High Performance Collision Cross Section (HPCCS) : utilização de técnicas de HPC para aceleração do cálculo da seção de choque transversal

Orientador: Guido Costa Souza de AraújoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A técnica de Mobilidade Iônica junto com a Espectrometria de Massa (IM-MS) tem sido utilizada desde 2003 por laboratórios de pesquisa e análises, quando foram introduzidos os primeiros equipamentos comerciais. Ela é usada como uma ferramenta de separação molecular, técnica cromatográfica e também para obter informação estrutural de íons moleculares. A interpretação dos dados obtidos ainda é um desafio, dependendo dos cálculos da seção de choque transversal (CCS) contra um gás de arraste. Este trabalho, apresenta um novo software, \textit{High Performance Collision Cross Section} - HPCCS, que, baseado no método de trajetória, realiza os cálculos de CCS utilizando técnicas de \textit{High Performance Computing} como paralelização, vetorização e otimização. Agora é possível calcular o CCS de maneira eficiente, desde para pequenas moléculas orgânicas até proteínas complexas com um número maior de átomos. Os resultados mostraram que, comparados com o software usado atualmente (MOBCAL), houve um ganho em média de 78 vezes em um nó de um cluster com 24 cores e 48 threads, utilizando Simultaneous Multithreading (SMT)Abstract: Ion Mobility coupled to Mass Spectrometry technique (IM-MS) have been used since 2003 for research and analysis laboratories, when they were commercially introduced. It has been used as a tool for molecular separation, chromatography technique, and to obtain structural information for molecular ions. The interpretation of the resulting data is still a challenge, depending on collision cross section (CCS) calculation against a buffer gas. This work, presents a new software, High Performance Collision Cross Section - HPCCS, which is based on the trajectory method, using High Performance Computing techniques like parallelization, vectorization and optimization. By using HPCCS now calculate the CCS efficiently, from small organic molecules to protein complexes with a larger number of atoms. The results presented in this work when comparing to the state of the art software (MOBCAL), show an average speedup of 78 times on a cluster node with 24 cores and 48 threads, with Simultaneous Multithreading (SMT)MestradoCiência da ComputaçãoMestre em Ciência da Computação2012/24750-6, 2013/08293-7, 2016/04963-6FAPES

A parallelized molecular collision cross section package with optimized accuracy and efficiency

Ion mobility-based separation prior to mass spectrometry has become an invaluable tool in the structural elucidation of gas-phase ions and in the characterization of complex mixtures. Application of ion mobility to structural studies requires an accurate methodology to bridge theoretical modelling of chemical structure with experimental determination of an ion's collision cross section (CCS). Herein, we present a refined methodology for calculating ion CCS using parallel computing architectures that makes use of atom specific parameters, which we have called MobCal-MPI. Tuning of ion-nitrogen van der Waals potentials on a diverse calibration set of 162 molecules returned a RMSE of 2.60% in CCS calculations of molecules containing the elements C, H, O, N, F, P, S, Cl, Br, and I. External validation of the ion-nitrogen potential was performed on an additional 50 compounds not present in the validation set, returning a RMSE of 2.31% for the CCSs of these compounds. Owing to the use of parameters from the MMFF94 forcefield, the calibration of the van der Waals potential can be extended to additional atoms defined in the MMFF94 forcefield (i.e., Li, Na, K, Si, Mg, Ca, Fe, Cu, Zn). We expect that the work presented here will serve as a foundation for facile determination of molecular CCSs, as MobCal-MPI boasts up to 64-fold speedups over traditional calculation packages.The authors would like to acknowledge the financial support provided by the Natural Sciences and Engineering Research Council (NSERC) of Canada

CCSP 2.0: An Open-Source Jupyter Tool for the Prediction of Ion Mobility Collison Cross Sections in Metabolomics

Tandem mass spectrometric methods revolutionized the chemical identification landscape, allowing serums and molecules to be separated in two or more dimensions. Ion Mobility Mass Spectrometry workflows combined with liquid or gas chromatographic separation have continued to progress chemical identification and further increase the amount and confidence of these identities. Such advancements have also given birth to a new molecular descriptor: the Collision Cross Section, sparking heavy interest in the analytical-computational chemistry to compile these values for known molecules. The main shortcoming has been predicting the CCS value for new molecules such as Poly-Fluorinated Alkyl Sub-stances. Preliminary prediction software has revealed that predicting CCS values for this molecular class is possible, but it can prove temporally, computationally, and financially expensive between different licenses and genetic algorithm. This work combines open-source Python modules (NumPy, Mordred, Pandas, etc.) to construct an alternative workflow that is completely free and capable of running on a mid-specification laptop within a half hour. Using the M-H and combined M+H and M-H datasets taken from the McClean CCS Compendium, median prediction errors of 2.07% and 1.84%, respectively, were found using Support Vector Regression within 5 minutes on a mid-spec laptop, satisfying the 2.50% benchmark. This overall success illustrates the power and versatility of this workflow to produce low errors with datasets as large as 1300+ molecules and as few as 37. This script can be distributed on file-sharing sites like GitHub where other users may customize the free source code to fit their experimental needs.Undergraduat

