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.

Robustness of Threshold Collision-Induced Dissociation Simulations for Bond Dissociation Energies

The threshold collision-induced dissociation (T-CID) method is the workhorse for gas-phase bond dissociation energy (BDE) measurements. However, T-CID does not measure BDEs directly; instead, BDEs are obtained by fitting simulated data to the experimental data. We previously observed several large discrepancies between the computed and experimental BDEs. To analyze the reliability of the experimental values, we previously reported a study of the dissociation rate models in the simulation. Here, we report a study of the collision simulation part, specifically in the L-CID (ligand CID) program. We show that the BDE values are robust even to intentionally introduced mistakes in the simulations, varying in most cases by less than 3 kcal mol-1. The most significant exception is the collisional energy transfer (CET) simulation, which led to deviations larger than 10 kcal mol-1. However, we found that the BDEs obtained with explicitly simulated CET distributions deviated by only 3 kcal mol-1 from those simulated with the original model. Collectively, our results suggest that the T-CID-derived BDE values are robust and are likely to be accurate.

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.

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.

A map of mass spectrometry-based in silico fragmentation prediction and compound identification in metabolomics

Metabolomics, the comprehensive study of the metabolome, and lipidomics-the large-scale study of pathways and networks of cellular lipids-are major driving forces in enabling personalized medicine. Complicated and error-prone data analysis still remains a bottleneck, however, especially for identifying novel metabolites. Comparing experimental mass spectra to curated databases containing reference spectra has been the gold standard for identification of compounds, but constructing such databases is a costly and time-demanding task. Many software applications try to circumvent this process by utilizing cutting-edge advances in computational methods-including quantum chemistry and machine learning-and simulate mass spectra by performing theoretical, so called in silico fragmentations of compounds. Other solutions concentrate directly on experimental spectra and try to identify structural properties by investigating reoccurring patterns and the relationships between them. The considerable progress made in the field allows recent approaches to provide valuable clues to expedite annotation of experimental mass spectra. This review sheds light on individual strengths and weaknesses of these tools, and attempts to evaluate them-especially in view of lipidomics, when considering complex mixtures found in biological samples as well as mass spectrometer inter-instrument variability.

Direct Dynamics Simulations of the Thermal Fragmentation of a Protonated Peptide Containing Arginine

Arginine has significant effects on fragmentation patterns of the protonated peptide due to its high basicity guanidine tail. In this article, thermal dissociation of the singly protonated glycine-arginine dipeptide (GR-H⁺) was investigated by performing direct dynamics simulations at different vibrational temperatures of 2000-3500 K. Fourteen principal fragmentation mechanisms containing side-chain and backbone fragmentation were found and discussed in detail. The mechanism involving partial or complete loss of a guanidino group dominates side-chain fragmentation, while backbone fragmentation mainly involves the three cleavage sites of a1-x1⁺, a2⁺-x0, and b1-y1⁺. Fragmentation patterns for primary dissociation have been compared with experimental results, and the peak that was not identified by the experiment has been assigned by our simulation. Kinetic parameters for GR-H⁺ unimolecular dissociation may be determined by direct dynamics simulations, which are helpful in exploring the complex biomolecules.

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

In this article, a perspective is given of chemical dynamics simulations of collisions of biological ions with surfaces and of collision-induced dissociation (CID) of ions. The simulations provide an atomic-level understanding of the collisions and, overall, are in quite good agreement with experiment. An integral component of ion/surface collisions is energy transfer to the internal degrees of freedom of both the ion and the surface. The simulations reveal how this energy transfer depends on the collision energy, incident angle, biological ion, and surface. With energy transfer to the ion's vibration fragmentation may occur, i.e. surface-induced dissociation (SID), and the simulations discovered a new fragmentation mechanism, called shattering, for which the ion fragments as it collides with the surface. The simulations also provide insight into the atomistic dynamics of soft-landing and reactive-landing of ions on surfaces. The CID simulations compared activation by multiple "soft" collisions, resulting in random excitation, versus high energy single collisions and nonrandom excitation. These two activation methods may result in different fragment ions. Simulations provide fragmentation products in agreement with experiments and, hence, can provide additional information regarding the reaction mechanisms taking place in experiment. Such studies paved the way on using simulations as an independent and predictive tool in increasing fundamental understanding of CID and related processes.

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).

When classical trajectories get to quantum accuracy: II. The scattering of rotationally excited H2 on Pd(111)

The classical trajectory method in a quantum spirit assigns statistical weights to classical paths on the basis of two semiclassical corrections: Gaussian binning and the adiabaticity correction.

When Classical Trajectories Get to Quantum Accuracy: The Scattering of H2 on Pd(111)

When elementary reactive processes occur at such low energies that only a few states of reactants and/or products are available, quantum effects strongly manifest and the standard description of the dynamics within the classical framework fails. We show here, for H₂ scattering on Pd(111), that by pseudoquantizing in the spirit of Bohr the relevant final actions of the system, along with adequately treating the diffraction-mediated trapping of the incoming wave, classical simulations achieve an unprecedented agreement with state-of-the-art quantum dynamics calculations.

Theoretical Study of Barrierless Chemical Reactions Involving Nearly Elastic Rebound: The Case of S(1D) + X2, X = H, D

For some values of the total angular momentum consistent with reaction, the title processes involve nonreactive trajectories proceeding through a single rebound mechanism during which the internal motion of the reagent diatom is nearly unperturbed. When such paths are in a significant amount, the classical reaction probability is found to be markedly lower than the quantum mechanical one. This finding was recently attributed to an unusual quantum effect called diffraction-mediated trapping, and a semiclassical correction was proposed in order to take into account this effect in the classical trajectory method. In the present work, we apply the resulting approach to the calculation of opacity functions as well as total and state-resolved integral cross sections (ICSs) and compare the values obtained with exact quantum ones, most of which are new. As the title reactions proceed through a deep insertion well, mean potential statistical calculations are also presented. Seven values of the collision energy, ranging from 30 to 1127 K, are considered. Two remarkable facts stand out: (i) The corrected classical treatment strongly improves the accuracy of the opacity function as compared to the usual classical treatment. When the entrance transition state is tight, however, those trajectories crossing it with a bending vibrational energy below the zero point energy must be discarded. (ii) The quantum opacity function, particularly its cutoff, is finely reproduced by the statistical approach. Consequently, the total ICS is also very well described by the two previous approximate methods. These, however, do not predict state-resolved ICSs with the same accuracy, proving thereby that (i) one or several genuine quantum effects involved in the dynamics are missed by the corrected classical treatment and (ii) the dynamics are not fully statistical.

A Trajectory-Based Method to Explore Reaction Mechanisms

The tsscds method, recently developed in our group, discovers chemical reaction mechanisms with minimal human intervention. It employs accelerated molecular dynamics, spectral graph theory, statistical rate theory and stochastic simulations to uncover chemical reaction paths and to solve the kinetics at the experimental conditions. In the present review, its application to solve mechanistic/kinetics problems in different research areas will be presented. Examples will be given of reactions involved in photodissociation dynamics, mass spectrometry, combustion chemistry and organometallic catalysis. Some planned improvements will also be described.