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Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and signal-to-noise ratio for the analyte. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.
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In mass spectroscopy, amines undergo fragmentation to give parent ions with odd molecule weights. This observed mass spectrum follows the nitrogen rule: a molecule with an odd number of nitrogen atoms produces a parent ion with an odd molecular weight. The remaining fragments have an even mass.
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Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
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Mass Spectrometry: Molecular Fragmentation Overview01:20

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The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
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A New Library-Search Algorithm for Mixture Analysis Using DART-MS.

Arun S Moorthy1, Edward Sisco1

  • 1National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States.

Journal of the American Society for Mass Spectrometry
|June 17, 2021
PubMed
Summary
This summary is machine-generated.

A new Inverted Library-Search Algorithm (ILSA) improves the identification of illicit drug mixtures using direct analysis in real time mass spectrometry (DART-MS). This method refines presumptive identifications, aiding forensic analysis of seized substances.

Keywords:
DART-MSalgorithmslibrary searchingmass spectrometryseized drug analysis

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Area of Science:

  • Forensic Chemistry
  • Analytical Chemistry
  • Mass Spectrometry

Background:

  • Forensic analysis of seized drugs requires accurate identification of illicit compounds within mixtures.
  • Direct Analysis in Real Time Mass Spectrometry (DART-MS) is a valuable screening tool for presumptive identification.
  • Enhancing the accuracy of DART-MS for complex mixtures is crucial for forensic investigations.

Purpose of the Study:

  • To introduce and validate a novel library-search algorithm, the Inverted Library-Search Algorithm (ILSA).
  • To improve the presumptive identification of components in seized drug mixtures analyzed by DART-MS.
  • To provide forensic analysts with a more refined tool for mixture analysis.

Main Methods:

  • Development of the Inverted Library-Search Algorithm (ILSA) for multistage spectral searching.
  • Utilizing in-source collision-induced dissociation mass spectra obtained via DART-MS.
  • Searching lowest fragmentation spectra for target peaks (presumed protonated molecules) and scoring potential library matches.

Main Results:

  • Demonstrated proof of concept using model seized drug mixtures (acetyl fentanyl, benzyl fentanyl, amphetamine, methamphetamine).
  • Successful application of ILSA against a small compound library and the NIST DART-MS Forensics Database.
  • ILSA provides refined information on mixture components, enhancing presumptive identifications.

Conclusions:

  • The ILSA significantly enhances presumptive identifications of illicit compounds in drug mixtures analyzed by DART-MS.
  • This new algorithm offers a valuable advancement for forensic laboratories utilizing DART-MS technology.
  • Further research is recommended to expand the method's capabilities and applications.