Unimolecular Fragmentation of Deprotonated Diproline [Pro2-H

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Unimolecular Fragmentation of Deprotonated Diproline [Pro-H] Studied by Chemical Dynamics Simulations and IRMPD Spectroscopy Ana Martin-Somer, Jonathan Martens, Josipa Grzetic, William Louis Hase, Jos Oomens, and Riccardo Spezia J. Phys. Chem. A, Just Accepted Manuscript • DOI: 10.1021/acs.jpca.7b11873 • Publication Date (Web): 16 Feb 2018 Downloaded from http://pubs.acs.org on February 24, 2018

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The Journal of Physical Chemistry

Unimolecular Fragmentation of Deprotonated Diproline [Pro2-H]- Studied by Chemical Dynamics Simulations and IRMPD Spectroscopy Ana Martin-Somer,1,2,* Jonathan Martens,3 Josipa Grzetic3, William L. Hase,4 Jos Oomens3,5 and Riccardo Spezia1,6* 1

Laboratoire Analyse et Modélisation pour la Biologie et l’Environnement, CEA-CNRS, Université

Paris Saclay, Evry, France 2

Departamento de Química, Facultad de Ciencias, Módulo 13, Universidad Autónoma de Madrid,

Campus de Excelencia UAM-CSIC, Cantoblanco, 28049 Madrid, Spain. 3

Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7c,

6525ED Nijmegen, The Netherlands 4

Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas (USA)

5

van’t Hoff Institute for Molecular Sciences, University of Amsterdam, 1098XH Amsterdam, Science

Park 908, The Netherlands 6

Sorbonne Université, CNRS, Laboratoire de Chimie Théorique, LCT, F. 75005 Paris, France

correspondence to: [email protected] ; [email protected]

Abstract Dissociation chemistry of the diproline anion [Pro2-H]- is studied using chemical dynamics simulations coupled with quantum-chemical calculations and RRKM analysis. Pro2- is chosen due to its reduced size and the small number of sites where deprotonation can take place. The mechanisms leading to the two dominant collision-induced dissociation (CID) product ions are elucidated. Trajectories from a variety of isomers of [Pro2-H]- were followed in order to sample a larger range of possible reactivity. While different mechanisms yielding y1- product ions are proposed, there is only one mechanism yielding the b2- ion. This mechanism leads to formation of a b2- fragment with a diketopiperazine structure. The sole formation of a diketopiperazine b2 sequence ion is experimentally confirmed by infrared ion spectroscopy of the fragment anion. Furthermore, collisional and internal energy activation simulations are used in parallel to identify the different dynamical aspects of the observed reactivity.

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1. Introduction Mass spectrometry (MS) and tandem mass spectrometry (MS/MS or MSn) have become leading tools in the so-called OMICS-sciences (proteomics, genomics, metabolomics, lipidomics, foodomics, etc.).1-10 The reason of this success lies in the versatility of MS for the identification and quantification of a wide variety of molecular species, together with the possibility of complementing MS with other technologies such as chromatography and spectroscopy. MSn provides structural (sequence) information about biomacromolecules under study and has the advantage of softly introducing intact biomolecular ions (positively or negatively charged) into the gas phase, i.e., without previous modifications. Beyond the highthroughput proteomics studies for which tandem mass spectrometry is routinely used, it has also been applied for characterization of structures and conformations of individual peptides or proteins as well as their fragmentation products resulting from tandem MS. The vast majority of mass spectrometric studies are carried out in positive mode1-10 which can lead to an incomplete description of acidic portions of proteomes.11 Many naturally occurring peptides are acidic (~50%)12 and therefore favour deprotonation. This makes positive electrospray techniques less well-suited for their characterization.13-15 It has also been shown that even highly basic peptides can easily form singly deprotonated ions with sufficient intensities for fragmentation experiments16 Moreover, post-translational modifications such as phosphorylation, sulfation, and glycosylation can impart acidic properties to the peptide/protein they modify.11,13,17-21 The relatively few negative ion mode studies performed to date14,22-25 have shown that negative ion collision induced dissociation (CID) spectra are often as informative as their positive mode analogs in terms of sequence information. Furthermore, negative-ion fragmentation is often found to exhibit c- and z-type ions providing complementary structural information to positive ion fragmentation (mainly yielding a-, band y-type backbone fragments). Moreover, CID mass spectra of negative ions can allow identification of amino acid residues by characteristic fragmentation of their side chains that is not available from positive ion spectra.22 In addition to fundamental interest, understanding peptide fragmentation patterns improves the ability to interpret spectra, develop mechanistic insight, and allows the design of better and more refined algorithms to identify peptides and proteins.26,27 A number of questions can be put forward regarding the dissociation chemistry involved in negative mode mass spectrometry of peptides and proteins. Where does the peptide deprotonate in absence of acidic residues?28 After activation of peptide anions, are protons


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mobile in a fashion similar to that in their protonated analogues? Is there also a competition between oxazolone and diketopiperazine structures for the b2-type fragment?25,29-31 Deprotonated diproline ([Pro2-H]-) is a good model to address these questions, since there are a relatively small number of sites where deprotonation can take place; i.e., it does not have amide protons or any side chain sites that can accept/donate a proton. Furthermore, polyprolines in general exhibit rather unusual fragmentation patterns. Pro2- serves also as a starting point in the elucidation of this unusual chemistry using computational chemistry. Among the many available activation methods, CID32 remains the one most widely used and available.33 Hence, we have employed different theoretical methods to model the CID process and compare these results with CID experiments. In particular, we employed direct chemical dynamics simulations in which the potential energy surface (PES) is computed on-the-fly using a semi-empirical Hamiltonian. In order to assess different factors that may influence ion fragmentation upon energization, in the present work we considered two types of activation in the simulations: (i) by an explicit collision between [Pro2-H]- and an Ar atom; (ii) by an increase in the internal energy, uniformly distributed over all internal modes of the molecule. When using trajectories to understand CID experiments, one needs to consider an ensemble of trajectories for reasons of statistical sampling, so that high level theoretical methods cannot be employed due to the excessive computational cost that would be required. Nevertheless, it has been shown that semi-empirical Hamiltonians offer a valuable tool to understand the fragmentation of amino acids and peptides,34-38 sugars39,40 and other relatively large organic molecules (e.g. uracil41,42 and testosterone43). These types of simulations have also been used to understand isomerization and fragmentation mechanisms. For specific cases, these results were further elaborated upon by calculating transition states (TS), intrinsic reaction coordinates (IRC), and rate constants using the Rice-Ramsperger-Kassel-Marcus44-46 (RRKM) theory. To the best of our knowledge this is the first time that chemical dynamics simulations have been extensively used to understand CID induced dissociation processes of negatively charged peptides.

2. Experimental and computational methods. 2.1 Experiments IR ion spectroscopy measurements were performed using a modified quadrupole ion trap mass spectrometer (Bruker, AmaZon Speed ETD) interfaced with the FELIX IR beamline.47 Details of the modifications and of standard operating protocols have been reported elsewhere.48 Pro2 was electrosprayed (-ESI) using solutions of 10-7 M in 50:50 MeOH:H2O.


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CID was performed after mass isolation of the deprotonated peptide precursor ion with activation for 40 ms using an amplitude parameter of ~0.3-0.4. The FELIX free electron laser generates infrared radiation as ~5 μs macropulses at a 10 Hz repetition rate with ~40 mJ pulse energy and a bandwidth of ~0.4% of the center frequency. We monitor the precursor and IR-photodissociation product ion intensities (IR yield= Σ I(fragment ions)/ΣI(parent + fragment ions)) as the IR laser wavelength is tuned in order to generate an infrared spectrum. The yield at each IR wavelength was obtained from averaged mass spectra and has been linearly corrected for laser power; the frequency was calibrated throughout the measurements using a grating spectrometer.

2.2 Quantum chemistry calculations and RRKM rate constants Geometry optimizations of minima and TS structures of [Pro2-H]- were obtained at the PM349 and DFT levels of theory. We used the B3LYP50,51 functional together with the 6-31++G(d,p) basis set. Diffuse functions are added to all atoms in order to ensure an adequate description of regions of space significantly apart from the nuclei which are important when dealing with negative ions. The same level of theory was used to calculate energies and harmonic vibrational frequencies, allowing the classification of stationary points found on the PES as minima or TSs.

