Role of Chemical Dynamics Simulations in Mass Spectrometry Studies of Collision-Induced Dissociation and Collisions of Biological Ions with Organic Surfaces

Predicting Collision-Induced-Dissociation Tandem Mass Spectra (CID-MS/MS) Using Ab Initio Molecular Dynamics

Compound identification is at the center of metabolomics, usually by comparing experimental mass spectra against library spectra. However, most compounds are not commercially available to generate library spectra. Hence, for such compounds, MS/MS spectra need to be predicted. Machine learning and heuristic models have largely failed except for lipids. Here, quantum chemistry software can be used to predict mass spectra. However, quantum chemistry predictions for collision induced dissociation (CID) mass spectra in LC-MS/MS are rare. We present the CIDMD (Collision-Induced Dissociation via Molecular Dynamics) framework to model CID-based MS/MS spectra. It uses first-principles molecular dynamics (MD) to simulate the physical process of molecular collisions in CID tandem mass spectrometry. First, molecular ions are constructed at specific protonation sites. Using density functional theory, these protonated ions are targeted by argon collider gas atoms at user-specified velocities. Subsequent bond breakages are simulated over time for at least 1,000 fs. Each simulation is repeated multiple times from various collisional directions. Fragmentations are accumulated over those repeated collisions to generate CIDMD in silico mass spectra. Twelve small metabolites (<205 Da) were selected to test the accuracy of this framework in comparison to experimental MS/MS spectra. When testing different protomers, collider velocities, number of simulations, simulation time and impact factor b cutoffs, we yielded 261 predicted mass spectra. These in silico spectra resulted in entropy similarity scores of an average 624 ± 189 for all 261 spectra compared to their corresponding experimental spectra, which improved to 828 ± 77 when using optimal parameters of the most probable protomers for 12 molecules. With increasing molecular mass, higher velocities achieved better results. Similarly, different protomers showed large differences in fragmentation; hence, with increasing numbers of protomers and tautomers, the average CIDMD prediction accuracy decreased. Mechanistic details showed that specific fragment ions can be produced from different protomers via multiple fragmentation pathways. We propose that CIDMD is a suitable tool to predict mass spectra of small metabolites like produced by the gut microbiome.

Molecular Dynamics Simulations of Soft and Reactive Landing of Proteins Desorbed by Argon Cluster Bombardment

Reactive molecular dynamics (MD) simulations were conducted to investigate the soft and reactive landing of hyperthermal velocity proteins transferred to a vacuum using large argon clusters. Experimentally, the interaction of argon cluster ion beams (Ar1000-5000+) with a target biofilm was previously used in such a manner to transfer lysozymes onto a collector with the retention of their bioactivity, paving the way to a new solvent-free method for complex biosurface nanofabrication. However, the experiments did not give access to a microscopic view of the interactions needed for their full understanding, which can be provided by the MD model. Our reactive force field simulations clarify the landing mechanisms of the lysozymes and their fragments on collectors with different natures (gold- and hydrogen-terminated graphite). The results highlight the conditions of soft and reactive landing on rigid surfaces, the effects of the protein structure, energy, and incidence angle before landing, and the adhesion forces with the collector substrate. Many of the obtained results can be generalized to other soft and reactive landing approaches used for biomolecules such as electrospray ionization and matrix-assisted laser desorption ionization.

A spectroscopic test suggests that fragment ion structure annotations in MS/MS libraries are frequently incorrect

Modern untargeted mass spectrometry (MS) analyses quickly detect and resolve thousands of molecular compounds. Although features are readily annotated with a molecular formula in high-resolution small-molecule MS applications, the large majority of them remains unidentified in terms of their full molecular structure. Collision-induced dissociation tandem mass spectrometry (CID-MS2) provides a diagnostic molecular fingerprint to resolve the molecular structure through a library search. However, for de novo identifications, one must often rely on in silico generated MS2 spectra as reference. The ability of different in silico algorithms to correctly predict MS2 spectra and thus to retrieve correct molecular structures is a topic of lively debate, for instance in the CASMI contest. Underlying the predicted MS2 spectra are the in silico generated product ion structures, which are normally not used in de novo identification, but which can serve to critically assess the fragmentation algorithms. Here we evaluate in silico generated MSn product ion structures by comparison with structures established experimentally by infrared ion spectroscopy (IRIS). For a set of three dozen product ion structures from five precursor molecules, we find that virtually all fragment ion structure annotations in three major in silico MS2 libraries (HMDB, METLIN, mzCloud) are incorrect and caution the reader against their use for structure annotation of MS/MS ions.

