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The functional therapeutic chemical classification system

Motivation: Drug repositioning is the discovery of new indications for compounds that have already been approved and used in a clinical setting. Recently, some computational approaches have been suggested to unveil new opportunities in a systematic fashion, by taking into consideration gene expressi...

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Detalles Bibliográficos
Autores principales: Croset, Samuel, Overington, John P., Rebholz-Schuhmann, Dietrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3957075/
https://www.ncbi.nlm.nih.gov/pubmed/24177719
http://dx.doi.org/10.1093/bioinformatics/btt628
Descripción
Sumario:Motivation: Drug repositioning is the discovery of new indications for compounds that have already been approved and used in a clinical setting. Recently, some computational approaches have been suggested to unveil new opportunities in a systematic fashion, by taking into consideration gene expression signatures or chemical features for instance. We present here a novel method based on knowledge integration using semantic technologies, to capture the functional role of approved chemical compounds. Results: In order to computationally generate repositioning hypotheses, we used the Web Ontology Language to formally define the semantics of over 20 000 terms with axioms to correctly denote various modes of action (MoA). Based on an integration of public data, we have automatically assigned over a thousand of approved drugs into these MoA categories. The resulting new resource is called the Functional Therapeutic Chemical Classification System and was further evaluated against the content of the traditional Anatomical Therapeutic Chemical Classification System. We illustrate how the new classification can be used to generate drug repurposing hypotheses, using Alzheimers disease as a use-case. Availability: https://www.ebi.ac.uk/chembl/ftc; https://github.com/loopasam/ftc. Contact: croset@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.