Harmonic frequencies were also employed to estimate the zero point

vibrational energy (ZPVE) as well as for the RRKM calculations (see below). To verify the connectivity between a TS and its adjacent minima we ran intrinsic reaction coordinate (IRC) calculations at the PM3 level. All calculations were performed using the Gaussian0952 suite of programs. RRKM theory was employed to obtain unimolecular dissociation rate constants in the statistical limit. Using geometries, energies and (harmonic) vibrational frequencies of reactants and transition states, harmonic microcanonical RRKM rate constants are computed as a function of the internal energy of the molecule:53

(1) where σ is the reaction degeneracy, h is Plank’s constant, E0 is the activation energy, N‡(E – E0) is the TS sum of states, and ρ(E) is the reactant density of states (the latter two quantities are only for active degrees of freedom). The Zhu and Hase code54 was used to compute k(E). In order to better compare the results from RRKM calculations with reaction times obtained


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from dynamics calculations (which employ classical equations of motion on the PES calculated on-the-fly as described below), we computed classical rate constants, i.e., barrier heights correspond to classical barriers: ZPVE of reactants or TSs are not included. We recall that one of the main assumptions of RRKM theory is that the molecule’s phase space is uniformly sampled prior to the fragmentation reaction, so that rate constants obtained are in the statistical limit.

2.3 Chemical dynamics simulations Our aim is to identify reaction mechanisms observed in CID experiments by means of chemical dynamics simulations. Collisional activation of ions in tandem mass spectrometry is accomplished through collisions with background inert gas molecules. During the collision, the relative kinetic energy is partially transferred to the internal vibrational and rotational degrees of freedom of the ion (collisional energies are too low for electronic activation) eventually leading to dissociation. Two limiting cases of the collisional regime are conceivable: i) a single collision transfers enough energy to the molecule to induce fragmentation or ii) the ion experiences a number of low energy collisions that slowly and uniformly activate it prior to fragmentation. A schematic picture is shown in Figure 1. In the first case the energy is deposited locally to the region of the molecule where the collision occurs triggering fragmentation of this part of the molecule (direct fragmentation mechanism, non-statistical). Alternatively, energy is redistributed over all internal modes of the molecule (internal vibrational energy redistribution, IVR) and statistically leads to fragmentation (statistical mechanism). In the second regime, the molecule is slowly and uniformly heated and fragmentation proceeds along the lowest energy pathway.


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Figure 1: Schematic picture of the two limiting cases for ion activation by collisions: i) one single collision transfers enough energy to trigger fragmentation, ii) the molecule undergoes multiple collisions that slowly and uniformly heat the ion.

In order to model fragmentation in these limiting cases, two types of simulations were employed: i) single-collision activation that accounts for non-statistical fragmentation and ii) internal energy activation leading to statistical dissociation of the ion as a function of its internal energy. Comparison between the two allows us to assess the role of the activation process in the ensuing fragmentation dynamics. In both cases the VENUS55 code coupled with MOPAC56 was used to propagate the dynamics based on the PES computed on-the-fly at the PM3 level. Even if other semi-empirical Hamiltonian are available, PM3 was recently shown to be able to correctly reproduce CID of some peptides and negative ions.37-40 Since the aim of the present study is not a method comparison in reaction dynamics, here we report PM3-based results which are directly compared with experiments. Collisional activation simulations. In this single collision regime, the dynamics after the collision between an inert gas molecule (Ar) and the [Pro2-H]- ion is followed. The total potential energy for the system is composed of the ion internal energy, computed with the PM3 semi-empirical Hamiltonian, and the ion-Ar interaction, evaluated using

(2)

where i runs over all atoms and Ai, Bi, and Ci are positive coefficients yielding a purely repulsive potential. Attractive ion-Ar interactions are negligible at the collision energies used here. The form of the potential in Eq. 2 was optimized by Meroueh and Hase for polyglycine


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and polyalanine collisions with Ar57 and parameters developed in that work are used for all chemical moieties but the carboxylate one. The carboxylate – Ar parameters were obtained in previous work.58 All parameters used are reported in Table S1 in the Supporting Information. Note that to compute the ion internal energy we use a semi-empirical method since the use of DFT or ab initio electronic structure methods for the direct dynamics simulations is not computationally practical for the size of the system studied here. The following initial conditions were used. For the ions’ initial internal energy: (i) a quasiclassical 300 K Boltzmann distribution of vibrational energies was added about each potential energy minimum.59 A random phase was chosen for each normal mode, with the kinetic and potential energies accordingly partitioned; (ii) each principal ion rotation axis was given a 300 K rotational energy of RT/2;(iii) the collisional parameters were set up by randomly rotating the ion about its Euler angles to emulate random directions of Ar – ion collisions in experiments; (iv) afterwards, relative velocities are added to the Ar – [Pro2-H]- system according to the center-of-mass collision energy Ecoll and impact parameter b. The collision energy used for this set of simulations is 300 kcal/mol. The impact parameter was randomly sampled between 0 and bmax. For b = 5.0 Å energy transfer is less than 10% of the collision energy, therefore bmax was set to this value;58 and (v) the initial separation between Ar and the ion is set to 10 Å with respect of their center-of-mass to ensure that there is no interaction prior to the collision. Simulations were stopped when the distance exceeded 400 Å, which corresponds to simulation times in the 5 – 40 ps range. Newton’s equations of motion were integrated using the velocity Verlet algorithm60 with a time step of 0.1 fs, which provides good energy conservation. This set-up was used to run simulations starting from the six isomers: 1, I2, I3, I4, I5, and I6 (see Figure 3). For 1, I2, and I3 we ran enough trajectories to have about 1000 reactive trajectories, i.e., 11713, 1980 and 8000 respectively. For I4, I5, and I6 we ran about 4000 trajectories per isomer. Internal energy activation simulations. The other activation method used consists of giving a fixed amount of internal energy to the ion that is randomly distributed among its vibrational modes. For these trajectories the system is only composed of the ion itself, i.e., the collision is not modelled. Classical microcanonical normal mode sampling was used61 (ZPVE is not considered) to distribute the energy among the ion’s vibrational modes. Note that for collisional activation simulations the sampling is quasi-classical. The values sampled for the internal energy are 209, 250, 292, 334, 376, 417 459 and 501 kcal/mol. To compute energies and forces at each step of the trajectory we employed the PM349 Hamiltonian. Again, the Velocity Verlet60 algorithm was used to numerically solve Newton’s equations of motion with


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a time step of 0.2 fs, which ensured energy conservation for all internal energies considered. An ensemble of 200 trajectories was used for each internal energy and isomer. These trajectories were propagated up to 10 ps. Here we highlight differences concerning the total internal energy that the ion possesses during the simulations. For collisional activation simulations, the ion starts in all trajectories with an internal energy equal to its ZPVE + its 300 K thermal quantum harmonic vibrational energy. After the collision, a fraction of the collision energy is transferred to the ion (Etransf). Hence, the total energy available for dissociation is Eint = ZPVE + thermal vibrational + Etransf and therefore it will vary from one trajectory to another as a function of the energy transferred in the collision. On the other hand, for internal energy activation trajectories, a fixed amount of internal energy (Eint), that is constant for all trajectories, is given to the molecule. A schematic picture of both possibilities is shown in Figure 2.

Figure 2: Schematic picture of internal energy distribution for both kinds of dynamics simulations. For collisional activation simulations Eint = ZPVE + thermal vibrational energy + Etransf, being Etransf a variable value for each trajectory. Since the thermal vibrational energy at 300K is much smaller than ZPVE and often than Etransf we have omitted it in the picture for simplicity. For internal energy activation the amount of energy is fixed from the beginning of the trajectory.

3. Results and discussion 3.1 Structure of the deprotonated Pro2 precursor peptide. [Pro2-H]- has a large conformational space. Although the carboxylic acid group is the most likely site of deprotonation, several sites are in principle conceivable; i.e. the carboxylate


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group, the N-terminal (N5), and the alpha carbons C1 and C10 (see Figure 3). Another important feature is the conformation of the peptide bond (cis or trans). Although peptide bonds are generally found to be in the trans configuration, amide bonds adjacent to proline residues are frequently found to feature a cis conformation.31,62,63 Therefore, we considered the cis conformation for the peptide bond for all structures. The stability of the six structures that were deemed relevant for [Pro2-H]- unimolecular reactivity were investigated at the PM3 and DFT levels (B3LYP/6-31++G(d,p)), as shown in Figure 3 alongside with the nomenclature used throughout the paper. The atom numbering used to identify relevant atoms in the fragmentations process is indicated for structure 1. Note that the Cα carbon is not usually considered as a deprotonation site, but this possibility (I4 and I5) has been included since simulations show that this site is in fact quite acidic.

