17th International Mass Spectrometry Conference :: Prague, 2006
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|Session:||LATE-BREAKING/Drug Discovery and Development|
|Presentation date:||Tue, Aug 29, 2006|
|Presentation time:||09:50 – 11:20|
Margaret Antler1, Mark A. Bayliss1, Vitaly Lashin11 Advanced Chemistry Development, Inc., Toronto, Canada
Correspondence address: Margaret Antler, Advanced Chemistry Development, Inc., 110 Yonge Street, 14th floor, Toronto, ON, M5C 1T4 Canada.
Keywords: Chromatography, Liquid (LC); Data Analysis; Metabolism, Metabolites; Molecular Weight Determination.
Novel aspect: New algorithm that extracts all components from LC/MS datasets using chemometrics and mass spectrometry knowledge.
Chemometric algorithms have been developed for the extraction of chromatographic peaks from LC/MS datasets. It is often recognized that these peak extraction approaches can significantly reduce the processing time for scientists. Historically it has not been possible for software to automatically determine the molecular ion for each eluting peak and be able to reliably determine optimal processing parameters on a per dataset basis hence removing the need for often complex setup and optimization by a user.
Software systems for automated confirmation of expected analytes have been developed by numerous instrument and software vendors using user driven targeted extracted ion chromatograms. These systems assume that if a chromatographic peak is detected for a target mass value then this is consistent with the presence of a required chemical entity. It is estimated that up to 10% of all automated ion confirmations using this approach for nominal mass determination may be incorrect being the result of isotopic contributions from other eluting chromatographic components.
This presentation will describe an algorithm which is designed to extract all chromatographic components in LC/MS datasets, and identify the molecular ion for each component. The software uses a combination of chemometric algorithms and mass spectral ion knowledge. The output from this extensive analysis is a reduced dataset that details the molecular ions present in the dataset, 12C and 13C classifications, adduct ions, multimers and potential fragment ions, which can reduce the amount of manual data review for the analyst. For automated confirmation systems, the number of false positive confirmations is reduced. This presentation will describe the implementation of the algorithm, as well as applications of the software to metabolite identification problems.