MOTIVATION: Biomedical ontologies have proved to be valuable tools for data analysis and data interoperability. Protein-ligand interactions are key players in drug discovery and development; however, existing public ontologies that describe the knowledge space of biomolecular interactions do not cover all aspects relevant to pharmaceutical modelling and simulation. RESULTS: The protein--ligand interaction ontology (PLIO) was developed around three main concepts, namely target, ligand and interaction, and was enriched by adding synonyms, useful annotations and references. The quality of the ontology was assessed based on structural, functional and usability features. Validation of the lexicalized ontology by means of natural language processing (NLP)-based methods showed a satisfactory performance (F-score = 81%). Through integration into our information retrieval environment we can demonstrate that PLIO supports lexical search in PubMed abstracts. The usefulness of PLIO is demonstrated by two use-case scenarios and it is shown that PLIO is able to capture both confirmatory and new knowledge from simulation and empirical studies. AVAILABILITY: The PLIO ontology is made freely available to the public at http://www.scai.fraunhofer.de/bioinformatics/downloads.html.
MOTIVATION: Biomedical ontologies have proved to be valuable tools for data analysis and data interoperability. Protein-ligand interactions are key players in drug discovery and development; however, existing public ontologies that describe the knowledge space of biomolecular interactions do not cover all aspects relevant to pharmaceutical modelling and simulation. RESULTS: The protein--ligand interaction ontology (PLIO) was developed around three main concepts, namely target, ligand and interaction, and was enriched by adding synonyms, useful annotations and references. The quality of the ontology was assessed based on structural, functional and usability features. Validation of the lexicalized ontology by means of natural language processing (NLP)-based methods showed a satisfactory performance (F-score = 81%). Through integration into our information retrieval environment we can demonstrate that PLIO supports lexical search in PubMed abstracts. The usefulness of PLIO is demonstrated by two use-case scenarios and it is shown that PLIO is able to capture both confirmatory and new knowledge from simulation and empirical studies. AVAILABILITY: The PLIO ontology is made freely available to the public at http://www.scai.fraunhofer.de/bioinformatics/downloads.html.
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