(0.00)[0.00]

(10.13)[--]

(9.40)[24.70]

(34.34)[62.46]a)

(2.91)[30.09]

(4.55)[24.51]

(6.84)[--]

Figure 3: Structures and nomenclature of relevant isomers of [Pro2-H] -. Atom numbering for relevant atoms is specified for isomer 1. Relative energies (kcal/mol), without ZPE, computed at the PM3 level are shown within parenthesis and at the B3LYP/6-31++G(d,p) level within brackets. a)Energy for I2’ conformer.

Since the dynamics for the internal energy activation simulations are run on the BornOppenheimer PES without ZPVE, the different energies given throughout this manuscript


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always refer to the bottom of the well of the most stable structure, 1, which is taken as the reference. Energies never include ZPVE except when explicitly stated. For structure I6 it was not possible to find a minimum at the DFT level corresponding to the PM3 structure. For the lowest energy conformer of I2 we could not find a minimum at the DFT level, however the conformer I2’ used for the simulations (see section 3.4 and Figure S6 in the supporting information) was also optimized with DFT. Both energies are shown in Figure 3. PM3 energies are systematically higher than B3LYP ones. Also, the order of stability changes depending on the method used. However, these differences are not very relevant since the energy range on which simulations are run is much higher (Eint ∈ [209 – 451 kcal/mol]). Nevertheless, the most stable structure for both methods corresponds to the one in which the carboxylic group is deprotonated and the peptide bond is cis (structure 1). It agrees with previous studies on singly deprotonated amino acids and short peptides which have shown that deprotonation takes place preferentially at the C-terminus forming a carboxylate anion.28,64,65 To support this result we compared the experimental IRMPD spectrum of deprotonated Pro2 (m/z 211) with the calculated IR spectrum of the carboxylate structure 1 (see Figure 4). The computed spectrum for the C-terminally deprotonated structure 1 nicely matches the experimental one, further justifying the choice of structure 1 as the starting structure for the dynamics simulations.

Figure 4: Comparison of the IRMPD spectrum of the deprotonated precursor peptide Pro2 (black trace) with the DFT-calculated spectrum (blue trace) for carboxylate structure 1.


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3. 2 Reactivity vs. Internal energy Starting from carboxylate 1 we ran both collision and internal energy activation simulations. We observe three kinds of trajectories: (i) trajectories which lead to fragmentation (“Reactives”), (ii) trajectories which isomerize at some time during the trajectory but do not fragment (“Isomerization”), and (iii) trajectories in which none of the two previous events occur (“Non-reactives”). In Figure 5a we report the percentage of each kind of trajectory as a function of the ion’s internal energy for both kinds of simulations. For collisional activation the ion starts with the corresponding ZPVE (154 kcal/mol for 1) + the thermal vibrational energy and we used a collision energy Ecoll = 300 kcal/mol. After the collision the ion’s internal energy is the sum of the ZPVE, the thermal vibrational energy, and the energy transferred during the collision: Eint= ZPVE + thermal vibrational energy + Etransf. The energy transfer is between -2 and 235 kcal/mol, i.e., between -1% and 78 % of the collisional energy. Therefore, the classical internal energy of the ion after the collision is in the 152 –389 kcal/mol energy range. Figure 5a shows the average and standard deviation in the energy transfer for each kind of trajectory: reactives, isomerizing and non-reactives. The final internal energy distribution of the collisional simulations is shown in Figure 5b. The average internal energy for each of the three types of trajectories (reactives (R), isomers (I) and nonreactives(NR)) is 327 ±2 9, 300 ± 54, and 215 ± 56 kcal/mol, respectively. The corresponding percentages of trajectories R, I, and NR (8.7, 0.5, and 90.8%, respectively) are shown in Figure 5a. Most of the trajectories do not react and the ion’s internal energy after the collision for the reactive ones is in the 230 – 390 kcal/mol energy range (Figure 5b). For internal energy activation the ion is given a fixed amount of energy at the beginning of the trajectory. In Figure 5a the lines show the percentage of each kind of trajectory as a function of this internal energy (the corresponding values are reported in Table S2 of the Supporting Information). As expected, reactivity increases with internal energy up to almost 100% for Eint = 501 kcal/mol. Nonetheless, for the first two energies considered, 209 and 250 kcal/mol, there are no reactive trajectories, while it suddenly increases up to 30% for 292 kcal/mol of internal energy. It can be seen as a threshold energy for [Pro2-H]- reactivity under internal energy activation conditions and for the time the trajectories are integrated. If they were integrated for longest times, reactivity may be observed at the lower energies. This 250 kcal/mol threshold is similar, but higher, than the lowest bound of internal energy found for reactive trajectories in the collision activation simulations: 230 kcal/mol (see blue histograms on Figure 5b), which corresponds to the threshold energy for this kind of activation, given the trajectory integration time. For the same range of ion internal energies the percentage of


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reactive trajectories (and isomerization trajectories) is larger when the ion is internally activated than when energy is transferred during the collision process. The percentage of nonreactive trajectories is similar in both cases. This is possibly due to the fact that more time is needed to react (and isomerize) after the collision, since energy redistribution has to occur within the molecule.

Figure 5: Panel a) shows the percentage of trajectories, using 1 as initial structure, that reacted (R, blue circles), isomerized (I, green squares) and did not reacted: non-reactive (NR, black diamonds) for each internal energy considered. Solid filled symbols linked with a line correspond to internal energy activation simulations. The empty symbols stand for collisional activation simulations. The symbol corresponds to the average value of internal energy for non-reactive (black), reactive (blue) and isomer (green) trajectories. The bars are the standard deviation for the internal energy distribution on each kind of trajectories. Panel b) shows, for collisional activation simulations, the distribution of internal energy of [Pro2-H] ion at the end of the trajectory, i.e., after a fraction of the collision energy has been converted into ion’s internal energy in the collision. Grey bars correspond to all the simulations while the blue bars represent the internal energy distribution only for reactive trajectories.


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3.3. Isomerization It is interesting to notice the non-negligible percentage of trajectories showing isomerization, which corresponds mostly to proton transfer reactions. For internal activation this number steadily increases to a maximum of about 20% of the trajectories for Eint = 334 kcal/mol. At higher energies, the percentage decreases again due to the increase of reactive trajectories. In Table 1 we show the percentage of trajectories yielding each of the isomers (over the total number of isomerizations for each set). We consider isomerizations taking place at any point of the trajectory but only for trajectories that did not end in fragmentation. Their structures, relative energies and nomenclature correspond to what is shown in Figure 3.

Table 1: Distribution of the isomers formed during the simulation for each set of trajectories using 1 as initial structure. CID

THERMAL EXCITATION

Ecoll

Internal Energy [kcal/mol]

Isomer

300

209

250

292

334

376

417

459

501

1(a)

--

--

5

3

10

12

8

25

--

I2

--

13

18

5

8

--

--

--

--

I3

--

--

--

1

--

--

--

--

--

I4

32

44

36

58

67

68

46

25

50

I5

--

--

9

19

3

8

38

50

50

I6

66

44

36

12

10

8

--

--

--

others

2

--

--

1

3

4

8

--

--

total

100

100

100

100

100

100

100

100

100

(a)

Trajectories ending up in carboxylate structure 1 but with some H interchange.

We observe different trends for collisional and internal energy activated trajectories. In the first, the predominant isomer is I6, resulting from a nucleophilic attack of one of the carboxylate oxygen atoms onto the electrophilic carbonyl carbon of the peptide linkage. For internal energy activation on the other hand, the other isomers, resulting from proton transfers, are dominant. The most abundantly observed isomer is I4, in which the negative charge moves to the alpha carbon C1. This is in agreement with the fact that I4 is the second lowest energy structure (see Figure 3). The next isomers in order of energy, I5 and I6, are also the next most frequently formed isomers. Isomers I2 and I3 are higher in energy and less


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frequent. The I2 structure lies 10.13 kcal/mol above the minimum energy structure, while I3 is 9.40 kcal/mol higher. However, I3 formation requires initial formation of I2 as can be seen in Scheme S2 of the Supporting Information. This explains the low percentage of I3 observed in the trajectories: its formation implies two steps and the simulation time is probably not long enough to observe both proton transfer and nucleophilic attack of the N-terminal nitrogen onto the carboxylate carbon to form the cycle (see Section 3.5). Formation of isomers I2, I4, and I5 show that the mobile proton model66,67 used to describe fragmentation of protonated peptides can also be applied in this case. This model states that a proton added to the peptide, as the internal energy of the ion increases, does not remain fixed at the site of the greatest proton affinity (PA), but is capable of migrating to positions of lower PA. In the negative counterpart we observe how the proton migrates from different positions with higher proton affinity to positions with lower PA, with the concomitant migration of the negative charge. For [Pro2-H]- we observe three mobile protons: the proton attach to the Nterminal, that yields I2 when it migrates to the C-terminus, but also the protons on each of the two alpha carbons yielding I4 and I5. Proton exchanges from these carbons that are not normally considered as mobile are actually more frequent than from the N-terminus. We computed all the TSs and corresponding IRCs to access isomers I2, I4, I5, and I6 from 1. The IRC energy curves and structures of the reactants, products and TSs are reported in Figures S2-S6 of the Supporting Information, while relative energies of TSs are reported in Table 2. The highest TS corresponds to the 1  I5 isomerization and it lies 37 kcal/mol above the minimum of the potential well for 1. The lowest energy considered in internal energy activation simulations is 209 kcal/mol above this minimum, enough to eventually cross any of the isomerization barriers. For collisional activation simulations, as we showed before, trajectories have a distribution of internal energy in the [152 – 389 kcal/mol] range, therefore, also for these trajectories the ion has enough energy to overcome the barriers. Thus, failure to observe isomerizations in both cases would come from the limited simulation time of 10 ps for internal energy activation and 2-40 ps for collisional activation.


