Complex Formation during SID and Its Effect on Proton Mobility

Letter pubs.acs.org/JPCL

Complex Formation during SID and Its Effect on Proton Mobility Waleed Ijaz,‡ Zackary Gregg,‡ and George L. Barnes* Department of Chemistry and Biochemistry, Siena College, Loudonville, New York 12211, United States ABSTRACT: Surface-induced dissociation (SID) of protonated peptides is a vibrant, active field of study. Significant focus has been placed on understanding the mechanism of dissociation, with most approaches using equilibrium thermodynamic arguments. Here, we explore the dynamics of SID using atomistic simulations. We find that it is common for complexes of peptide fragments to form following dissociation. An important consequence of complexation is that excess protons are not isolated following initial fragmentation and can participate in subsequent chemical reactions. Our work reveals an alternate mechanism for proton mobility that, to our knowledge, has not been previously observed in simulations.

SECTION: Kinetics and Dynamics

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he collision between protonated peptides and organic selfassembled monolayers (SAMs) is a widely studied field.1−7 Several processes can take place during and after the collision, one of which is surface-induced dissociation (SID).2−4,7 SID takes place because of the translational to vibrational energy transfer that is possible during the collision event. SID is an extremely useful analytic technique because it provides a “fingerprint” of the ion’s structure. The empirical mobile proton model, initially developed by Wysocki and co-workers, gives a qualitative description of experimentally observed peptide fragments.8,9 For a recent perspective on this model, see ref 10. The mobile proton model is based on a gradual heating of the peptide due to energy transfer. As the peptide is heated, the excess proton can hop to thermodynamically less stable sites that weaken specific backbone bonds and allow for fragmentation. This description of SID is appealing, insightful, and allows for predictions based on chemical intuition. Theoretical studies have been performed that outline peptide fragmentation pathways based on the idea of mobile protons,11,12 but the dynamics of the system reveals an unexpected and interesting alternative mechanism for proton motion. In this work, we report results from simulations of hyperthermal collisions between a protonated octaglycine (gly8H+) and a fluorinated octanethiol organic self-assembled monolayer (FSAM) surface, which is depicted in Figure 1. FSAM surfaces are “stiff” and transfer a large portion of translational energy to the internal degrees of freedom, hence making fragmentation more likely. We focused on gaining an atomistic view of SID within this system and discovered that complexation between the initial fragmentation products can play an important role in subsequent chemical reactions, including secondary fragmentation. In short, if a complex forms following fragmentation, the excess proton is not isolated and can contribute to additional chemical processes. We begin our discussion of the results with the fragmentation fractions (see Figure 2) obtained from our simulations. We find © 2013 American Chemical Society

Figure 1. A cartoon representation of the FSAM. The color scheme for this and all other figures is as follows: carbon, black; nitrogen, dark blue; oxygen, red; fluorine, light blue; sulfur, light green; gold, yellow; and hydrogen, white. Image created using VMD.13

Figure 2. Fraction of trajectories that fragment within the 16 ps simulation time frame as a function of collision energy. The fraction increases dramatically with increasing energy before leveling off. Comparison to experiment shows that additional fragmentation will take place outside of our simulation window, and it is possible that other important product pathways may occur on longer time scales.

that for 30 eV collisions, only 16% of trajectories fragmented within the time frame of the simulations. Comparing this to the Received: September 27, 2013 Accepted: November 5, 2013 Published: November 5, 2013 3935

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experimental results of Laskin and Futrell4 is revealing. Their work shows that for a FSAM surface, all trajectories fragment experimentally at collision energies slightly larger than 40 eV. Our fragmentation fractions have a strong time dependence, and we are certainly missing fragmentation events that occur later in time. This strongly suggests that significant dynamical processes could take place outside of our simulation time frame. To facilitate our discussion of fragmentation, we make use of mass spectrometry nomenclature14 for some ions and a slightly modified version to describe bond cleavage sites. The most common fragment formed is the (NH2CH2)+ ion, which occurs with a probability of 0.199 at 30 eV and 0.570 at 110 eV. Experimentally, such an increase is an indication that complex formation may be taking place.15 This ion can be formed directly as the a1 ion or through a multistep process. A significant portion of the trajectories that produce (NH2CH2)+ simultaneously form the CO molecule, which corresponds to an (A−X) + (B−Y) type of fragmentation. The identity of this primary fragment is consistent with both previous simulations and the mobile proton model. A striking result of these simulations is that the peptide fragments do not necessarily move apart quickly following fragmentation. Some fragments, such as CO, move apart quickly and never complex with any other fragments. Other fragments, such as (NH2CH2)+, frequently form complexes with other fragments, as illustrated in Figure 3. Complexes that

