An Application of Computational Drug Repurposing Based on Transcriptomic Signatures
Drug repurposing is a methodology where already existing drugs are tested against diseases outside their initial usage, in order to reduce the high cost and long periods of new drug development. In silico drug repurposing further speeds up the process, by testing a large number of drugs against the biological signatures of known diseases. In this chapter, we present a step-by-step methodology of a transcriptomics-based computational drug repurposing pipeline providing a comprehensive guide to the whole procedure, from proper dataset selection to short list derivation of repurposed drugs which might act as inhibitors against the studied disease. The presented pipeline contains the selection and curation of proper transcriptomics datasets, statistical analysis of the datasets in order to extract the top over- and under-expressed gene identifiers, appropriate identifier conversion, drug repurposing analysis, repurposed drugs filtering, cross-tool screening, drug-list re-ranking, and results’ validation.
Key wordsDrug repurposing Drug repositioning Transcriptomics Computational pipeline Gene expression RNA-Seq Microarrays
George M. Spyrou holds the Bioinformatics ERA Chair Position funded by the European Commission Research Executive Agency (REA) Grant BIORISE (Num. 669026), under the Spreading Excellence, Widening Participation, Science with and for Society Framework.
Evangelos S. Karatzas is a PHD student in the National and Kapodistrian University of Athens. His doctoral thesis is being funded by the IKY (State Scholarships Foundation) scholarship, funded by the Action “Strengthening Human Resources, Education and Lifelong Learning,” 2014–2020, co-funded by the European Social Fund (ESF) and the Greek State.
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