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Table 2: Relative energies (in kcal/mol) of the TSs for the different isomerizations process. TS

[kcal/mol]

TS_I2

18.9

TS_I3

25.9

TS_I4

11.6

TS_I5

36.9

TS_I6

8.65

To better account for the proton mobility in each set of trajectories, we defined an H transfer coefficient, ht, as the number of times that any X-H bond is broken, among all the trajectories of one set, divided by the total number of trajectories of the set. A number close to one would mean that there is one H-transfer per trajectory in the set. The values of ht obtained are shown in Table 3.

Table 3: H transfer coefficient, ht, for the different sets of trajectories. ht is defined as the number of times an X-H bond is broken in the whole set of trajectories divided by the total number of trajectories. ht = 1 means there is one H transfer per trajectory. CID

THERMAL EXCITATION

Ecoll

Internal Energy [kcal/mol]

300

209

250

292

334

376

417

459

501

0.06

0.04

0.20

0.53

0.62

0.92

1.18

1.21

1.38

In general, proton mobility is larger for internal energy activated trajectories than for collisional activation trajectories. Only the set with Eint = 209 kcal/mol shows an ht lower than that for collisional activation. In fact, since the average Eint for the CID simulations is 226 kcal/mol, the value ht = 0.06 agrees well with what could be expected for an internal energy activation simulation at this energy. Nevertheless, this difference in ht values may also be explained by the fact that in internal energy activation trajectories, the activation energy is uniformly distributed within the molecule, so all the X-H bonds are activated and can eventually break. On the other hand, for collisional activation, the energy is acquired by the molecule in the region where the collision takes place, which is not necessarily an X-H bond, and time is required to redistribute the energy.


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3.4 Experimental spectrum and fragment distribution Figure 6 shows the experimental CID mass spectrum of deprotonated Pro2. Note that signals below m/z 45 are not recorded due to the low mass cut-off of the MS. To identify product ions observed

after

fragmentation

we

use

the

standard

nomenclature

for

peptide

fragmentation.30,68,69 Important to note is that we observe mainly the ym/bn ion fragment series and not c- or z- type fragments more typically observed in CID MS/MS spectra of anionic peptides. This fragmentation behaviour can be related to the pyrrolidine ring of the proline residue hindering formation of c- or z- type fragments due to the necessity to break two bonds. The main fragmentation channel is b2/y1 with b2- fragment being dominant, although the y1- fragment is also of significant intensity. From right (high m/z) to left (low m/z) the peaks are: the parent ion [Pro2-H]- (m/z 211), b2- (m/z 193) corresponding to water loss, [C9 H15N2O]- (a2 ion, m/z 167) arising from CO2 loss, y1- (m/z 114) amide bond fragmentation with the charge retained at the C-terminus and, with lower intensity, b1- (m/z 98) amide bond fragmentation with the charge retained at the N-terminus and [H6C4N]- (m/z 68).

Figure 6. Experimental CID mass spectrum for [Pro2-H] - precursor ion. Labelled ions: y1114 m/z – b2- 193 m/z – b1- 98 m/z – a2- 167 m/z and [H6C4N] - m/z.


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We now focus our attention on the fragmentation products obtained from the chemical dynamics simulations. As explained in Section 3.3, different isomers are energetically accessible, but the simulations are in the picosecond time scale such that it is not possible to correctly populate all isomers. Furthermore, as we have described in a recent study,58 once an isomer is populated the system needs extra time to randomize positions and velocities. In other words, by starting trajectories from potential minimum 1, isomerization can occur but in general there will be insufficient time in the simulation for this isomerized species to further react (it occurs for 0-6% of the trajectories in all sets). To overcome this constraint, we also ran trajectories starting from the other five isomers I2, I3, I4, I5 and I6. Note that for isomer I2, the N-terminal deprotonated ion, we started trajectories from a different conformer, I2’, shown in Figure S6, even though its energy is higher (34.34 kcal/mol with respect to the minimum energy structure). The reason is that I2 readily converts into the carboxylate structure 1 while for I2’ isomerization is somewhat hindered since the N-terminal and –COOH terminal groups are further apart than in I2. In this way we observe fragmentation pathways starting at the N-terminally deprotonated ion I2’ and not only I2  1 isomerization. The products found in the simulations are shown in Figure 7.

Figure 7: Isomerizations and subsequent fragmentation products observed for [Pro2-H] - in the chemical dynamics simulations.


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From the simulations we obtain fragment distributions. Reporting the abundance of charged fragments, we derive the predicted m/z distribution that represents a theoretical mass spectrum. Note that these resulting spectra are time dependent since trajectories are stopped at a given time (much shorter than experiments which are on the ~40 ms time scale). To summarize the results for [Pro2-H]-, we show in Figure 8 the m/z distributions of products as obtained from the simulations starting from each of the six isomers. The peak corresponding to the parent ion (211 m/z) is not shown in any of the theoretical spectra. We report internal energy activation simulations corresponding to Eint=334 kcal/mol (intermediate activation energy). In Figures S7-S12 of the Supporting Information we show the predicted mass spectra for each isomer for all internal energies considered.

Figure 8: Theoretical MS/MS spectra of [Pro2-H] - as obtained from simulations. Collisional activation (left panels) and internal energy activation (right panels) for the six starting structures considered: 1, I2’, I3, I4, I5, and I6 from top to bottom.

As we have previously shown increasing the internal energy at the beginning of the trajectory has the effect of increasing the reactivity for all isomers. Also, the number of fragments increases, and consequently the masses of the fragments obtained are smaller. If we compare internal energy activation and collisional activation spectra, we observe that, in general, they are similar in the sense that the fragments obtained are the same. The main differences are


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observed in the relative intensities of the fragments. Details on the ions formed in the simulations are reported for completeness in the Supporting Information (Table S2) and the corresponding mechanisms in Schemes S1-S32 (the most relevant ones are discussed in the next Section). For collisional activation simulations, 99% of the reactive trajectories yield fragments arising from a bond rupture without any prior rearrangement (direct fragmentation mechanisms). This value varies from 92 to 98% for internal energy activation trajectories, where fragmentation pathways involve more structural reorganizations, particularly H transfers, i.e., proton mobility (see ht coefficients in Table 3, which are higher for internal energy than for collisional activation simulations). These mechanistic differences between the two activation modes are also reflected by the fact that while in the internal energy activation simulations the m/z distributions are not very dependent on the initial structure, in the collisional activation simulations, the product distribution varies for the different isomers (see Figure 8). In the mechanisms observed in the simulations (Schemes S1-S32 and following section) the bond rearrangements involved in [Pro2-H]- fragmentation are triggered by the localization of the negative charge (charge-directed fragmentation) in analogy to the charge-directed mechanisms use to explain fragmentation for positively charged peptides. Let us now describe the mechanisms for the main fragmentation pathways.

3.5 Fragmentation mechanisms Particular attention will be paid to the bn and ym ion series, formed by cleavage of the amide bond. As observed for protonated peptides, this is a common fragmentation channel for deprotonated peptides29,30,47 and these fragment ions provide valuable structural information about the peptide sequence. Also, it is the main fragmentation channel observed in the experimental MS/MS spectrum (see Figure 6). Formation and structure of the b2- ion. The b2- fragment of [Pro2-H]- is the base peak in the CID mass spectrum and corresponds to water loss. The main structural candidates for this fragment are ions containing either a diketopiperazine or an oxazolone ring. A comparison of theoretical and experimental IR spectra for this fragment is presented in Figure 9. It is immediately obvious that the b2- ion has a diketopiperazine structure.


