An integrated dataset for in silico drug discovery.
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 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.
Cockell
Simon J
SJ
Bioinformatics Support Unit, Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle-upon-Tyne NE1 7RH, UK
Weile
Jochen
J
Lord
Phillip
P
Wipat
Claire
C
Andriychenko
Dmytro
D
Pocock
Matthew
M
Wilkinson
Darren
D
Young
Malcolm
M
Wipat
Anil
A
D002746:Chlorpromazine / Q000032:analysis; D019295:Computational Biology; D019992:Databases as Topic; D055808:Drug Discovery; D012660:Semantics
D002746:Chlorpromazine