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Interactive visual analysis of drug-target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing

期刊

BRIEFINGS IN BIOINFORMATICS
卷 21, 期 1, 页码 211-220

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bby119

关键词

network visualization; drug-target interactions; drug mode-of-action; drug repurposing; precision oncology

资金

  1. European Union's Horizon 2020 Research and Innovation Program 2014-2020 [634143]
  2. Cancer Society of Finland
  3. Sigrid Juselius Foundation
  4. Academy of Finland [277293, 292611, 295504, 310507, 313267]
  5. Academy of Finland (AKA) [277293] Funding Source: Academy of Finland (AKA)
  6. Cancer Foundation Finland sr [160061] Funding Source: researchfish

向作者/读者索取更多资源

Knowledge of the full target space of drugs (or drug-like compounds) provides important insights into the potential therapeutic use of the agents to modulate or avoid their various on- and off-targets in drug discovery and precision medicine. However, there is a lack of consolidated databases and associated data exploration tools that allow for systematic profiling of drug target-binding potencies of both approved and investigational agents using a network-centric approach. We recently initiated a community-driven platform, Drug Target Commons (DTC), which is an open-data crowdsourcing platform designed to improve the management, reproducibility and extended use of compound-target bioactivity data for drug discovery and repurposing, as well as target identification applications. In this work, we demonstrate an integrated use of the rich bioactivity data from DTC and related drug databases using Drug Target Profiler (DTP), an open-source software and web tool for interactive exploration of drug-target interaction networks. DTP was designed for network-centric modeling of mode-of-action of multi-targeting anticancer compounds, especially for precision oncology applications. DTP enables users to construct an interaction network based on integrated bioactivity data across selected chemical compounds and their protein targets, further customizable using various visualization and filtering options, as well as cross-links to several drug and protein databases to provide comprehensive information of the network nodes and interactions. We demonstrate here the operation of the DTP tool and its unique features by several use cases related to both drug discovery and drug repurposing applications, using examples of anticancer drugs with shared target profiles.

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