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Figure 9: The IRMPD spectrum of the b2-ion from [Pro2-H] - (black in both panels) compared to DFT-calculated spectra (blue and red) for isomeric structures diketopiperazine and oxazolone. Calculated relative-ZPE corrected energies are given for each of the structures. In our simulations, the b2- ion is only observed for trajectories started from the cyclic structure I3 and has an abundance lower than that of the y1- product. The mechanism observed in the simulations is illustrated in Scheme 1. In the case of the collisional simulations, the Ar atom collides with the OH group, triggering the cleavage of the O-C bond resulting in loss of OH-. The OH- ion then abstracts a proton from the nearby α-carbon (C10) forming neutral H2O and the b2- fragment (m/z 193). In some of the collisional simulations (12%) the proton abstracted to form H2O comes from another carbon, C4, C9 or C11, all being spatially close to the ruptured C-O bond. Internal energy activation simulations follow the same mechanism. The C-O bond breaks when enough vibrational energy is placed in the system, yielding OH- that then forms H2O. In some trajectories, the proton is abstracted from the α-carbon of the first proline residue (C1) instead of C10.


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Scheme 1. Fragmentation mechanism leading to the formation of the b2- ion, 193 m/z. It is interesting to note that, in about 61% of the collisional simulation trajectories in which this C-O bond breaks (corresponding to 40 trajectories), the final ion was the hydroxyl group (OH-). On the other hand, for the internal energy activation simulations, the leaving OHalways forms neutral H2O and the b2- ion. The difference is due to the fact that during the collision with Ar, a large amount of energy is transferred to the C-O bond which eventually becomes translational energy of the leaving OH- group. When the leaving OH- has too much translational energy it has no time to interact with any of the hydrogens to form H2O, yielding OH- (which lies below the low mass cutoff in the experiments). Of course, since for the internal activation simulations energy is not localized in any specific bond but distributed among all normal modes, OH- leaves with less translational energy and has sufficient time to abstract one of the nearby protons. This also explains why other protons such as the α-carbon proton of the first proline residue being slightly further away, can be abstracted. As mentioned above, the b2- fragment is the dominant peak in the experimental MS/MS spectrum of [Pro2-H]-, but computationally this fragment is only observed in trajectories started from I3 and with an intensity lower than that of other peaks, such as the y1- ion. We have thus analyzed the pathway going from 1 to I3 in more detail. The first step is isomerization of 1 to form the N-terminal ion I2, followed by a nucleophilic attack of the nitrogen on the carboxylic carbon forming I3, as shown in Scheme 2.

Scheme 2: I3 formation starting from the most stable structure, carboxylate 1.


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A schematic PES for this isomerization process is shown in Figure 10. Relative energies (PM3) for the stationary points are also shown in the figure. The highest TS necessary to pass in order to form I3 lies about 26 kcal/mol higher than the minimum energy structure. Recall that the energies given to the ion at the beginning of the internal energy activation trajectories are between 209 and 501 kcal/mol and therefore the ion has enough energy to complete the whole isomerization process.

Figure 10: Schematic PES for 1  I2  I3 reactions. Relative energies computed at PM3 level for the different stationary points are also shown in the figure. Structures for TS_I2 and TS_I3 are also shown in the figures. The two arrows at the top show the range of internal energy given to the ion in internal energy activation simulations. With the TS energies we can calculate the classical RRKM rate constants as a function of the internal energy, k(E), in order to estimate the time needed for statistical isomerization. We determined the reaction half-life, t1/2(E), i.e. the time needed for 50% of the population to isomerize (t1/2(E) = -(ln 0.5)/k(E)). A plot of t1/2 vs. Eint for both reactions is depicted in Figure S14. Since the value of t1/2(E) is a function of the molecule’s internal energy we report in Table 4 t1/2(E) values for the lowest (201 kcal/mol) and highest (501 kcal/mol) energies given to 1 in internal energy activation simulations.


22

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Table 4: k(E), and t1/2(E) values for the isomerization (1  I2) and backward reaction (I2  1) and isomerization (I2  I3) reactions required to form the I3 ion. Total Energy

k(E)

[kcal/mol]

[sec-1]

t1/2(E) [ps]

1  I2 201

3.981 1010

17.41

501

7.618 1011

9.10

201

1.225·1012

0.57

501

6.144·1012

0.11

201

8.656 1010

8.01

501

11

7.67

I2  1

I2  I3

9.034 10

For internal energy activation we used simulation times of 10 ps. Considering the t1/2 values above, we should expect to observe some trajectories going from 1  I2. Although the reaction times for I2  I3 are on the same order of magnitude, it requires 1  I2 to occur first, as well as time to randomize positions and momenta, making the whole process too long to be observed in a significant number of the 10-ps trajectories (see Table 1). A small percentage of trajectories started at 1 form I2’, and only one in the entire set of trajectories makes it all the way to I3. Of course, for higher energies we expect to find a larger abundance of I2 (and consequently also of I3), but at those high energies there are a large number of competing reactions, especially those leading to fragmentation. This leads to an increase of I2’ isomers up to an intermediate internal energy (334 kcal/mol) and from there on, the number of isomerizations starts to decrease until none are observed for the highest energies. As well, when trajectories are started from I2’ we do not observe many isomerizations to I3 (only 3 trajectories for collisional and 1 for all internal energy activation simulations), because the reaction back to 1 is much faster (see Table 4 and Figure S14 on the Supporting Information). Formation and structure of the y1- ion. The peak at m/z 114 is assigned as the y1- ion. It corresponds to rupture of the amide bond with the charge retained by the C-terminal fragment. In the simulations, we observe several mechanisms leading to y1-. The relative abundances at which each of the different mechanisms occur, starting from each of the


23


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isomers considered, are listed in Tables S6-S11 of the Supporting Information. The most common mechanisms are illustrated in Scheme 3.

Scheme 3. Fragmentation mechanisms resulting in the y1- ion, 114 m/z. In the first mechanism (Scheme 3-a), the I2 isomer is first formed and then the C1-C6 bond breaks yielding the x1- fragment ion. The same mechanism is also observed for some trajectories starting directly from the I2’ isomer. Subsequently, the C6-N8 amide bond breaks, resulting in CO neutral loss and the y1- fragment. An alternative mechanism, displayed in Scheme 3-b, starts with formation of isomer I4 after which the C6-N8 amide bond breaks yielding directly the y1- ion. For some trajectories, a fragment is formed with the same m/z as y1- (m/z 114), but that corresponds to the N-terminal side of the dipeptide. This is possible due to formation of a cyclic structure that eventually opens again in such a way that the carboxylate group is transferred to the N-terminal side of the molecule (see Scheme 4). The other two mechanisms of this kind are shown in Schemes 33 and 34 of the Supporting Information and are not further discussed here.


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Scheme 4: Fragmentation mechanism yielding a fragment ion isobaric with the y1- fragment ion at m/z 114. Formation of the x1- fragment. The x1- fragment systematically appears in the theoretical spectra but is not detected in the experiments. The x1- structure can be considered as a precursor of the y1- fragment. As shown above, most of the mechanisms yielding the y1fragment depend on formation of the x1- anion, which subsequently expels CO to yield y1-. Therefore, the presence of x1- in the theoretical spectra may be due to the simulation time being insufficient to observe a second fragmentation (CO loss) from the primary x1- product. In order to verify the validity of this hypothesis, we ran a series of trajectories starting from the x1- anion. These trajectories were activated with an internal energy of Eint = 119 kcal/mol (ZPVE for x1- anion is 85.58 kcal/mol). Figure 11 shows the time evolution of these trajectories, where one observes that the relative intensity of the y1- ion starts to increase significantly after t ≈ 1 ps and reaches a constant level for t ≈ 3 ps. As expected, y1- is the main product from x1- fragmentation, arising from neutral CO loss. The formate anion at m/z 45, [HCO2]-, starts to appear after t ≈ 3ps and comes from subsequent fragmentations of y1-, but is below the low mass cutoff in the experiments. In Figure S13 of the Supporting Information the results at four internal energies (Eint = 119, 143, 167, and 238 kcal/mol) for 10 ps simulations are presented. With increasing internal energy, the ion fragments further with a concomitant decrease of the y1- peak and increase of the [HCO2]- peak.