Collision Induced Dissociation of Deprotonated Isoxazole and 3-Methyl Isoxazole via Direct Chemical Dynamics Simulations

Isoxazoles are an important class of organic compounds widely employed in synthesis and drug design. Fragmentation chemistry of the parent isoxazole molecule and its substituents has been the subject of several experimental and theoretical investigations. Collision induced dissociation (CID) of isoxazole and its substituents has been studied experimentally under negative ion conditions. Based on the observed reaction products, dissociation patterns were proposed. In the present work, we studied the dissociation chemistry of deprotonated isoxazole and 3-methyl isoxazole using electronic structure theory calculations and direct chemical dynamics simulations. Various deprotonated isomers of these molecules were activated by collision with an Ar atom, and the ensuing fractionation patterns were studied using on-the-fly classical trajectory simulations at the density functional B3LYP/6-31+G* level of electronic structure theory. A variety of reaction products and pathways were observed, and it was found that a nonstatistical shattering mechanism dominates the CID dynamics of these molecules. Simulation results are compared with experiments, and detailed atomic level dissociation mechanisms are presented.

A self-adapting first-principles exploration on the dissociation mechanism in sodiated aldohexose pyranoses assisted with neural network potentials

Understanding the mechanism of collision-induced dissociation (CID) in mono-saccharides with density functional theory (DFT) is challenging because of many possible reaction paths that originate from their high structural diversity. To search for the transition state (TS) from the huge number of conformers, we propose a three-step search scheme with the assistance of neural network potential (NNP). The search starts from a cross-checking of sugars, to a global search of all possible channels, and in the end, an exhaustive exploration around the low-lying channels. The cross-checking step quickly adapts the NNP from the studied molecules to the target ones. The other two steps utilize the adapted NNP to find the available pathways via random sampling of the structures. The study of the CID reactions in all eight types of aldohexose pyranoses was applied using the search scheme. The DFT calculations on AH-0 (Glc, Gal, and Man) in the previous study were utilized to construct an NNP and provide the TS structure database for searching AH-1 (All, Alt, Gul, Ido, and Tal). In total, we identified around 5200 TSs in AH-0 and AH-1, and the final NNP covers an energy range of more than 500 kJ mol^-1 with a mean absolute error of energy less than 4 kJ mol^-1. The search scheme is useful not only for saccharides but also for highly flexible bio-molecules.

Quantum versus classical unimolecular fragmentation rate constants and activation energies at finite temperature from direct dynamics simulations

In the present work, we investigate how nuclear quantum effects modify the temperature dependent rate constants and, consequently, the activation energies in unimolecular reactions. In the reactions under study, nuclear quantum effects mainly stem from the presence of a large zero point energy. Thus, we investigate the behavior of methods compatible with direct dynamics simulations, the quantum thermal bath (QTB) and ring polymer molecular dynamics (RPMD). To this end, we first compare them with quantum reaction theory for a model Morse potential before extending this comparison to molecular models. Our results show that, in particular in the temperature range comparable with or lower than the zero point energy of the system, the RPMD method is able to correctly capture nuclear quantum effects on rate constants and activation energies. On the other hand, although the QTB provides a good description of equilibrium properties including zero-point energy effects, it largely overestimates the rate constants. The origin of the different behaviours is in the different distance distributions provided by the two methods and in particular how they differently describe the tails of such distributions. The comparison with transition state theory shows that RPMD can be used to study fragmentation of complex systems for which it may be difficult to determine the multiple reaction pathways and associated transition states.

