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F1000Res. 2019 Jun 20;8:908. doi: 10.12688/f1000research.19592.1. eCollection 2019.

Visualization of drug target interactions in the contexts of pathways and networks with ReactomeFIViz.

Author information

1
Knight Cancer Institute, Oregon Health & Science University, Portland, OR, 97239, USA.
2
Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, 97239, USA.
3
Ontario Institute for Cancer Research, Toronto, ON, M5G 0A3, Canada.
4
Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A1, Canada.

Abstract

The precision medicine paradigm is centered on therapies targeted to particular molecular entities that will elicit an anticipated and controlled therapeutic response. However, genetic alterations in the drug targets themselves or in genes whose products interact with the targets can affect how well a drug actually works for an individual patient. To better understand the effects of targeted therapies in patients, we need software tools capable of simultaneously visualizing patient-specific variations and drug targets in their biological context. This context can be provided using pathways, which are process-oriented representations of biological reactions, or biological networks, which represent pathway-spanning interactions among genes, proteins, and other biological entities. To address this need, we have recently enhanced the Reactome Cytoscape app, ReactomeFIViz, to assist researchers in visualizing and modeling drug and target interactions. ReactomeFIViz integrates drug-target interaction information with high quality manually curated pathways and a genome-wide human functional interaction network. Both the pathways and the functional interaction network are provided by Reactome, the most comprehensive open source biological pathway knowledgebase. We describe several examples demonstrating the application of these new features to the visualization of drugs in the contexts of pathways and networks. Complementing previous features in ReactomeFIViz, these new features enable researchers to ask focused questions about targeted therapies, such as drug sensitivity for patients with different mutation profiles, using a pathway or network perspective.

KEYWORDS:

Boolean network; Reactome; biological pathway; constrained fuzzy logic modeling; drug interaction visualization; functional interaction network; systems pharmacology; targeted therapy

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