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Figure 11: Time evolution of a set of trajectories started from the x1- anion activated with an internal energy equal to 119 kcal/mol (x1- anion ZPVE = 85.58 kcal/mol). The number on the left hand side of each panel is the time in ps, from 0.05 to 10. CO2 loss. The peak at m/z 167 (a2- ion), corresponding to neutral CO2 loss, is the main fragmentation path observed in both types of simulations when started from isomer 1: 89 % of the collisional activation and 48 – 79% of the internal energy activation trajectories. CO2 loss is a common fragmentation channel and is frequently observed in CID mass spectra of negatively charged peptides.25,30,70,71 In this molecule, CO2 loss implies C10-C26 bond rupture. The corresponding bond breaking for I2, I3, I4, and I5 yields the formate ion at m/z 45, [HCO2]-, which is also the main fragmentation channel observed for the internal energy activation simulations of those isomers. The percentages of trajectories where the C10-C26 bond is broken is: 24, 14, 39, 18, and 45 % for I2, I3, I4, I5, and I6 isomers, respectively, in the CID simulations and [12-75%]; [13-70%]; [63-70%]; [38-52%]; and [67-91%] for the internal energy activation. On each range the lowest percentage corresponds to the lowest internal energy and the highest to the highest internal energy. For the intermediate energies the percentage of trajectories where the C10-C26 bond is broken lies within the showed range. For the complete data set see Table S4 and S5. Since this is the main channel in the simulations, but there is no experimental verification for it, we investigated the energetics of CO2 loss via quantum/chemical calculations. Electronic energies were computed while scanning the C10-C26 distance as shown in Figure 12. Two


26

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approaches were employed: (i) a relaxed scan, in which for each fixed C10-C26 distance the geometry of the system is optimized, (ii) a non-relaxed scan in which the C10-C26 distance is changed keeping all other coordinates fixed. The actual dynamics of CO2 loss is expected to be a mix of these two limiting situations. We first note that PM3 curves show barriers that are lower for 1 than for the other isomers, and this is reflected in the larger abundance of CO2 loss for 1 than for any of the other isomers. Note that for I2 it is not possible to perform a relaxed scan, because it forms the HCOOH product and fragments. As well, the energies to pass these barriers are clearly lower than the energy available to the ion in both types of simulations, explaining the high abundance of CO2 (or HCO2-) loss. These calculations are carried out at the same level of theory as the simulations (PM3). For sake of comparison we have also computed the energies for the carboxylate structure 1 (for which CO2 loss is most abundant and has the lowest barrier) at the B3LYP/6-31++G(d,p) level of theory. The energies obtained are similar to the PM3 ones; i.e. the relaxed-scan barrier obtained by DFT is just 13 kcal/mol higher than PM3, while for the non-relaxed, the DFT barrier is 11 kcal/mol lower than the PM3 one. Therefore, we conclude that the abundance of CO2 loss is not largely overestimated due to the use of a semi-empirical Hamiltonian, but is due to an intrinsic feature of the [Pro2H]- potential energy surface.

Figure 12: Potential energy scan along the C10-C26 bond length (CO2 loss for carboxylate 1, or HCO2 for the other isomers I2, I4, and I5). Solid lines are relaxed scans, dashed lines represent energies for rigid scans. The B3LYP/6-31++G(d,p) scan for carboxylate 1 structure is also reported.


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Other fragments. Fragments y1- and b1- are observed in all the theoretical mass spectra with different relative intensities depending on the isomer considered. As well, m/z 68, corresponding to the [H6C4N]- anion, is also present in the mass spectra obtained from all isomers. The a1- fragment is not detected in the experiments. It is mainly present in the internal energy activation simulations, though only at low intensities, and does not appear in any of the CID simulated mass spectra except for trajectories starting from the I6 isomer. For the I6 structure, formation of the a1- ion only requires breakage of one bond (see mechanism in Scheme 35 of the Supporting Information) which means that the a1- ion is obtained by a direct fragmentation mechanism.

4. Conclusions Based on modelling of the unimolecular reactivity of [Pro2-H]- by means of chemical dynamics simulations, we propose mechanisms of formation for the dominant fragment ions. For the most intense peak in the experimental mass spectrum, the b2- ion that is formed by water loss, we suggest that there is only one mechanism which contributes. This mechanism requires formation of the N-terminally deprotonated ion followed by a nucleophilic attack of this nitrogen onto the carboxylic carbon. As a result, the structure of the b2- ion is a diketopiperazine, as confirmed by its IRMPD spectrum, instead of the more typical oxazolone structure seen for several other b2- ions. On the other hand, for the formation of the y1fragment (the second most abundant product ion), our calculations suggest that there are several mechanisms participating in its formation. Concerning the two activation modes for dynamics simulations (collisional with random excitation and internal energy non-random excitation) the main differences encountered are in terms of relative peak intensities and mechanisms, while the type of fragments found are generally the same. We also show that theoretical CID mass spectra are more dependent on the initial structure than internal activation ones. This is mainly due to the fact that the collisional activation leads to a larger number of direct fragmentation mechanisms while for internal activation there is more likely to be rearrangements before fragmentation, following more statistical mechanisms. For internal energy activation simulations, in particular, we show that the proton mobility observed in positively charged peptides (and all the corresponding “rules”) can also be applied to the negatively charged peptides, and proton mobility is crucial in determining the fragmentation patterns. However, it does not necessarily imply proton transfer from the N-terminus to the C-terminus prior to fragmentation but also to


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the two alpha carbons, which bear relatively acidic protons that can participate in the proton exchanges taking place. Supporting Information IRCs for isomerization reactions Comparison of I2 and I2’ structures Experimental and computed MS/MS spectra for all the isomers Half-life time plot for I1  I2  I3 A, B, and C parameters for CID simulations Tables of reactivity and probabilities of fragmentation pathways Mechanisms for the fragmentation pathways

Acknowledgments We thank ANR DynBioReact (Grant Number ANR-14-CE06-0029-01) and the National Science Foundation under grant CHE-1416428 for support. W.L.H. also acknowledges support from the Robert A. Welch Foundation under grant No. D-0005. A.M.S. acknowledges support by the Comunidad Autónoma de Madrid under grant 2016-T2/IND-1660. The authors acknowledge the excellent assistance from the FELIX operators and staff. J.M., J.G and J.O. acknowledge financial support by NWO Chemical Sciences under VICI project nr. 724.011.002.

References (1) Steen, H.; Mann, M.: The ABC's (and XYZ's) of peptide sequencing. Nature Reviews Molecular Cell Biology 2004, 5, 699. (2) Aebersold, R.; Goodlett, D. R.: Mass spectrometry in proteomics. Chemical Reviews 2001, 101, 269-296. (3) Yates, J. R.: Mass spectrometry and the age of the proteome. Journal of Mass Spectrometry 1998, 33, 1-19. (4) Altuntas, E.; Schubert, U. S.: "Polymeromics": Mass spectrometry based strategies in polymer science toward complete sequencing approaches: A review. Analytica Chimica Acta 2014, 808, 56-69. (5) Bensimon, A.; Heck, A. J. R.; Aebersold, R.: Mass spectrometry-based proteomics and network biology. Annual Review of Biochemistry 2012, 81, 379-405. (6) Yates, J. R.; Ruse, C. I.; Nakorchevsky, A.: Proteomics by mass spectrometry: Approaches, advances, and applications. Annual Review of Biomedical Engineering 2009, 11, 49-79. (7) Köfeler, H. C.; Fauland, A.; Rechberger, G. N.; Trötzmüller, M.: Mass spectrometry based lipidomics: An overview of technological platforms. Metabolites 2012, 2, 19-38. ACS Paragon Plus Environment

