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Welcome to the research blog for the project titled “Semantic motif searching in an Ondex drug discovery network“.

Drug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound. Systematic approaches to this drug repositioning are needed to increase throughput and find candidates more reliably. Here we address this need with an integrated systems biology dataset, developed using the Ondex data integration platform, for the in silico discovery of new drug repositioning candidates. We demonstrate that the information in this dataset allows known repositioning examples to be discovered. We also propose a means of automating the search for new treatment indications of existing compounds.

Motivation: Drug discovery is an expensive industry and many pharmaceutical companies are now seeking cheaper and more practical approaches. Drug repurposing is one of those approaches which can save time and money over novel techniques, allowing smaller companies and groups to get a foothold in the industry. Recent research has developed an integrated network of protein and drug information in the data integration platform Ondex, using a variety of sources. The network allows the discovery of existing indicative drug repurposing on a drug-by-drug approach, which is impractical. A new mechanism known as semantic motifs, which match a particular metadata or semantic structure that may indicate a new drug indication, has been proposed. It is suggested that this mechanism can be generically automated and the results scored by using systems biology approaches.
Results: Three types of semantic motif were defined and then searched for within the dataset using an automated systems biology approach in the Java programming language. The motifs identified were stored to allow for further analyses in Cytoscape, Java and other tools. Network motif analysis was performed by FANMOD, individual motif analyses were performed and compound represen-tation within motifs were all taken into account in an attempt to devise a scoring algorithm for semantic motifs.
Availability and Implementation: The Ondex platform and Ondex-mini repository are freely available on the web at http://www.ondex.org and the dataset used for this analysis is avail-able from http://bsu.ncl.ac.uk/ondex/.