Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2006-9-21
pubmed:abstractText
An improved mass defect filter (MDF) method employing both drug and core structure filter templates was applied to the processing of high resolution liquid chromatography/mass spectrometry (LC/MS) data for the detection and structural characterization of oxidative metabolites with mass defects similar to or significantly different from those of the parent drugs. The effectiveness of this approach was investigated using nefazodone as a model compound, which is known to undergo multiple common and uncommon oxidative reactions. Through the selective removal of all ions that fall outside of the preset filter windows, the MDF process facilitated the detection of all 14 nefazodone metabolites presented in human liver microsomes in the MDF-filtered chromatograms. The capability of the MDF approach to remove endogenous interferences from more complex biological matrices was examined by analyzing omeprazole metabolites in human plasma. The unprocessed mass chromatogram showed no distinct indication of metabolite peaks; however, after MDF processing, the metabolite peaks were easily identified in the chromatogram. Compared with precursor ion scan and neutral loss scan techniques, the MDF approach was shown to be more effective for the detection of metabolites in a complex matrix. The comprehensive metabolite detection capability of the MDF approach, together with accurate mass determination, makes high resolution LC/MS a useful tool for the screening and identification of both common and uncommon drug metabolites.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0090-9556
pubmed:author
pubmed:issnType
Print
pubmed:volume
34
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1722-33
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Detection and characterization of metabolites in biological matrices using mass defect filtering of liquid chromatography/high resolution mass spectrometry data.
pubmed:affiliation
Pharmaceutical Candidate Optimization, Bristol-Myers Squibb Pharmaceutical Research Institute, Princeton, NJ, USA.
pubmed:publicationType
Journal Article