title: Identifying the unknowns by aligning fragmentation trees.
abstract: Mass spectrometry allows sensitive, automated, and high-throughput analysis of small molecules. In principle, tandem mass spectrometry allows us to identify "unknown" small molecules not in any database, but the automated interpretation of such data is in its infancy. Fragmentation trees have recently been introduced for the automated analysis of the fragmentation patterns of small molecules. We present a method for the automated comparison of such fragmentation patterns, based on aligning the compounds' fragmentation trees. We cluster compounds based solely on their fragmentation patterns and show a good agreement with known compound classes. Fragmentation pattern similarities are strongly correlated with the chemical similarity of molecules. We present a tool for searching a database for compounds with fragmentation pattern similar to an unknown sample compound. We apply this tool to metabolites from Icelandic poppy. Our method allows fully automated computational identification of small molecules that cannot be found in any database.
authors.affiliation: Chair for Bioinformatics, Friedrich Schiller University, Jena, Germany.
authors.forename: Florian
authors.initials: F
authors.lastname: Rasche
authors.forename: Kerstin
authors.initials: K
authors.lastname: Scheubert
authors.forename: Franziska
authors.initials: F
authors.lastname: Hufsky
authors.forename: Thomas
authors.initials: T
authors.lastname: Zichner
authors.forename: Marco
authors.initials: M
authors.lastname: Kai
authors.forename: Aleš
authors.initials: A
authors.lastname: Svatoš
authors.forename: Sebastian
authors.initials: S
authors.lastname: Böcker
mesh_terms: D016000:Cluster Analysis; D016208:Databases, Factual; D013058:Mass Spectrometry / Q000379:methods*; D010207:Papaver / Q000737:chemistry; D013223:Statistics as Topic / Q000379:methods*