Network medicine for disease module identification and drug repurposing with the NeDRex platform

Sepideh Sadegh,James Skelton,Harald H H W Schmidt,Anil Wipat,Gihanna Galindez,David B Blumenthal,Marisol Salgado-Albarrán,Simon Cockell,Cristian Nogales,Elisa Anastasi,Olga Lazareva,Ana I Casas,Keith Flanagan,Tim Kacprowski,Judith Bernett,Jan Baumbach

doi:10.1038/s41467-021-27138-2

Abstract

Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster drug development timelines. However, the data necessary for the identification of disease modules, i.e. pathways and sub-networks describing the mechanisms of complex diseases which contain potential drug targets, are scattered across independent databases. Moreover, existing studies are limited to predictions for specific diseases or non-translational algorithmic approaches. There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. We close this gap with NeDRex, an integrative and interactive platform for network-based drug repurposing and disease module discovery. NeDRex integrates ten different data sources covering genes, drugs, drug targets, disease annotations, and their relationships. NeDRex allows for constructing heterogeneous biological networks, mining them for disease modules, prioritizing drugs targeting disease mechanisms, and statistical validation. We demonstrate the utility of NeDRex in five specific use-cases.

Highlights

Traditional drug discovery faces a severe efficacy crisis
They tend to be located in so-called disease modules, i.e., small subnetworks representing interconnected mechanisms that can be linked to the phenotype[6,7,8]
We find that the ErbB signaling pathway, which is involved in cancer cell growth, proliferation, motility, and survival[25] is associated with the disease module

Summary

Introduction

Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster drug development timelines. There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. We close this gap with NeDRex, an integrative and interactive platform for network-based drug repurposing and disease module discovery. Network-based approaches are attractive, because networks offer a natural representation of complex biological associations and provide a framework for incorporating multiple data types In such networks, nodes can represent drugs, proteins, or diseases, and edges indicate drug-drug similarities, drug-target interactions, gene-disease associations, and gene-gene interactions (e.g., protein-protein interaction (PPI) networks, gene regulatory networks, signaling networks, and metabolic networks)[5]. Potentially repurposable drugs can be identified in silico by carrying out the following three steps: 1. Construct a heterogeneous biological network by integrating data from multiple biomedical databases which are relevant for the given task

Methods

Results

Conclusion