Karatzas Evangelos, Kolios George, Spyrou George M
Department of Informatics and Telecommunications, University of Athens, Athens, Greece.
Laboratory of Pharmacology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece.
Methods Mol Biol. 2019;1903:149-177. doi: 10.1007/978-1-4939-8955-3_9.
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.
药物重新利用是一种方法，即针对已上市药物在其初始用途之外的疾病进行测试，以降低新药开发的高成本和长周期。计算机辅助药物重新利用通过针对已知疾病的生物学特征测试大量药物，进一步加速了这一过程。在本章中，我们介绍了一种基于转录组学的计算药物重新利用流程的分步方法，为整个过程提供了全面指南，从合适的数据集选择到可能作为所研究疾病抑制剂的重新利用药物的短名单推导。所介绍的流程包括合适转录组学数据集的选择和整理、对数据集进行统计分析以提取最显著上调和下调的基因标识符、适当的标识符转换、药物重新利用分析、重新利用药物筛选、跨工具筛选、药物列表重新排名以及结果验证。
