Vertaisarvioitu katsausartikkeli tieteellisessä aikakauslehdessä (A2)
Interactive visual analysis of drug-target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing
Julkaisun tekijät: Tanoli Ziaurrehman, Alam Zaid, Ianevski Aleksandr, Wennerberg Krister, Vähä-Koskela Markus, Aittokallio Tero
Kustantaja: OXFORD UNIV PRESS
Julkaisuvuosi: 2020
Journal: Briefings in Bioinformatics
Tietokannassa oleva lehden nimi: Briefings in bioinformatics
Lehden akronyymi: Brief Bioinform
Volyymi: 21
Julkaisunumero: 1
Aloitussivu: 211
Lopetussivun numero: 220
Sivujen määrä: 10
ISSN: 1467-5463
eISSN: 1477-4054
DOI: http://dx.doi.org/10.1093/bib/bby119
Verkko-osoite: https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bby119/5232987
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/39175522
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. DTP is freely accessible at http://drugtargetprofiler.fimm.fi/.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
