scholarly journals Advancing Critical Applications of High Resolution Mass Spectrometry for DOM Assessments: Re-Engaging with Mass Spectral Principles, Limitations, and Data Analysis

2020 ◽  
Vol 54 (19) ◽  
pp. 11654-11656
Author(s):  
Juliana D’Andrilli ◽  
Sarah J. Fischer ◽  
Fernando L. Rosario-Ortiz
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
High Resolution ◽  
High Resolution Mass Spectrometry ◽  
Mass Spectral ◽  
High Resolution Mass ◽  
Resolution Mass

scholarly journals Analysis of stable isotope assisted metabolomics data acquired by high resolution mass spectrometry

2017 ◽  
Vol 9 (15) ◽  
pp. 2275-2283 ◽  
Author(s):  
X. Wei ◽  
P. K. Lorkiewicz ◽  
B. Shi ◽  
J. K. Salabei ◽  
B. G. Hill ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
High Resolution ◽  
Stable Isotope ◽  
Mass Spectrometer ◽  
High Resolution Mass Spectrometry ◽  
Metabolomics Data ◽  
High Resolution Mass ◽  
High Resolution Mass Spectrometer ◽  
Resolution Mass

Developed a suite of data analysis algorithms for automatic analysis of SIAM data acquired on a high resolution mass spectrometer.

scholarly journals Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Myriam Guillevic ◽  
Aurore Guillevic ◽  
Martin K. Vollmer ◽  
Paul Schlauri ◽  
Matthias Hill ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
High Resolution ◽  
High Resolution Mass Spectrometry ◽  
Trace Gases ◽  
Trace Gas ◽  
Atmospheric Measurements ◽  
High Resolution Mass ◽  
Atmospheric Trace Gas ◽  
Resolution Mass

Abstract Background Non-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago in the field of water analysis, together with dedicated compound identification tools, but is still very scarce for indoor and atmospheric trace gas measurements, despite the clear need for a better understanding of the atmospheric trace gas composition. For a systematic detection of emerging trace gases in the atmosphere, a new and powerful analytical method is gas chromatography (GC) of preconcentrated samples, followed by electron ionisation, high resolution mass spectrometry (EI-HRMS). In this work, we present data analysis tools to enable automated fragment formula annotation for unknown compounds measured by GC-EI-HRMS. Results Based on co-eluting mass/charge fragments, we developed an innovative data analysis method to reliably reconstruct the chemical formulae of the fragments, using efficient combinatorics and graph theory. The method does not require the presence of the molecular ion, which is absent in $$\sim$$ ∼ 40% of EI spectra. Our method has been trained and validated on >50 halocarbons and hydrocarbons, with 3–20 atoms and molar masses of 30–330 g mol$$^{-1}$$ - 1 , measured with a mass resolution of approx. 3500. For >90% of the compounds, more than 90% of the annotated fragment formulae are correct. Cases of wrong identification can be attributed to the scarcity of detected fragments per compound or the lack of isotopic constraint (no minor isotopocule detected). Conclusions Our method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.

Exploring the Active Compounds of Traditional Mongolian Medicine Agsirga in Intervention of Novel Coronavirus (2019-nCoV) Based on HPLC-Q-Exactive-MS/MS and Molecular Docking Method

2020 ◽  
Author(s):  
Jie Cheng ◽  
Yuchen Tang ◽  
Baoquan Bao ◽  
Ping Zhang
Keyword(s):  
Mass Spectrometry ◽  
Molecular Docking ◽  
High Resolution ◽  
Mass Spectra ◽  
High Resolution Mass Spectrometry ◽  
Structural Formula ◽  
Active Compounds ◽  
High Resolution Mass ◽  
Q Exactive ◽  
Resolution Mass

<p><a></a><a></a><a></a><a><b>Objective</b></a>: To screen all compounds of Agsirga based on the HPLC-Q-Exactive high-resolution mass spectrometry and find potential inhibitors that can respond to 2019-nCoV from active compounds of Agsirga by molecular docking technology.</p> <p><b>Methods</b>: HPLC-Q-Exactive high-resolution mass spectrometry was adopted to identify the complex components of Mongolian medicine Agsirga, and separated by the high-resolution mass spectrometry Q-Exactive detector. Then the Orbitrap detector was used in tandem high-resolution mass spectrometry, and the related molecular and structural formula were found by using the chemsipider database and related literature, combined with precise molecular formulas (errors ≤ 5 × 10<sup>−6</sup>) , retention time, primary mass spectra, and secondary mass spectra information, The fragmentation regularities of mass spectra of these compounds were deduced. Taking ACE2 as the receptor and deduced compounds as the ligand, all of them were pretreated by discover studio, autodock and Chem3D. The molecular docking between the active ingredients and the target protein was studied by using AutoDock molecular docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-2019-nCoV drugs.</p> <p><b>Result</b>: Based on the fragmentation patterns of the reference compounds and consulting literature, a total of 96 major alkaloids and stilbenes were screened and identified in Agsirga by the HPLC-Q-Exactive-MS/MS method. Combining with molecular docking, a conclusion was got that there are potential active substances in Mongolian medicine Agsirga which can block the binding of ACE2 and 2019-nCoV at the molecular level.</p>

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