Calculation of Mass Spectra with the QCxMS Method for Negatively and Multiply Charged Molecules

Analysis and validation of a mass spectrometry (MS) experiment are usually performed by comparison to reference spectra. However, if references are missing, measured spectra cannot be properly matched. To close this gap, the Quantum Chemical Mass Spectrometry (QCxMS) program has been developed. It enables fully automatic calculations of electron ionization (EI) and positive ion collision-induced dissociation (CID) mass spectra of singly charged molecular ions. In this work, the extension to negative and multiple ion charge for the CID run mode is presented. QCxMS is now capable of calculating structures carrying any charge, without the need for pretabulated fragmentation pathways or machine learning of database spectra. Mass spectra of four single negatively charged and two multiple positively charged organic ions with molecular sizes from 12 to 92 atoms were computed and compared to reference spectra. The underlying Born-Oppenheimer molecular dynamics (MD) calculations were conducted using the semiempirical quantum mechanical GFN2-xTB method, while for some small molecules, ab initio DFT-based MD simulations were performed. Detailed insights into the fragmentation pathways were gained, and the effects of the computed charge assignments on the resulting spectrum are discussed. Especially for the negative ion mode, the influence of the deprotonation site to create the anion was found to be substantial. Doubly charged fragments could successfully be calculated fully automatically for the first time, while higher charged structures introduced severe assignment problems. Overall, this extension of the QCxMS program further enhances its applicability and underlines its value as a sophisticated toolkit for CID-based tandem MS structure elucidation.

Efficient and Accurate Description of Diels-Alder Reactions Using Density Functional Theory

Modeling chemical reactions using Quantum Chemistry is a widely used predictive strategy capable to complement experiments in order to understand the intrinsic mechanisms guiding the chemicals towards the most favorable reaction products. However, at this purpose, it is mandatory to use reliable and computationally tractable theoretical methods. In this work, we focus on six Diels-Alder reactions of increasing complexity and perform an extensive benchmark of middle- to low-cost computational approaches to predict the characteristic reactions energy barriers. We found that Density Functional Theory, using the ωB97XD, LC-ωPBE, CAM-B3LYP, M11 and MN12SX functionals, with empirical dispersion corrections coupled to an affordable 6-31G basis set, provides quality results for this class of reactions, at a small computational effort. Such efficient and reliable simulation protocol opens perspectives for hybrid QM/MM molecular dynamics simulations of Diels-Alder reactions including explicit solvation.

Surface-induced Dissociation Mass Spectrometry as a Structural Biology Tool

Native mass spectrometry (nMS) is evolving into a workhorse for structural biology. The plethora of online and offline preparation, separation, and purification methods as well as numerous ionization techniques combined with powerful new hybrid ion mobility and mass spectrometry systems has illustrated the great potential of nMS for structural biology. Fundamental to the progression of nMS has been the development of novel activation methods for dissociating proteins and protein complexes to deduce primary, secondary, tertiary, and quaternary structure through the combined use of multiple MS/MS technologies. This review highlights the key features and advantages of surface collisions (surface-induced dissociation, SID) for probing the connectivity of subunits within protein and nucleoprotein complexes and, in particular, for solving protein structure in conjunction with complementary techniques such as cryo-EM and computational modeling. Several case studies highlight the significant role SID, and more generally nMS, will play in structural elucidation of biological assemblies in the future as the technology becomes more widely adopted. Cases are presented where SID agrees with solved crystal or cryoEM structures or provides connectivity maps that are otherwise inaccessible by "gold standard" structural biology techniques.

