title: Ontologies in medicinal chemistry: current status and future challenges.
abstract: Recent years have seen a dramatic increase in the amount and availability of data in the diverse areas of medicinal chemistry, making it possible to achieve significant advances in fields such as the design, synthesis and biological evaluation of compounds. However, with this data explosion, the storage, management and analysis of available data to extract relevant information has become even a more complex task that offers challenging research issues to Artificial Intelligence (AI) scientists. Ontologies have emerged in AI as a key tool to formally represent and semantically organize aspects of the real world. Beyond glossaries or thesauri, ontologies facilitate communication between experts and allow the application of computational techniques to extract useful information from available data. In medicinal chemistry, multiple ontologies have been developed during the last years which contain knowledge about chemical compounds and processes of synthesis of pharmaceutical products. This article reviews the principal standards and ontologies in medicinal chemistry, analyzes their main applications and suggests future directions.
authors.affiliation: Artificial Intelligence Department, Computer Science Faculty, Polytechnic University of Madrid, 28660 Boadilla del Monte, Madrid, Spain.
authors.forename: Asunción
authors.initials: A
authors.lastname: Gómez-Pérez
authors.forename: Marcos
authors.initials: M
authors.lastname: Martínez-Romero
authors.forename: Alejandro
authors.initials: A
authors.lastname: Rodríguez-González
authors.forename: Guillermo
authors.initials: G
authors.lastname: Vázquez
authors.forename: José M
authors.initials: JM
authors.lastname: Vázquez-Naya
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000639:trends; D006801:Humans; D008490:Medical Informatics / Q000639:trends; D018875:Vocabulary, Controlled