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.