(NH2CH2)+ ion is 0.83 at 30 eV and 0.55 at 110 eV. It is striking that these complexes are relatively long-lived and stable. We note that the work of Hase and co-workers on gly8-H+ colliding with a diamond surface also found that (NH2CH2)+ was the most common ion produced.20 They also observed several complicated rearrangement products, and although their simulation time frame was significantly shorter, it is possible that similar complexation dynamics were important in that system. Two limiting types of complexes are observed in the simulations, hydrogen bonding and proton-transfer complexes. A general theme for both is that the smaller peptide fragment is solvated by the larger fragment. The small fragment is quite mobile and moves from hydrogen-bonding site (or transfer site) to hydrogen-bonding site; this constitutes a new mechanism for proton transfer within the system. The proton itself does not need to move from site to site, breaking and forming covalent bonds as it progresses, but rather, the fragment can move directly from solvation site to solvation site. A future study will examine the transition states involved in this process. Complexation allows for a new mechanism of proton mobility within the molecule and can play an important role in additional peptide fragmentation events. In a recent work of Wysocki and co-workers,19 a new mechanism involving ion− molecule complexes was also proposed. It is quite striking and timely to see such similar mechanisms found in both simulations and experiment. This is illustrated vividly by a 50 eV trajectory (see Figure 4). The initial fragmentation event occurs at 5.3 ps, producing (NH2CH2)+ and CO, meaning that the fragmentation proceeded through an (A−X) + (B−Y) pathway. The CO molecule quickly drifts away, while the a1 ion complexes with the resulting gly7 fragment. At 10.7 ps, the complex is still present, and a proton transfers from the a1 ion to the larger fragment, resulting in gly7-H+ and NHCH2, which drift apart. Gly7-H+ itself fragments 3.5 ps later, which produces another (NH2CH2)+ and CO molecule as well as gly6. Once again, a small ion was created that could complex with the larger fragment. This process could continue for multiple iterations and have a dramatic effect on the final ions observed experimentally. These observations are consistent with the results from Paizs’s Pathways in Competition model.11 Although this example shows fragmentation starting from the N terminus moving toward the C terminus, it is possible for the proton to transfer to multiple sites within the larger fragment. The traditional view of proton mobility and fragment proton mobility can also work in concert. For example, a 50 eV trajectory depicted in Figure 5 shows the initial formation of the (NH2CH2)+ along with COH-gly7 at 5.6 ps. At 8.5 ps, a proton transfers from the a1 ion to the larger fragment to form NHCH2 and HCO-gly7-H+. By this time, another proton has transferred further down the peptide backbone. A combination of traditional proton motion within the peptide backbone and the introduction of another proton made possible due to complexation allows for the eventually (at 10.7 ps) secondary fragmentation that results in (HCONHCH2CONHCH2)+ and COH-gly5. These two fragments stay close together for the remainder of the trajectory, and it is possible that additional reactions would have occurred later in time. This work provides an atomistic view of a new mechanism for proton mobility within peptide fragments that complements the existing mobile proton model. It is interesting to note that the initial fragmentation usually results from a short distance

Figure 3. A snapshot from a 30 eV trajectory that illustrates complex formation during SID. The smaller a1 ion is solvated by the larger gly7 peptide fragment. The a1 ion is able to move from site to site along the peptide fragment backbone, which has far-reaching consequences for proton mobility.

involve the (NH2CH2)+ ion have an average lifetime of 5.7 ps at a collision energy of 30 eV and 4.3 ps at 110 eV. These averages clearly show that the complexes exist for a significant amount of time, which is consistent with the experimental results of Morton,16,17 Paizs,18 and Wysocki.19 However, the fragmentation lifetimes themselves can also be misleading. The time at which fragmentation occurs varies dramatically depending on intramolecular proton motion as well as intramolecular vibrational energy relaxation. In addition, secondary chemical reactions or recombination of fragments can take place, both of which could happen rapidly or gradually. To ameliorate these effects, we examine the average based on the length of time that the fragments could have been complexed. For example, if the peptide dissociation occurs at 12 ps and the fragments complex with a lifetime of 3 ps (out of the 4 ps remaining in the simulation), the complex has a lifetime fraction of 0.75. The average lifetime fraction for complexes involving the 3936

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Figure 5. Snapshots of a 50 eV trajectory that illustrates traditional proton mobility and fragment proton mobility working in concert to produce large fragmentation products. The first frame shows the (NH2CH2)+ ion in a proton-transfer complex with the peptide. When that proton eventually transfers, it along with other backbone proton motion allows for a secondary fragmentation event. The two resulting fragments are both sizable and stay close together for the remainder of the simulation.