29


Page 30 of 51

(8) Mishur, R. J.; Rea, S. L.: Applications of mass spectrometry to metabolomics and metabonomics: Detection of biomarkers of aging and of age-related diseases. Mass Spectrometry Reviews 2012, 31, 70-95. (9) Gstaiger, M.; Aebersold, R.: Applying mass spectrometry-based proteomics to genetics, genomics and network biology. Nature Reviews Genetics 2009, 10, 617-627. (10) Herrero, M.; Simó, C.; García-Cañas, V.; Ibáñez, E.; Cifuentes, A.: Foodomics: MS-based strategies in modern food science and nutrition. Mass Spectrometry Reviews 2012, 31, 49-69. (11) Riley, N. M.; Rush, M. J. P.; Rose, C. M.; Richards, A. L.; Kwiecien, N. W.; Bailey, D. J.; Hebert, A. S.; Westphall, M. S.; Coon, J. J.: The negative mode proteome with activated ion negative electron transfer dissociation (AI-NETD). Molecular & Cellular Proteomics 2015, 14, 2644-2660. (12) Kalli, A.; Grigorean, G.; Hakansson, K.: Electron induced dissociation of singly deprotonated peptides. Journal of The American Society for Mass Spectrometry 2011, 22, 2209-2221. (13) Ewing, N. P.; Cassady, C. J.: Dissociation of multiply charged negative ions for hirudin (54-65), fibrinopeptide B, and insulin A (oxidized). Journal of The American Society for Mass Spectrometry 2001, 12, 105-116. (14) Jai-nhuknan, J.; Cassady, C. J.: Negative ion postsource decay time-of-flight mass spectrometry of peptides containing acidic amino acid residues. Analytical Chemistry 1998, 70, 5122-5128. (15) Vinh, J. l.; Loyaux, D.; Redeker, V.; Rossier, J.: Sequencing branched peptides with CID/PSD MALDI-TOF in the low-picomole range: Application to the structural study of the posttranslational polyglycylation of tubulin. Analytical Chemistry 1997, 69, 3979-3985. (16) Clipston, N. L.; Jai-nhuknan, J.; Cassady, C. J.: A comparison of negative and positive ion time-of-flight post-source decay mass spectrometry for peptides containing basic residues. International Journal of Mass Spectrometry 2003, 222, 363-381. (17) Dalpathado, D. S.; Desaire, H.: Glycopeptide analysis by mass spectrometry. Analyst 2008, 133, 731-738. (18) Engholm-Keller, K.; Larsen, M. R.: Technologies and challenges in largescale phosphoproteomics. PROTEOMICS 2013, 13, 910-931. (19) Kiraga, J.; Mackiewicz, P.; Mackiewicz, D.; Kowalczuk, M.; Biecek, P. Ç.; Polak, N.; Smolarczyk, K.; Dudek, M. R.; Cebrat, S.: The relationships between the isoelectric point and: length of proteins, taxonomy and ecology of organisms. BMC Genomics 2007, 8, 163. (20) Leymarie, N.; Zaia, J.: Effective use of mass spectrometry for glycan and glycopeptide structural analysis. Analytical Chemistry 2012, 84, 3040-3048. (21) Robinson, M. R.; Moore, K. L.; Brodbelt, J. S.: Direct identification of tyrosine sulfation by using ultraviolet photodissociation mass spectrometry. Journal of The American Society for Mass Spectrometry 2014, 25, 1461-1471. (22) Bilusich, D.; Bowie, J. H.: Fragmentations of (M–H)- anions of underivatised peptides. Part 2: Characteristic cleavages of Ser and Cys and of disulfides and other posttranslational modifications, together with some unusual internal processes. Mass Spectrometry Reviews 2009, 28, 20-34. (23) Bowie, J. H.; Brinkworth, C. S.; Dua, S.: Collision-induced fragmentations of the (M-H)− parent anions of underivatized peptides: An aid to structure determination and some unusual negative ion cleavages. Mass Spectrometry Reviews 2002, 21. ACS Paragon Plus Environment

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(24) Chass, G. A.; Marai, C. N. J.; Harrison, A. G.; Csizmadia, I. G.: Fragmentation reactions of a2 ions derived from deprotonated dipeptides - A synergy between experiment and theory. The Journal of Physical Chemistry A 2002, 106, 9695-9704. (25) Harrison, A. G.: Sequence-specific fragmentation of deprotonated peptides containing H or alkyl side chains. Journal of The American Society for Mass Spectrometry 2001, 12, 1-13. (26) Gu, C.; Tsaprailis, G.; Breci, L.; Wysocki, V. H.: Selective gas-phase cleavage at the peptide bond C-terminal to aspartic acid in fixed-charge derivatives of Aspcontaining peptides. Analytical Chemistry 2000, 72, 5804-5813. (27) Perkins, B. R.; Chamot-Rooke, J.; Yoon, S. H.; Gucinski, A. C.; Somogyi, A.; Wysocki, V. H.: Evidence of diketopiperazine and oxazolone structures for HA b2+ Ion. Journal of the American Chemical Society 2009, 131, 17528-17529. (28) Grzetic, J.; Oomens, J.: Spectroscopic evidence for an oxazolone structure in anionic b-type peptide fragments. Journal of The American Society for Mass Spectrometry 2012, 23, 290-300. (29) Harrison, A. G.; Young, A. B.: Fragmentation of deprotonated Nbenzoylpeptides: Formation of deprotonated oxazolones. Journal of The American Society for Mass Spectrometry 2004, 15, 446-456. (30) Harrison, A. G.; Young, A. B.: Fragmentation reactions of deprotonated peptides containing proline. The proline effect. Journal of Mass Spectrometry 2005, 40, 1173-1186. (31) Martens, J. K.; Grzetic, J.; Berden, G.; Oomens, J.: Gas-phase conformations of small polyprolines and their fragment ions by IRMPD spectroscopy. International Journal of Mass Spectrometry 2015, 377, 179-187. (32) Hunt, D. F.; Yates, J. R.; Shabanowitz, J.; Winston, S.; Hauer, C. R.: Protein sequencing by tandem mass spectrometry. Proceedings of the National Academy of Sciences of the United States of America 1986, 83, 6233-6237. (33) Brodbelt, J. S.: Ion activation methods for peptides and proteins. Analytical Chemistry 2016, 88, 30-51. (34) Homayoon, Z.; Pratihar, S.; Dratz, E.; Snider, R.; Spezia, R.; Barnes, G. L.; Macaluso, V.; Martin-Somer, A.; Hase, W. L.: Model simulations of the thermal dissociation of the TIK(H+)(2) tripeptide: Mechanisms and kinetic parameters. Journal of Physical Chemistry A 2016, 120, 8211-8227. (35) Meroueh, S. O.; Wang, Y.; Hase, W. L.: Direct dynamics simulations of collision- and surface-induced dissociation of N-protonated glycine. Shattering fragmentation. The Journal of Physical Chemistry A 2002, 106, 9983-9992. (36) Ortiz, D.; Martin-Gago, P.; Riera, A.; Song, K.; Salpin, J. Y.; Spezia, R.: Gasphase collision induced dissociation mechanisms of peptides: Theoretical and experimental study of N-formylalanylamide fragmentation. International Journal of Mass Spectrometry 2013, 335, 33-44. (37) Spezia, R.; Lee, S. B.; Cho, A.; Song, K.: Collision-induced dissociation mechanisms of protonated penta- and octa-glycine as revealed by chemical dynamics simulations. International Journal of Mass Spectrometry 2015, 392, 125-138. (38) Spezia, R.; Martens, J.; Oomens, J.; Song, K.: Collision-induced dissociation pathways of protonated Gly2NH2 and Gly3NH2 in the short time-scale limit by chemical dynamics and ion spectroscopy. International Journal of Mass Spectrometry 2015, 388, 40-52. (39) Rossich-Molina, E.; Eizaguirre, A.; Haldys, V.; Urban, D.; Doisneau, G.; Bourdreux, Y.; Beau, J. M.; Salpin, J. Y.; Spezia, R.: Characterization of protonated model ACS Paragon Plus Environment

