On the potential of ion mobility spectrometry coupled to GC pre-separation – A tutorial

Vautz, Wolfgang; Franzke, Joachim; Zampolli, S.; Elmi, I.; Liedtke, Sascha

doi:10.1016/j.aca.2018.02.052

Cited by 71 publications

(33 citation statements)

References 50 publications

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“…This technique not only breaks through the limitations of the ion mobility spectrum, but also greatly expands the performance and application range of the mass spectrometer. Moreover, it can obtain the ion mobility and mass-to-charge ratio parameters of the samples and improve the accuracy of traditional mass spectrometry data; and at the same time as the specificity, the collisional cross-section (CCS) of the ions can be calculated, and the structural states of the samples can be obtained, which thus shows a great advantage in the identification of the unknown compounds (Pirok et al, 2017; Vautz et al, 2018).…”

Section: Esi-ms and Its Applications In Ligand-target Interactionsmentioning

confidence: 99%

Advances in MS Based Strategies for Probing Ligand-Target Interactions: Focus on Soft Ionization Mass Spectrometric Techniques

et al. 2019

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The non-covalent interactions between small drug molecules and disease-related proteins (ligand-target interactions) mediate various pharmacological processes in the treatment of different diseases. The development of the analytical methods to assess those interactions, including binding sites, binding energies, stoichiometry and association-dissociation constants, could assist in clarifying the mechanisms of action, precise treatment of targeted diseases as well as the targeted drug discovery. For the last decades, mass spectrometry (MS) has been recognized as a powerful tool to study the non-covalent interactions of the ligand-target complexes with the characteristics of high sensitivity, high-resolution, and high-throughput. Soft ionization mass spectrometry, especially the electrospray mass spectrometry (ESI-MS) and matrix assisted laser desorption ionization mass spectrometry (MALDI-MS), could achieve the complete transformation of the target analytes into the gas phase, and subsequent detection of the small drug molecules and disease-related protein complexes, and has exerted great advantages for studying the drug ligands-protein targets interactions, even in case of identifying active components as drug ligands from crude extracts of medicinal plants. Despite of other analytical techniques for this purpose, such as the NMR and X-ray crystallography, this review highlights the principles, research hotspots and recent applications of the soft ionization mass spectrometry and its hyphenated techniques, including hydrogen-deuterium exchange mass spectrometry (HDX-MS), chemical cross-linking mass spectrometry (CX-MS), and ion mobility spectrometry mass spectrometry (IMS-MS), in the study of the non-covalent interactions between small drug molecules and disease-related proteins.

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Section: Esi-ms and Its Applications In Ligand-target Interactionsmentioning

confidence: 99%

Advances in MS Based Strategies for Probing Ligand-Target Interactions: Focus on Soft Ionization Mass Spectrometric Techniques

et al. 2019

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“…Ionization is achieved by radiation [38] (α or β from isotopic radioactive sources), UV radiation [39], or corona discharge [40]. The different velocities of the ions will depend on their mass, charge, and characteristic shapes [41]. Based on these variables, IMS can achieve a different selectivity than mass-spectrometry-based methods.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Konieczka

Aliaño-González

Ferreiro-González

et al. 2020

Sensors

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Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches.

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“…23 A drifting gas, usually nitrogen, flows in a direction against the ion current, and thus differentially lowers the velocity of ions depending on their physical characteristics. [24][25] As a result, gas phase ions can be differentiated depending on their travel time in the IMS drifting tube. 23,26 3 | Page Independent IMS units have already been successfully applied in food volatile analysis.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Sauvignon Blanc Aroma and Quality Gradings Based on Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS): Merging Analytical Chemistry with Machine Learning

Zhu¹,

Benkwitz²,

Kilmartin³

2020

Preprint

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<div>In this paper, we report on the application of the static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) instrument in the field of wine aroma analysis and its potential in constructing a prediction model for the quality gradings of wines. The easy-to-operate, cost effective SHS-GC-IMS instrument was innovatively used for a non-targeted search for volatile compounds in Sauvignon Blanc wine, with the identification of volatiles seldom before reported. The wine aroma profile acquired by the instrument was organically and innovatively combined with advanced classification models, inspired by the computer science community, to produce high classification accuracy in terms of wine quality gradings. Useful insights were also extracted by using advanced interpretation methods on complex models to learn the important volatiles correlated with wine quality grading.</div>

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On the potential of ion mobility spectrometry coupled to GC pre-separation – A tutorial

Cited by 71 publications

References 50 publications

Advances in MS Based Strategies for Probing Ligand-Target Interactions: Focus on Soft Ionization Mass Spectrometric Techniques

Advances in MS Based Strategies for Probing Ligand-Target Interactions: Focus on Soft Ionization Mass Spectrometric Techniques

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Assessment of Sauvignon Blanc Aroma and Quality Gradings Based on Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS): Merging Analytical Chemistry with Machine Learning

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