Short Lecture "Ontology based ethnobotany data management to support natural product-based drug discovery"

For millennia and across cultures, plants have been utilised to treat human diseases. Despite recent efforts to organise this knowledge into databases and ontologies, attempts have so far been either limited to specific types of traditional medicines, or unable to practically support drug discovery tasks. In this work, we describe our work of creating ontologies and controlled vocabularies to describe ethnobotanical data, with the aim to achieve interoperability with chemical, biological, and medical datasets in order to be able to identify entry points for drug discovery. Ethnobotanical data comprises subdomains including species, preparation and usage methods, geo-location of usage, diseases and symptoms, etc. In order to organise ethnobotany data into structured ontologies and to establish links with drug discovery datasets we extracted structured and unstructured data from various sources and organised them into graph-structured knowledge bases using a Linked Data Model. Subsequently, we either leveraged established domain-specific ontologies such as DOID, SYMP, MeSH, Mondo, NCBITaxon, PO, etc., or developed new ontologies where needed. After establishing ontologies for all subdomains, we performed ontology alignment. Our ontologies are based on OWL and are built using Protégé which can be queried using SPARQL. By using the ontological framework described here, we not only gain analytical insights into existing knowledge about traditional medicines but are also able to draw novel inferences that are able to accelerate natural product-based drug discovery based on historical use information of medicinal plants.

Publication History

Article published online:
16 November 2023