BACKGROUND: One of the most successful approaches to develop new small molecule 
therapeutics has been to start from a validated druggable protein target. 
However, only a small subset of potentially druggable targets has attracted 
significant research and development resources. The Illuminating the Druggable 
Genome (IDG) project develops resources to catalyze the development of likely 
targetable, yet currently understudied prospective drug targets. A central 
component of the IDG program is a comprehensive knowledge resource of the 
druggable genome.
RESULTS: As part of that effort, we have developed a framework to integrate, 
navigate, and analyze drug discovery data based on formalized and standardized 
classifications and annotations of druggable protein targets, the Drug Target 
Ontology (DTO). DTO was constructed by extensive curation and consolidation of 
various resources. DTO classifies the four major drug target protein families, 
GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, 
function, target development level, disease association, tissue expression, 
chemical ligand and substrate characteristics, and target-family specific 
characteristics. The formal ontology was built using a new software tool to 
auto-generate most axioms from a database while supporting manual knowledge 
acquisition. A modular, hierarchical implementation facilitate ontology 
development and maintenance and makes use of various external ontologies, thus 
integrating the DTO into the ecosystem of biomedical ontologies. As a formal 
OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from 
the Library of Integrated Network-based Cellular Signatures (LINCS) program 
illustrates the potential of DTO for contextual data integration and nuanced 
definition of important drug target characteristics. DTO has been implemented in 
the IDG user interface Portal, Pharos and the TIN-X explorer of protein target 
disease relationships.
CONCLUSIONS: DTO was built based on the need for a formal semantic model for 
druggable targets including various related information such as protein, gene, 
protein domain, protein structure, binding site, small molecule drug, mechanism 
of action, protein tissue localization, disease association, and many other 
types of information. DTO will further facilitate the otherwise challenging 
integration and formal linking to biological assays, phenotypes, disease models, 
drug poly-pharmacology, binding kinetics and many other processes, functions and 
qualities that are at the core of drug discovery. The first version of DTO is 
publically available via the website http://drugtargetontology.org/ , Github ( 
http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( 
http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is 
to provide such an integrative framework and to populate the ontology with this 
information as a community resource.