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Register a new userRapid Prediction of Electron-Ionization Mass Spectrometry using Neural Networks
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When confronted with a substance of unknown identity, researchers often perform mass spectrometry on the sample and compare the observed spectrum to a library of previously-collected spectra to identify the molecule. While popular, this approach will fail to identify molecules that are not in the existing library. In response, we propose to improve the librarys coverage by augmenting it with synthetic spectra that are predicted using machine learning. We contribute a lightweight neural network model that quickly predicts mass spectra for small molecules. Achieving high accuracy predictions requires a novel neural network architecture that is designed to capture typical fragmentation patterns from electron ionization. We analyze the effects of our modeling innovations on library matching performance and compare our models to prior machine learning-based work on spectrum prediction.
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Revelation of chlorine and bromine isotope fractionation of halogenated organic compounds (HOCs) in electron ionization mass spectrometry (EI-MS) is crucial for compound-specific chlorine/bromine isotope analysis (CSIA-Cl/Br) using gas chromatography EI-MS (GC-EI-MS). This study systematically investigated chlorine/bromine isotope fractionation in EI-MS of HOCs including 12 organochlorines and 5 organobromines using GC-double focus magnetic-sector high resolution MS (GC-DFS-HRMS). Chlorine/bromine isotope fractionation behaviors of the HOCs in EI-MS showed varied isotope fractionation patterns and extents depending on compounds. Besides, isotope fractionation patterns and extents varied at different EI energies, demonstrating potential impacts of EI energy on the chlorine/bromine isotope fractionation. Hypotheses of inter-ion and intra-ion isotope fractionations were applied to interpreting the isotope fractionation behaviors. The inter-ion and intra-ion isotope fractionations counteractively contributed to the apparent isotope ratio for a certain dehalogenated product ion. The isotope fractionation mechanisms were tentatively elucidated on basis of the quasi-equilibrium theory. In the light of the findings of this study, isotope ratio evaluation scheme using complete molecular ions and the EI source with sufficient stable EI energies may be helpful to achieve optimal precision and accuracy of CSIA-Cl/Br data. The method and results of this study can help to predict isotope fractionation of HOCs during dehalogenation processes and further to reveal the dehalogenation pathways.
Native electrospray ionization/ion mobility-mass spectrometry (ESI/IM-MS) allows an accurate determination of low-resolution structural features of proteins. Yet, the presence of proton dynamics, observed already by us for DNA in the gas phase, and its impact on protein structural determinants, have not been investigated so far. Here, we address this issue by a multi-step simulation strategy on a pharmacologically relevant peptide, the N-terminal residues of amyloid-beta peptide (Abeta(1-16)). Our calculations reproduce the experimental maximum charge state from ESI-MS and are also in fair agreement with collision cross section (CCS) data measured here by ESI/IM-MS. Although the main structural features are preserved, subtle conformational changes do take place in the first ~0.1 ms of dynamics. In addition, intramolecular proton dynamics processes occur on the ps-timescale in the gas phase as emerging from quantum mechanics/molecular mechanics (QM/MM) simulations at the B3LYP level of theory. We conclude that proton transfer phenomena do occur frequently during fly time in ESI-MS experiments (typically on the ms timescale). However, the structural changes associated with the process do not significantly affect the structural determinants.
Rapid progress in atomic, molecular, and optical (AMO) physics techniques enabled the creation of ultracold samples of molecular species and opened opportunities to explore chemistry in the ultralow temperature regime. In particular, both the external and internal quantum degrees of freedom of the reactant atoms and molecules are controlled, allowing studies that explored the role of the long range potential in ultracold reactions. The kinetics of these reactions have typically been determined using the loss of reactants as proxies. To extend such studies into the short-range, we developed an experimental apparatus that combines the production of quantum-state-selected ultracold KRb molecules with ion mass and kinetic energy spectrometry, and directly observed KRb + KRb reaction intermediates and products [Science, 2019, 366, 1111]. Here, we present the apparatus in detail. For future studies that aim for detecting the quantum states of the reaction products, we demonstrate a photodissociation based scheme to calibrate the ion kinetic energy spectrometer at low energies.
This is a methodological guide to the use of deep neural networks in the processing of double electron-electron resonance (DEER, aka PELDOR) data encountered in structural biology, organic photovoltaics, photosynthesis research, and other domains featuring long-lived radical pairs. DEER spectroscopy uses distance dependence of magnetic dipolar interactions; measuring a single well-defined distance is straightforward, but extracting distance distributions is a hard and mathematically ill-posed problem requiring careful regularisation and background fitting. Neural networks do this exceptionally well, but their robust black box reputation hides the complexity of their design and training - particularly when the training dataset is effectively infinite. The objective of this paper is to give insight into training against infinite databases, to shed some light on the processes inside the neural net, and to provide a practical data processing flowchart for structural biology work.
The diatomic molecule radium monofluoride (RaF) has recently been proposed as a versatile probe for physics beyond the current standard model. Herein, a route towards production of a RaF molecular beam via radium ions is proposed. It takes advantage of the special electronic structure expected for group 2 halides and group 2 hydrides: The electronic ground state of neutral RaF and its monocation differ in occupation of a non-bonding orbital of $sigma$ symmetry. This implies similar equilibrium distances and harmonic vibrational wavenumbers in the two charge states and thus favourable Franck--Condon factors for neutralisation without dissociation in neutralising collisions. According to the calculated ionisation energy of RaF, charge exchange collisions of RaF$^+$ with sodium atoms are almost iso-enthalpic, resulting in large cross-sections for the production of neutral radium monofluoride.
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