Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1016/j.aca.2008.03.060
Titel (primär) The use of MS classifiers and structure generation to assist in the identification of unknowns in effect-directed analysis
Autor Schymanski, E.; Meinert, C.; Meringer, M.; Brack, W.
Quelle Analytica Chimica Acta
Erscheinungsjahr 2008
Department WANA
Band/Volume 615
Heft 2
Seite von 136
Seite bis 147
Sprache englisch
Keywords Effect-directed analysis; Structure generation; Mass spectral classifiers; Confirmation; MODELKEY
Abstract Structure generation and mass spectral classifiers have been incorporated into a new method to gain further information from low-resolution GC-MS spectra and subsequently assist in the identification of toxic compounds isolated using effect-directed fractionation. The method has been developed for the case where little analytical information other than the mass spectrum is available, common, for example, in effect-directed analysis (EDA), where further interpretation of the mass spectra is necessary to gain additional information about unknown peaks in the chromatogram. Structure generation from a molecular formula alone rapidly leads to enormous numbers of structures; hence reduction of these numbers is necessary to focus identification or confirmation efforts. The mass spectral classifiers and structure generation procedure in the program MOLGEN-MS was enhanced by including additional classifier information available from the NIST05 database and incorporation of post-generation ''filtering criteria''. The presented method can reduce the number of possible structures matching a spectrum by several orders of magnitude, creating much more manageable data sets and increasing the chance of identification. Examples are presented to show how the method can be used to provide ''lines of evidence'' for the identity of an unknown compound. This method is an alternative to library search of mass spectra and is especially valuable for unknowns where no clear library match is available.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=1445
Schymanski, E., Meinert, C., Meringer, M., Brack, W. (2008):
The use of MS classifiers and structure generation to assist in the identification of unknowns in effect-directed analysis
Anal. Chim. Acta 615 (2), 136 - 147 10.1016/j.aca.2008.03.060