Prediction of Retention Time and Collision Cross Section (CCSH plus , CCSH-, and CCSNa plus ) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Ultra-high performance liquid chromatography coupled to ion mobility separation and high-resolution mass spectrometry instruments have proven very valuable for screening of emerging contaminants in the aquatic environment. However, when applying suspect or nontarget approaches (i.e., when no reference standards are available), there is no information on retention time (RT) and collision cross-section (CCS) values to facilitate identification. In silico prediction tools of RT and CCS can therefore be of great utility to decrease the number of candidates to investigate. In this work, Multiple Adaptive Regression Splines (MARS) were evaluated for the prediction of both RT and CCS. MARS prediction models were developed and validated using a database of 477 protonated molecules, 169 deprotonated molecules, and 249 sodium adducts. Multivariate and univariate models were evaluated showing a better fit for univariate models to the experimental data. The RT model (R2 = 0.855) showed a deviation between predicted and experimental data of +/- 2.32 min (95% confidence intervals). The deviation observed for CCS data of protonated molecules using the CCSH model (R2 = 0.966) was +/- 4.05% with 95% confidence intervals. The CCSH model was also tested for the prediction of deprotonated molecules, resulting in deviations below +/- 5.86% for the 95% of the cases. Finally, a third model was developed for sodium adducts (CCSNa, R2 = 0.954) with deviation below +/- 5.25% for 95% of the cases. The developed models have been incorporated in an open-access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data

Prediction of Retention Time and Collision Cross Section (CCSH+, CCSH–, and CCSNa+) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Ultra-high performance liquid chromatography coupled to ion mobility separation and high-resolution mass spectrometry instruments have proven very valuable for screening of emerging contaminants in the aquatic environment. However, when applying suspect or nontarget approaches (i.e., when no reference standards are available), there is no information on retention time (RT) and collision cross-section (CCS) values to facilitate identification. In silico prediction tools of RT and CCS can therefore be of great utility to decrease the number of candidates to investigate. In this work, Multiple Adaptive Regression Splines (MARS) were evaluated for the prediction of both RT and CCS. MARS prediction models were developed and validated using a database of 477 protonated molecules, 169 deprotonated molecules, and 249 sodium adducts. Multivariate and univariate models were evaluated showing a better fit for univariate models to the experimental data. The RT model (R2 = 0.855) showed a deviation between predicted and experimental data of ±2.32 min (95% confidence intervals). The deviation observed for CCS data of protonated molecules using the CCSH model (R2 = 0.966) was ±4.05% with 95% confidence intervals. The CCSH model was also tested for the prediction of deprotonated molecules, resulting in deviations below ±5.86% for the 95% of the cases. Finally, a third model was developed for sodium adducts (CCSNa, R2 = 0.954) with deviation below ±5.25% for 95% of the cases. The developed models have been incorporated in an open-access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data.Funding for open access charge: CRUE-Universitat Jaume

Plate-height model of ion mobility-mass spectrometry: Part 2-Peak-to-peak resolution and peak capacity

In a previous work, we explored zone broadening and the achievable plate numbers in linear drift tube ion mobility-mass spectrometry through developing a plate-height model [1]. On the basis of these findings, the present theoretical study extends the model by exploring peak-to-peak resolution and peak capacity in ion mobility separations. The first part provides a critical overview of chromatography-influenced resolution equations, including refinement of existing formulae. Furthermore, we present exact resolution equations for drift tube ion mobility spectrometry based on first principles. Upon implementing simple modifications, these exact formulae could be readily extended to traveling wave ion mobility separations and to cases when ion mobility spectrometry is coupled to mass spectrometry. The second part focuses on peak capacity. The well-known assumptions of constant plate number and constant peak width form the basis of existing approximate solutions. To overcome their limitations, an exact peak capacity equation is derived for drift tube ion mobility spectrometry. This exact solution is rooted in a suitable physical model of peak broadening, accounting for the finite injection pulse and subsequent diffusional spreading. By borrowing concepts from the theoretical toolbox of chromatography, we believe that the present study will help in integrating ion mobility spectrometry into the unified language of separation science

The size-mobility relationship of ions, aerosols, and other charged particle matter