Figure 4. Snapshots of a 50 eV trajectory that illustrates a secondary reaction made possible due to complex formation. The initial fragmentation occurs at 5.34 ps through an (A−X) + (B−Y) mechanism, producing CO and the a1 ion. The a1 ion forms a long-lived complex, as shown in the first frame (Time = 9.14 ps). Between the first and second frames, the excess proton transfers to the larger fragment from the a1 ion, allowing NHCH2 to dissociate (Time = 10.74 ps). The proton transfers to the new terminal nitrogen, and several picoseconds later, a secondary fragmentation event occurs, as shown in the last frame. This fragmentation also follows the (A−X) + (B−Y) mechanism, but on the shorter gly7-H+ peptide produced by the initial fragmentation and subsequent proton transfer.

surface. Initial conditions for the peptide are sampled from a 300 K Maxwell−Boltzmann distribution for both vibrational and rotational motion.29−31 The peptide is placed 30 Å from the surface and given a collision energy from 30 to 110 eV with a normal incidence angle. The surface is also prepared with an initial 300 K vibrational distribution using a molecular dynamics velocity rescaling scheme. For each collision energy, 500 trajectories were calculated. Each simulation was propagated using a sixth-order symplectic integration scheme32 with a step size of 1 fs for a total simulation time of 16 ps with an output recorded every 50 fs. Any trajectories that did not conserve energy to within 1% of the collision energy were recalculated with a 0.5 fs time step. The surface construction, initial conditions, and simulations themselves were performed using VENUS33,34 coupled to MOPAC5.016 nm.35 Custom analysis code was developed to closely examine the dynamics related to postcollision SID of the peptide. Our first step was to obtain the bond order matrix (BOM) for each step of the trajectory. For a static equilibrium case, the BOM would be sufficient to determine which atoms are connected. However, during our simulations, the peptide exists far from equilibrium, and hence, we developed a set of criteria in addition to bond order (BO) to track the chemical changes that take place during the trajectory. It should be noted that changing this criteria would change our results slightly. For this reason, we choose stringent definitions that might report a fragmentation time that is larger than other definitions.

proton migration. Fragment proton mobility may be an important mechanism for products that require long-range proton motion. A future study will examine the correlation and time lag between proton transfer and peptide fragmentation as well as the common proton motion pathways during SID events.

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COMPUTATIONAL METHOD Our computational approach for simulating the collision between gly8-H+ and the FSAM surface follows closely that of Yang et al.21 and Barnes and co-workers.22 Hence, we will only briefly describe the simulation, and focus our narrative on the analysis technique. We perform direct dynamics simulations23−25 of the gly8-H+ + FSAM collision system. The intramolecular potential energy of the peptide is represented with the semiempirical RM1 method,26 which has been successfully used in several previous peptide + surface simulations that examine both reactivity and energy transfer.22,27,28 The geometry of gly8-H+ is taken from a previous study.22 Although the system is a singlet, we use an unrestricted wave function for its added flexibility and more realistic treatment of this high-energy collision system. The remainder of the potential energy terms are treated at the molecular mechanical level using the parameters laid out by Yang et al.21 The surface itself is a 9 × 9 octanethiol FSAM 3937

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We begin our criteria by considering two atoms bound if the BO between them is above 0.7. In order to capture relevant chemistry without overly focusing on momentary stretches, the matrix was averaged over five simulation steps. With this initial connectivity on hand, one or more fragments within the system can be defined. Our second criterion was that all free protons (or hydrogen atoms) were included in the fragment containing the heavy atom to which they were last bound. This was adopted because visual inspection of multiple trajectories showed that protons (or hydrogen atoms) were never “free”, but rather were always associated with heavy atoms. Protons were, however, transferred from one heavy atom to another, and at times, BO alone would suggest that they were free. Our third criterion is based on fragment charge. All fragments with nonunit charge (i.e., not 0 or +1) were identified, and appropriate pairs or triplets of fragments were combined. Fragments were only combined if the closest heavy atom distance between them was within 2.2 Å. In this step, we defined both “loose” and “strict” conditions, which refer to the magnitude away from nonunit charge. All trajectories were initially analyzed with strict conditions (more than 0.05 away from unit charge). If no fragmentation event was found, then the loose condition of 0.1 away from unit charge was considered in order to avoid missing fragmentation events that might involve complexes. Once again, we emphasize that any definition based on cutoff values is arbitrary, and hence, we have chosen relatively strict requirements for even our loose criteria. This ensures that the bond cleavages that we identify are real rather than being simple stretches. A side effect of this choice is that fragmentation times should be considered upper bounds rather than absolute numbers. This set of criteria allows for precise tracking of chemical change within the system and has been painstakingly checked through visual inspection. These inspections also revealed that several trajectories showed evidence of complexation between peptide fragments. In order to quantify this observation, the complexation lifetime was accumulated during the trajectory. Two fragments were considered to be in a complex if the two closest heavy atoms were within 4 Å of each other. The average lifetimes reported below do not include any “complexes” that existed for less than 0.8 ps under the assumption that they were never complexed, and the fragments simply took that long to dissociate from each other.