Collision-induced dissociation of protonated uracil water clusters probed by molecular dynamics simulations

Collision-induced dissociation experiments of hydrated molecular species can provide a wealth of important information. However, they often need a theoretical support to extract chemical information. In the present article, in order to provide a detailed description of recent experimental measurements [Braud et al., J. Chem. Phys., 2019, 150, 014303], collision simulations between low-energy protonated uracil water clusters (H₂O)_1-7,11,12UH⁺ and an Ar atom were performed using a quantum mechanics/molecular mechanics formalism based on the self-consistent-charge density-functional based tight-binding method. The theoretical proportion of formed neutral vs. protonated uracil containing clusters, total fragmentation cross sections as well as the mass spectra of charged fragments are consistent with the experimental data which highlights the accuracy of the present simulations. They allow to probe which fragments are formed on the short time scale and rationalize the location of the excess proton on these fragments. We demonstrate that this latter property is highly influenced by the nature of the aggregate undergoing the collision. Analyses of the time evolution of the fragments populations and of their relative abundances demonstrate that, up to 7 water molecules, a direct dissociation mechanism occurs after collision whereas for 11 and 12 water molecules a statistical mechanism is more likely to participate. Although scarce in the literature, the present simulations appear as a useful tool to complement collision-induced dissociation experiments of hydrated molecular species.

Exploring the Effects of Methylation on the CID of Protonated Lysine: A Combined Experimental and Computational Approach

We report the results of experiments, simulations, and DFT calculations that focus on describing the reaction dynamics observed within the collision-induced dissociation of l-lysine-H⁺ and its side-chain methylated analogues, N_ε-methyl-l-lysine-H⁺ (Me₁-lysine-H⁺), N_ε,N_ε-dimethyl-l-lysine-H⁺ (Me₂-lysine-H⁺), and N_ε,N_ε,N_ε-trimethyl-l-lysine-H⁺ (Me₃-lysine-H⁺). The major pathways observed in the experimental measurements were m/z 130 and 84, with the former dominant at low collision energies and the latter at intermediate to high collision energies. The m/z 130 peak corresponds to loss of N(CH₃)_nH_3-n, while m/z 84 has the additional loss of H₂CO₂ likely in the form of H₂O + CO. Within the time frame of the direct dynamics simulations, m/z 130 and 101 were the most populous peaks, with the latter identified as an intermediate to m/z 84. The simulations allowed for the determination of several reaction pathways that result in these products. A graph theory analysis enabled the elucidation of the significant structures that compose each peak. Methylation results in the preferential loss of the side-chain amide group and a reduction of cyclic structures within the m/z 84 peak population in simulations.

Determination of kinetic properties in unimolecular dissociation of complex systems from graph theory based analysis of an ensemble of reactive trajectories

In this paper, we report how graph theory can be used to analyze an ensemble of independent molecular trajectories, which can react during the simulation time-length, and obtain structural and kinetic information. This method is totally general and here is applied to the prototypical case of gas phase fragmentation of protonated cyclo-di-glycine. This methodology allows us to analyze the whole set of trajectories in an automatic computer-based way without the need of visual inspection but by getting all the needed information. In particular, we not only determine the appearance of different products and intermediates but also characterize the corresponding kinetics. The use of colored graph and canonical labeling allows for the correct characterization of the chemical species involved. In the present case, the simulations consist of an ensemble of unimolecular fragmentation trajectories at constant energy such that from the rate constants at different energies, the threshold energy can also be obtained for both global and specific pathways. This approach allows for the characterization of ion-molecule complexes, likely through a roaming mechanism, by properly taking into account the elusive nature of such species. Finally, it is possible to directly obtain the theoretical mass spectrum of the fragmenting species if the reacting system is an ion as in the specific example.

Current Challenges and Recent Developments in Mass Spectrometry-Based Metabolomics

High-resolution mass spectrometry (MS) has advanced the study of metabolism in living systems by allowing many metabolites to be measured in a single experiment. Although improvements in mass detector sensitivity have facilitated the detection of greater numbers of analytes, compound identification strategies, feature reduction software, and data sharing have not kept up with the influx of MS data. Here, we discuss the ongoing challenges with MS-based metabolomics, including de novo metabolite identification from mass spectra, differentiation of metabolites from environmental contamination, chromatographic separation of isomers, and incomplete MS databases. Because of their popularity and sensitive detection of small molecules, this review focuses on the challenges of liquid chromatography-mass spectrometry-based methods. We then highlight important instrumentational, experimental, and computational tools that have been created to address these challenges and how they have enabled the advancement of metabolomics research.

