title: Drug interaction ontology (DIO) for inferences of possible drug-drug interactions.
abstract: Drug Interaction Ontology (DIO) was developed for formal representation of pharmacological knowledge. It provides a fundamental framework for accumulation of reusable knowledge components in molecular pharmacology. Ontology was employed and implemented as a relational model. Some features include: 1) Drug-biomolecule interaction was assumed as a primitive knowledge element. 2) Symbolic representation was developed for drug-biomolecule interaction. Consequences of two conjugated units of interaction were defined by using symbols. These are applied for query development for identification of possible drug-drug interaction. 3) The triadic relationship model was developed as a ground model for bio-logical interactions and/or function, including semantic ones. One application of DIO is to support hypothesis generation of drug interaction by providing new hypotheses from a structured database storing literature information on known drug-biomolecule interactions. A knowledge base using DIO that contains information beginning with anti-cancer drugs is now under development. Detection of possible drug interaction was tested and its capacity to lead clinically known ones was confirmed. The system generated theoretically possible drug-drug interactions, which implies potential usefulness of new drugs to be tested before actual clinical application. In this paper, sorivudine and 5-fluorouracil mediated by dihydropyrimidine dehydrogenase are presented.
authors.affiliation: Bioinformatics Group, Genomic Sciences Center, RIKEN Institute of Physical and Chemical Research, E209, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa 230-0045, Japan.
authors.forename: Sumi
authors.initials: S
authors.lastname: Yoshikawa
authors.forename: Kenji
authors.initials: K
authors.lastname: Satou
authors.forename: Akihiko
authors.initials: A
authors.lastname: Konagaya
mesh_terms: D001086:Arabinofuranosyluracil / Q000031:analogs & derivatives* / Q000494:pharmacology; D001185:Artificial Intelligence; D019295:Computational Biology; D042943:Dihydrouracil Dehydrogenase (NADP) / Q000494:pharmacology; D004347:Drug Interactions; D005472:Fluorouracil / Q000494:pharmacology; D006801:Humans; D018875:Vocabulary, Controlled
chemical_list: D001086:Arabinofuranosyluracil; C031368:sorivudine; D042943:Dihydrouracil Dehydrogenase (NADP); D005472:Fluorouracil