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disaccharides from tandem mass spectrometry and chemical dynamics simulations. Chemphyschem 2017, 18, 2812-2823. (40) Ortiz, D.; Salpin, J. Y.; Song, K.; Spezia, R.: Galactose-6-Sulfate collision induced dissociation using QM plus MM chemical dynamics simulations and ESI-MS/MS experiments. International Journal of Mass Spectrometry 2014, 358, 25-35. (41) Rossich-Molina, E.; Ortiz, D.; Salpin, J. Y.; Spezia, R.: Elucidating collision induced dissociation products and reaction mechanisms of protonated uracil by coupling chemical dynamics simulations with tandem mass spectrometry experiments. Journal of Mass Spectrometry 2015, 50, 1340-1351. (42) Rossich-Molina, E.; Salpin, J. Y.; Spezia, R.; Martinez-Nunez, E.: On the gas phase fragmentation of protonated uracil: a statistical perspective. Physical Chemistry Chemical Physics 2016, 18, 14980-14990. (43) Lee, G.; Park, E.; Chung, H.; Jeanvoine, Y.; Song, K.; Spezia, R.: Gas phase fragmentation mechanisms of protonated testosterone as revealed by chemical dynamics simulations. International Journal of Mass Spectrometry 2016, 407, 40-50. (44) Kassel, L. S.: Studies in homogeneous gas reactions. I. The Journal of Physical Chemistry 1927, 32, 225-242. (45) Marcus, R. A.: Unimolecular dissociations and free radical recombination reactions. The Journal of Chemical Physics 1952, 20, 359-364. (46) Rice, O. K.; Ramsperger, H. C.: Theories of unimolecular gas reactions at low pressures. Journal of the American Chemical Society 1927, 49, 1617-1629. (47) Martens, J.; Grzetic, J.; Berden, G.; Oomens, J.: Structural identification of electron transfer dissociation products in mass spectrometry using infrared ion spectroscopy. Nature Communications 2016, 7, 11754. (48) Martens, J.; Berden, G.; Gebhardt, C. R.; Oomens, J.: Infrared ion spectroscopy in a modified quadrupole ion trap mass spectrometer at the FELIX free electron laser laboratory. Review of Scientific Instruments 2016, 87, 103108. (49) Stewart, J. J. P.: Optimization of parameters for semiempirical methods I. Method. Journal of Computational Chemistry 1989, 10, 209-220. (50) Becke, A. D.: A new mixing of Hartree-Fock and local density-functional theories. The Journal of Chemical Physics 1993, 98, 1372-1377. (51) Lee, C. T.; Yang, W. T.; Parr, R. G.: Development of the Colle-Salvetti correlation-energy formula into a functional of the electron-density. Physical Review B 1988, 37, 785-789. (52) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; et al.: Gaussian 09. Revision D. 01 ed.: Wallingford, CT, 2013. (53) Baer, T.; Hase, W. L.: Unimolecular Reaction Dynamics. Theory and Experiments: New York, 1996. (54) Zhu, L.; Hase, W. L.: A General RRKM Program. QCPE Bull. 1994, 14, 664. (55) 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.; Zhu, L.; Varandas, A.; Wang, H.; Wolf, R. J.: VENUS. A General Chemical Dynamics Compuer Program. QCPE Bull. 1996, 16, 671. (56) Stewart, J. J. P.; Fiedler, L. J.; Zhang, P.; Zheng, J.; Rossi, I.; Hu, W.-P.; Lynch, G. C.; Liu, Y.-P.; Chuang, Y.-Y.; Pu, J.; Li, J.; Cramer, C. J.; Fast, P. L.; Truhlar, D. G.: MOPAC 5.022mn. Department of Chemistry and Supercomputing Institute, University of Minnesota, Menneapolis, MN 55455-0431, USA. (57) Meroueh, O.; Hase, W. L.: Collisional zctivation of small peptides. The Journal of Physical Chemistry A 1999, 103, 3981-3990. ACS Paragon Plus Environment

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Page 33 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(58) Spezia, R.; Martin-Somer, A.; Macaluso, V.; Homayoon, Z.; Pratihar, S.; Hase, W. L.: Unimolecular dissociation of peptides: statistical vs. non-statistical fragmentation mechanisms and time scales. Faraday Discussions 2016, 195, 599-618. (59) Peslherbe, G. H.; Wang, H.; Hase, W. L.: Monte Carlo Sampling for cassical trajectory simulations. In Advances in Chemical Physics; John Wiley & Sons, Inc., 2007; pp 171-201. (60) Verlet, L.: Computer "experiments" on classical fluids. I. Thermodynamical properties of Lennard-Jones molecules. Physical Review 1967, 159, 98-103. (61) Hase, W. L.; Buckowski, D. G.: Monte carlo sampling of a microcanonical ensemble of classical harmonic oscillators. Chemical Physics Letters 1980, 74, 284-287. (62) Jabs, A.; Weiss, M. S.; Hilgenfeld, R.: Non-proline Cis peptide bonds in proteins. Journal of Molecular Biology 1999, 286, 291-304. (63) Pal, D.; Chakrabarti, P.: Cis peptide bonds in proteins: residues involved, their conformations, interactions and locations. Journal of Molecular Biology 1999, 294, 271-288. (64) Oomens, J.; Steill, J. D.: The structure of deprotonated tri-alanine and its a3 fragment anion by IR spectroscopy. Journal of The American Society for Mass Spectrometry 2010, 21, 698-706. (65) Oomens, J.; Steill, J. D.; Redlich, B.: Gas-Phase IR Spectroscopy of deprotonated amino acids. Journal of the American Chemical Society 2009, 131, 43104319. (66) Zhang, Z.: Prediction of low-energy collision-induced dissociation spectra of peptides. Analytical Chemistry 2004, 76, 3908-3922. (67) Dongré, A. R.; Jones, J. L.; Somogyi, Á.; Wysocki, V. H.: Influence of peptide composition, gas-phase basicity, and chemical modification on fragmentation efficiency: An evidence for the mobile proton model. Journal of the American Chemical Society 1996, 118, 8365-8374. (68) Biemann, K.: Contributions of mass spectrometry to peptide and protein structure. Biological Mass Spectrometry 1988, 16, 99-111. (69) Roepstorff, P.; Fohlman, J.: Proposal for a common nomenclature for sequence ions in mass-spectra peptides. Biomedical Mass Spectrometry 1984, 11, 601601. (70) Harrison, A. G.; Siu, K. W. M.; El Aribi, H.: Amide bond cleavage in deprotonated tripeptides: a newly discovered pathway to '' b(2) ions. Rapid Communications in Mass Spectrometry 2003, 17, 869-875. (71) Waugh, R. J.; Bowie, J. H.; Gross, M. L.; Vollmer, D.: Collision-induced dissociations of deprotonated peptides, dipeptides and tripeptieas containing proline. International Journal of Mass Spectrometry and Ion Processes 1994, 133, 165-174.


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TOC Graphic


34

Page 35 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


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The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


Page 36 of 51

Page 37 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


N

N

10

1

N

+

N

N 9

H

O I3

O

1

29

O

HO O

H N

H

H

O 28

O H N

O

H 11

4

N

H

OH

O

OH H

O

O H

N

O

m/z 193.22

OH H

O N

N H I2


N H

O I3

b2-

H2O

The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40


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% of trajectories

100 90 a) Collision 80 70 60 50 40 30 20 I 10 0 0.20 b)

P(E)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


NR

Internal

R

0.15 0.10

Eint = ZPVE + Etransf

0.05 0 150 200 250 300 350 400 450 500

Internal energy [kcal/mol]


Experimental CID spectrum -

[pro2-H]


x1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

0

y1

O

H N

b2

''b2

O

O

Page 40 of 51

-

a2

H N

H

a1

1 b1

y1

[H6C4N] 20

40

60

-

80

b1

-

-

-

[pro2-H] a2

-

100 120 140 160 180 200 220 240 m/z


Page 41 of 51

O

OH

O


H 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

HO

O N

O

N

H

N

N N

H

I3

N

H O

O

I2 O HO

O

H

H

N

H N

[H6C4N]-

H

a2-

N

H

O

I4 O

HO

1

O

!#'"($%&

O H

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y1

I5

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x1-

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H

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H

N

H

O H N

H

H N

O

O

O

b2-

H

O H N

O

H H N

O

O

H

N H

I6


a1-

H

b1-


Internal Energy Activation

Ecoll = 300 kcal/mol

Eint = 334 kcal/mol

1

-

I5 -

0.5

[HCO2]

I6

0.5 20

40

60

-

[H6C4N] -

[H6C4N]

x1 -

y1

a2 x1

0.5

x1

y1

-

a2

-

-

b1

[H6C4N]

-

[HCO2]

[HCO2]

0.0 0

-

y1

a1

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-

b1

a1

-

b1

-

y1

x1

-

-

x1

[H13C9N2O]

b1

-

a1

b2

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b1

0.5

1

[HCO2]

y1

y1

-

x1

-

x1

[H6C4N]

[H6C4N]

-

[HCO2]

1.0

-

-

b1

-

y1

-

a1

-

y1

-

y1

b1

x1

-

-

-

1.0 I4

[HCO2]

-

[OH]

1.0

[H6C4N]

-

-

0.5

-

-

a1

1.0

-

a2

1.0

-

[HCO2]

-

I3

0.5

x1

y1

b1

b1

a1

b1

-

[HCO2]

80 100 120 140 160 180 200 220 20

40

m/z

60

-

a1

-

y1

a2

0.5 0 1.0 0.5 1.0

-

a2

0.5

-

1.0

-

x1

80 100 120 140 160 180 200 220

m/z ACS Paragon Plus Environment

-

b2

a2

-

b1

-

a2

-

x1

-

[HCO2]

[H6C4N]

1.0

-

[H6C4N]

-

0.5

x1

-

I2

-

[HCO2]

-

y1

[H6C4N]

0.5 1.0

-

-

a2

b1

0.5 0.0

Relative Intensity

Collisional Activation

[H6C4N]

1.0

Relative Intensity

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

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8

Unimolecular Fragmentation of Deprotonated Diproline [Pro2-H

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