Electrical Mobility is arguably the property upon which some of the most successful classification criteria are based for aerosol particles and ions in the gas phase. Once the value of mobility is empirically obtained, it can be related to a geometrical descriptor of the charged entity through a size-mobility relationship. Given the multiscale range of sizes in the aerosol field, approaches that can provide accurate transformations from mobility to size are not straightforward, and many times rely on experimentally derived parameters. The most well-known size-mobility analytical expression covering the whole Knudsen range for spherical particles is the semi-empirical Stokes-Millikan correlation. This expression matches Stokes' drag friction coefficient in the continuum regime and the friction factor for a predominantly diffuse reemission of the gas molecule in the free molecular regime, as theorized by Epstein, with empirical slip coefficients chosen to agree with Millikan's oil drop experiments. Despite its success, the Stokes-Millikan correlation has its shortcomings. For example, it needs to be modified to predict the mobility of non-spherical entities and needs correction terms when potential interactions or reduced mass effects are non-negligible. The Stokes-Millikan asymptotic behavior also fails to predict the gradual transition from diffuse to specular reemission behavior that is observed for increasingly smaller ions within the free molecular regime. Here we make an attempt at providing a comprehensive account of the existing mass-mobility relations in the continuum, transition and free molecular regimes for both spherical and non-spherical particles. Epstein's diffuse interaction is critically explored experimentally and numerically for different gases in the free molecular regime with the observation that, as the size of the particle increases, a progression from specular to diffuse reemission occurs for all gases studied. The rate at which this variation happens seems to differ from gas to gas and to be related to the conditions for which diffuse reemission effects stem from a combination of scattering and potential interactions

The Future of High Energy Physics Software and Computing

Software and Computing (S&C) are essential to all High Energy Physics (HEP) experiments and many theoretical studies. The size and complexity of S&C are now commensurate with that of experimental instruments, playing a critical role in experimental design, data acquisition/instrumental control, reconstruction, and analysis. Furthermore, S&C often plays a leading role in driving the precision of theoretical calculations and simulations. Within this central role in HEP, S&C has been immensely successful over the last decade. This report looks forward to the next decade and beyond, in the context of the 2021 Particle Physics Community Planning Exercise ("Snowmass") organized by the Division of Particles and Fields (DPF) of the American Physical Society.Comment: Computational Frontier Report Contribution to Snowmass 2021; 41 pages, 1 figure. v2: missing ref and added missing topical group conveners. v3: fixed typo

Structure-diagnostic ion molecule reactions with environmental pollutants studied by theory and experiment

Atmospheric pressure chemical ionization (APCI) is widely used as a soft ionization technique for mass spectrometry. The APCI source acts not only as an ionization source, but also a reaction chamber for ion-molecule reactions. In this study, we investigated ion-molecule reactions between oxygen and two groups of environmental pollutants that are selective towards toxic isomers. The compounds of interest were tricresyl phosphates (TCPs) and tetrachlorodibenzo-p-dioxins (TCDDs). We propose the mechanisms of the ion molecule reactions of TCPs and TCDDs and provide support through computational and experimental analysis using density functional theory (DFT) and cyclic ion mobility-mass spectrometry (cIM-MS), respectively. Ortho-substituted isomers of TCPs and their toxic metabolites (e.g., CBDP: cresyl saligenin phosphate) can cause neurotoxic effects in humans. When TCP is introduced to an atmospheric pressure chemical ionization (APCI) source using gas chromatography (GC), abundant radical cations M˙⁺ are formed by charge exchange. The mass spectrum of an ortho-substituted isomer displays two intense peaks that are absent in the spectra of non-ortho-substituted isomers, leading us to propose a structure-diagnostic ion-molecule reaction between ions M˙⁺ and ozone. The mechanism proposed in this thesis consists of a multi-step reaction starting with the rearrangement of the molecular ion to a distonic isomer followed by an oxidation step and then, decomposition into [CBDP-H]⁺. This proposal is consistent with the results obtained from a series of isotopically-labelled analogues. Cyclic ion mobility experiments with a triorthocresyl phosphate standard, reveals the presence of at least two hydrogen shift isomers of the product ion [CBDP-H]⁺ that are connected by a low-lying energy barrier. The selectivity of the ion-molecule reaction towards the ortho-substituted cresyl groups in TCP structures provides us with an identification tool that differentiates potentially toxic and non-toxic tri-aryl phosphate esters present in complex mixtures of isomers that are produced in large volume by industry. TCDDs are infamous for their toxicity and persistence in the environment after being generated from the combustion of polychlorinated compounds. The analysis of (mixed) halogenated dibenzo-p-dioxin isomers is challenging due to the limitations of traditional separation techniques and the paucity of authentic standards. Hard ionization techniques, including EI, are not informative due to a lack of isomer selective fragmentation. However, when APCI is used in negative mode, TCDD isomers undergo isomer selective bond cleavages. Previous experimental studies have reported on two selective ion-molecule reactions between TCDDs and O₂. First, the oxidation reaction resulting in [M-Cl+O]⁻ ions, and second, the ether cleavage reaction resulting in a radical anion and a neutral product. In this thesis, mechanisms are proposed for both oxidation and ether cleavage reactions using Density Functional Theory (DFT) calculations. We also calculated theoretical collision cross section (CCS) values for the ether cleavage products using MobCal-MPI to support further studies on separating their isomeric structures using cyclic-ion mobility. These mechanisms will guide the eventual development of experimental methods that can differentiate between (potentially) toxic and non-toxic mixed halogenated dibenzo-p-dioxins