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REFERENCES

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Author Contributions ‡

W.I. and Z.G. contributed equally.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS G.L.B. gratefully acknowledges support from the Siena College New Faculty Start-up Fund and the Siena Summer Scholars program. Siena College student Stephen Jannetti is gratefully acknowledged for initial work on a related project. Computer resources were also provided in part from the National Science Foundation through XSEDE resources Grant No. TGCHE120104. 3938

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(22) Barnes, G. L.; Hase, W. L. Energy Transfer, Unfolding, and Fragmentation Dynamics in Collisions of N-Protonated Octaglycine with an H-SAM Surface. J. Am. Chem. Soc. 2009, 131, 17185−17193. (23) Bolton, K.; Hase, W. L.; Peslherbe, G. H. In Modern Methods for Multidimensional Dynamics Computations in Chemistry; Thompson, D. L., Ed.; World Scientific: Singapore, 1998; pp 143−189. (24) Sun, L.; Hase, W. L. Born−Oppenheimer Direct Dynamics Classical Trajectory Simulations. Rev. Comput. Chem. 2003, 19, 79− 146. (25) Warshel, A.; Levitt, M. Theoretical Studies of Enzymic Reactions: Dielectric, Electrostatic and Steric Stabilization of the Carbonium Ion in the Reaction of Lysozyme. J. Mol. Biol. 1976, 103, 227−249. (26) Rocha, G. B.; Freire, R. O.; Simas, A. M.; Stewart, J. J. P. RM1: A Reparameterization of AM1 for H, C, N, O, P, S, F, Cl, Br, and I. J. Comput. Chem. 2006, 27, 1101−1111. (27) Barnes, G. L.; Young, K.; Yang, L.; Hase, W. L. Fragmentation and Reactivity in Collisions of Protonated Diglycine with Chemically Modified Perfluorinated Alkylthiolate-Self-Assembled Monolayer Surfaces. J. Chem. Phys. 2011, 134, 094106. (28) Geragotelis, A.; Barnes, G. L. Surface Deposition Resulting from Collisions Between Diglycine and Chemically Modified Alkylthiolate Self-Assembled Monolayer Surfaces. J. Phys. Chem. C 2013, 117, 13087−13093. (29) Schultz, D. G.; Wainhaus, S. B.; Hanley, L.; de Sainte Claire, P.; Hase, W. L. Classical Dynamics Simulations of SiMe+3 Ion-Surface Scattering. J. Chem. Phys. 1997, 106, 10337−10348. (30) Song, K.; de Sainte Claire, P.; Hase, W. L.; Hass, K. C. Comparison of Molecular Dynamics and Variational Transition-StateTheory Calculations of the Rate Constant for H-Atom Association with the Diamond {111} Surface. Phys. Rev. B 1995, 52, 2949−2958. (31) Accary, C.; Barbarat, P.; Hase, W. L.; Hass, K. C. Importance of Energy Transfer and Lattice Properties in Hydrogen-Atom Association with the (111) Surface of Diamond. J. Phys. Chem. 1993, 97, 9934− 9941. (32) Schlier, C.; Seiter, A. High-Order Symplectic Integration: An Assessment. Comput. Phys. Commun. 2000, 130, 176−189. (33) Hu, X.; Hase, W. L.; Pirraglia, T. Vectorization of the General Monte Carlo Classical Trajectory Program VENUS. J. Comput. Chem. 1991, 12, 1014−1024. (34) Hase, W. L.; Duchovic, R. J.; Hu, X.; Komornicki, A.; Lim, K. F.; Lu, D. H.; Peslherbe, G. H.; Swamy, K. N.; Vande Linde, S. R.; Varandas, A.; et al. VENUS96: A General Chemical Dynamics Computer Program. Quant. Chem. Prog. Exch. Bull. 1996, 16, 671. (35) Stewart, J. J. P.; Fiedler, L.; Zhang, P.; Zheng, J.; Rossi, I.; Hu, W.-P.; Lynch, G. C.; Liu, Y.-P.; Chuang, Y.-Y.; Pu, J.; et al. MOPACVersion 5.016mn; University of Minnesota: Minneapolis, MN, 2010.

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