title: Reaction site mapping of xenobiotic biotransformations.
abstract: Predictive metabolism methods can be used in drug discovery projects to enhance the understanding of structure-metabolism relationships. The present study uses data mining methods to exploit biotransformation data that have been recorded in the MDL Metabolite database. Reacting center fingerprints were derived from a comparison of substrates and their corresponding products listed in the database. This process yields two fingerprint databases: all atoms in all substrates and all reacting centers. The metabolic reaction data are then mined by submitting a new molecule and searching for fingerprint matches to every atom in the new molecule in both databases. An "occurrence ratio" is derived from the fingerprint matches between the submitted compound and the reacting center and substrate fingerprint databases. Normalization of the occurrence ratio within each submitted molecule enables the results of the search to be rank-ordered as a measure of the relative frequency of a reaction occurring at a specific site within the submitted molecule. Predictive performance that would allow this method to be used by drug discovery teams to generate useful hypotheses regarding structure metabolism relationships was observed.
authors.affiliation: Safety Assessment, AstraZeneca Research & Development, 43183 Mölndal, Sweden. scott.boyer@astrazeneca.com
authors.forename: Scott
authors.initials: S
authors.lastname: Boyer
authors.forename: Catrin Hasselgren
authors.initials: CH
authors.lastname: Arnby
authors.forename: Lars
authors.initials: L
authors.lastname: Carlsson
authors.forename: James
authors.initials: J
authors.lastname: Smith
authors.forename: Viktor
authors.initials: V
authors.lastname: Stein
authors.forename: Robert C
authors.initials: RC
authors.lastname: Glen
mesh_terms: D016208:Databases, Factual; D015394:Molecular Structure; D015262:Xenobiotics / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D015262:Xenobiotics