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Related Concept Videos

Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...

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A Strategy for Sensitive, Large Scale Quantitative Metabolomics
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A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

An integrated strategy for in vivo metabolite profiling using high-resolution mass spectrometry based data processing

Jian Guo1, Minli Zhang, Charles S Elmore

  • 1DMPK of Infection Innovative Medicine, AstraZeneca Pharmaceuticals, Waltham, MA 02451, USA. jian.guo@astrazeneca.com

Analytica Chimica Acta
|May 18, 2013
PubMed
Summary

Accurate mass-based data processing tools effectively detect unknown drug metabolites in complex biological samples. Combining isotopic pattern recognition and data mining aids in identifying low-level metabolites and elucidating new metabolic pathways.

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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
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07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

Area of Science:

  • Pharmacology
  • Analytical Chemistry
  • Metabolomics

Background:

  • Drug metabolite profiling in complex biological matrices presents challenges in detecting unknown or low-level compounds.
  • Accurate mass measurement is crucial for identifying metabolites with high precision.

Purpose of the Study:

  • To present a generic strategy for metabolite detection using multiple accurate mass-based data processing tools.
  • To evaluate the effectiveness of isotopic pattern recognition and various data mining techniques for drug metabolite identification.

Main Methods:

  • Analysis of rat samples for two model drug candidates, AZD6280 and AZ12488024.
  • Application of isotopic pattern recognition for [(14)C]-AZD6280 metabolite detection.
  • Utilized background subtraction, mass defect filtering (MDF), and MZmine for untargeted data mining of AZ12488024 metabolites.

Main Results:

  • Isotopic pattern recognition effectively detected metabolites of [(14)C]-AZD6280, correlating well with radiochromatograms.
  • 33 metabolites of AZ12488024 were detected using data mining tools, with 16 identified exclusively through these methods.
  • New metabolic pathways, including S-oxidation and thiomethylation on the thiazole ring, were proposed.

Conclusions:

  • Accurate mass-based MDF and metabolomic data mining are complementary tools for detecting low-level metabolites in complex matrices.
  • Parallel or tandem application of multiple data-mining algorithms enables rapid in vivo drug metabolite profiling.