From QCEIMS to QCxMS: A Tool to Routinely Calculate CID Mass Spectra Using Molecular Dynamics

Mass spectrometry (MS) is a powerful tool in chemical research and substance identification. For the computational modeling of electron ionization MS, we have developed the quantum-chemical electron ionization mass spectra (QCEIMS) program. Here, we present an extension of QCEIMS to calculate collision-induced dissociation (CID) spectra. The more general applicability is accounted for by the new name QCxMS, where "x" refers to EI or CID. To this end, fragmentation and rearrangement reactions are computed "on-the-fly" in Born-Oppenheimer molecular dynamics (MD) simulations with the semiempirical GFN2-xTB Hamiltonian, which provides an efficient quantum mechanical description of all elements up to Z = 86 (Rn). Through the explicit modeling of multicollision processes between precursor ions and neutral gas atoms as well as temperature-induced decomposition reactions, QCxMS provides detailed insight into the collision kinetics and fragmentation pathways. In combination with the CREST program to determine the preferential protonation sites, QCxMS becomes the first standalone MD-based program that can predict mass spectra based solely on molecular structures as input. We demonstrate this for six organic molecules with masses ranging from 159 to 296 Da, for which QCxMS yields CID spectra in reasonable agreement with experiments.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Unimolecular Fragmentation Properties of Thermometer Ions from Chemical Dynamics Simulations

Thermometer ions are widely used to calibrate the internal energy of the ions produced by electrospray ionization in mass spectrometry. Typically, benzylpyridinium ions with different substituents are used. More recently, benzhydrylpyridinium ions were proposed for their lower bond dissociation energies. Direct dynamics simulations using M06-2X/6-31G(d), DFTB, and PM6-D3 are performed to characterize the activation energies of two representative systems: para-methylbenzylpyridinium ion (p-Me-BnPy⁺) and methyl,methylbenzhydrylpyridinium ion (Me,Me-BhPy⁺). Simulation results are used to calculate rate constants for the two systems. These rate constants and their uncertainties are used to find the Arrhenius activation energies and RRK fitted threshold energies which give reasonable agreement with calculated bond dissociation energies at the same level of theory. There is only one fragmentation mechanism observed for both systems, which involves C-N bond dissociation via a loose transition state, to generate either benzylium or benzhydrylium ion and a neutral pyridine molecule. For p-Me-BnPy⁺ using DFTB and PM6-D3 the formation of tropylium ion, from rearrangement of benzylium ion, was observed but only at higher excitation energies and for longer simulation times. These observations suggest that there is no competition between reaction pathways that could affect the reliability of internal energy calibrations. Finally, we suggest using DFTB with a modified-Arrhenius model in future studies.

Modeling the Effects of O-Sulfonation on the CID of Serine

We present the results of direct dynamics simulations and DFT calculations aimed at elucidating the effect of O-sulfonation on the collision-induced dissociation for serine. Toward this end, direct dynamics simulations of both serine and sulfoserine were performed at multiple collision energies and theoretical mass spectra obtained. Comparisons to experimental results are favorable for both systems. Peaks related to the sulfo group are identified and the reaction dynamics explored. In particular, three significant peaks (m/z 106, 88, and 81) seen in the theoretical mass spectrum directly related to the sulfo group are analyzed as well as major peaks shared by both systems. Our analysis shows that the m/z 106 peaks result from intramolecular rearrangements, intermolecular proton transfer among complexes composed of initial fragmentation products, and at high energy side-chain fragmentation. The m/z 88 peak was found to contain multiple constitutional isomers, including a previously unconsidered, low energy structure. It was also observed that the RM1 semiempirical method was not able to obtain all of the major peaks seen in experimens for sulfoserine. In contrast, PM6 did obtain all major experimental peaks.

Collisional dynamics simulations revealing fragmentation properties of Zn(ii)-bound poly-peptide

Collisional simulations show how peptide fragmentation is modified by the presence of Zn(ii).