, H.; Tamerler, C.; Evans, J. S. Molecular Recognition and Supramolecular Self-Assembly of a Genetically Engineered Gold Binding Peptide on Au{111}. ACS Nano 2009, 3, 1525−1531. (64) Soliman, W.; Bhattacharjee, S.; Kaur, K. Adsorption of an Antimicrobial Peptide on Self-Assembled Monolayers by Molecular Dynamics Simulation. J. Phys. Chem. B 2010, 114, 11292−11302. (65) Verde, A. V.; Acres, J. M.; Maranas, J. K. Investigating the Specificity of Peptide Adsorption on Gold Using Molecular Dynamics Simulations. Biomacromolecules 2009, 10, 2118−2128. (66) Wang, Q.; Zhao, C.; Zhao, J.; Wang, J.; Yang, J. C.; Yu, X.; Zheng, J. Comparative Molecular Dynamics Study of Aβ Adsorption on the Self-Assembled Monolayers. Langmuir 2010, 26, 3308−3316. (67) Wang, Q.; Zhao, J.; Yu, X.; Zhao, C.; Li, L.; Zheng, J.; Alzheimer, A. β1−42 Monomer Adsorbed on the Self-Assembled Monolayers. Langmuir 2010, 26, 12722−12732. (68) Zheng, J.; Li, L.; Tsao, H. K.; Sheng, Y. J.; Chen, S.; Jiang, S. Strong Repulsive Forces between Protein and Oligo (Ethylene Glycol) Self-Assembled Monolayers: A Molecular Simulation Study. Biophys. J. 2005, 89, 158−166. (69) Freddolino, P. L.; Harrison, C. B.; Liu, Y.; Schulten, K. Challenges in Protein-folding Simulations. Nat. Phys. 2010, 6, 751− 758. (70) Brooks, B. R.; Bruccoleri, R. E.; Olafson, B. D.; States, D. J.; Swaminathan, S.; Karplus, M. CHARMM: A Program for Macromolecular Energy, Minimization, and Dynamics Calculations. J. Comput. Chem. 1983, 4, 187−217. (71) MacKerell, A. D., Jr.; Brooks, B.; Brooks, C. L., III; Nilsson, L.; Roux, B.; Won, Y.; Karplus, M. In CHARMM: The Energy Function and Its Parameterization with an Overview of the Program; Schleyer, P. V. R., Allinger, N. L., Clark, T., Gasteiger, J., Kollman, P. A., Schaefer, H. F., III, Schreiner, P. R., Eds.; The Encyclopedia of Computational Chemistry 1; John Wiley & Sons: Chichester, U.K., 1998; pp 271− 277. (72) Brooks, B. R.; Brooks, C. L., III; Mackerell, A. D., Jr.; Nilsson, L.; Petrella, R. J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; et al. CHARMM: The Biomolecular Simulation Program. J. Comput. Chem. 2009, 30, 1545−1614. (73) Kojio, K.; Ge, S. R.; Takahara, A.; Kajiyama, T. Molecular Aggregation State of n-Octadecyltrichlorosilane Monolayer Prepared at an Air/Water Interface. Langmuir 1998, 14, 971−974. (74) Maboudian, R. Surface Processes in MEMS Technology. Surf. Sci. Rep. 1998, 30, 207−269. (75) Mazyar, O. A.; Jennings, G. K.; Kane, J.; McCabe, C. Frictional Dynamics of Alkylsilane Monolayers on SiO2: Effect of 1-n-Butyl-3methylimidazolium Nitrate as a Lubricant. Langmuir 2009, 25, 5103− 5110. (76) Bereźniak, T.; Jäschke, A.; Smith, J. C.; Imhof, P. Stereoselection in the Diels−Alderase Ribozyme: A Molecular Dynamics Study. J. Comput. Chem. 2012, 33, 1603−1614. (77) MacKerell, A. D., Jr.; Feig, M.; Brooks, C. L., III Extending the Treatment of Backbone Energetics in Protein Force Fields:

Limitations of Gas-Phase Quantum Mechanics in Reproducing Protein Conformational Distributions in Molecular Dynamics Simulations. J. Comput. Chem. 2004, 25, 1400−1415. (78) MacKerell, A. D., Jr.; Bashford, D.; Bellott, M.; Dunbrack, R. L., Jr.; Evanseck, J. D.; Field, M. J.; Fischer, S.; Gao, J.; Guo, H.; Ha, S.; et al. All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins. J. Phys. Chem. B 1998, 102, 3586−3616. (79) Lopes, P. E. M.; Murashov, V.; Tazi, M.; Demchuk, E.; MacKerell, A. D., Jr. Development of an Empirical Force Field for Silica. Application to the Quartz−Water Interface. J. Phys. Chem. B 2006, 110, 2782−2792. (80) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys. 1983, 79, 926−935. (81) Phillips, J. C.; Braun, R.; Wang, W.; Gumbart, J.; Tajkhorshid, E.; Villa, E.; Chipot, C.; Skeel, R. D.; Kale, L.; Schulten, K. Scalable Molecular Dynamics with NAMD. J. Comput. Chem. 2005, 26, 1781− 1802. (82) Allen, M. P.; Tildesley, D. J. Computer Simulation of Liquids; Oxford University Press: New York, 1990; pp 24−27. (83) Andersen, H. C. Rattle: A “Velocity” Version of the Shake Algorithm for Molecular Dynamics Calculations. J. Comput. Phys. 1983, 52, 24−34. (84) Swope, W. C.; Andersen, H. C.; Berens, P. H.; Wilson, K. R. A Computer Simulation Method for the Calculation of Equilibrium Constants for the Formation of Physical Clusters of Molecules: Applications to Small Water Clusters. J. Chem. Phys. 1982, 76, 637− 649. (85) Im, W.; Lee, J.; Kim, T.; Rui, H. Novel Free Energy Calculations to Explore Mechanisms and Energetics of Membrane Protein Structure and Function. J. Comput. Chem. 2009, 30, 1622−1633. (86) Lee, J.; Im, W. Restraint Potential and Free Energy Decomposition Formalism for Helical Tilting. Chem. Phys. Lett. 2007, 441, 132−135. (87) Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual Molecular Dynamics. J. Mol. Graphics 1996, 14, 33−38.

5680


and N-Terminus Cysteine Modified Cecropin P1 Chemically

Recommend Documents