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      NeDRex - an integrative and interactive network medicine platform for drug repurposing

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            Abstract

            Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs, reduced risk, and faster clinical application. The underlying mechanisms of complex diseases are best described by disease modules. These modules represent disease-relevant pathways and contain potential drug targets which can be identified in silico with network-based methods. The data necessary for the identification of disease modules and network-based drug repurposing are scattered across independent databases, moreover, existing studies have been limited to predictions for specific diseases or non-translational algorithmic approaches. Hence, there is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their specific use cases. We close this gap with NeDRex 1 , an integrative and interactive platform for network-based drug repurposing (available at https://nedrex.net). NeDRex integrates different data sources covering genes, proteins, drugs, drug targets, disease annotations, and their relationships, resulting in a network with 350,142 nodes and 14,127,004 edges. NeDRex allows for constructing heterogeneous biological networks and mining them. It provides users with a variety of network-based methods (available via NeDRexApp and the web application NeDRex-Web https://web.nedrex.net/) to derive disease modules associated with diseases under study, prioritize drugs targeting disease mechanisms, and statistical validation. Benefiting from the expert-in-the-loop paradigm, researchers from biomedical sciences can leverage their domain knowledge at different points of the workflow. The approach used in NeDRex is also adapted for COVID-19 drug repurposing and available via the web tool CoVex 2 ( https://exbio.wzw.tum.de/covex/).

            Content

            Author and article information

            Conference
            ScienceOpen
            12 August 2022
            Affiliations
            [1 ] Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany ( https://ror.org/02kkvpp62)
            [2 ] School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom ( https://ror.org/01kj2bm70)
            [3 ] Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany ( https://ror.org/00f7hpc57)
            [4 ] Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany;
            [5 ] Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of Technische Universität Braunschweig and Hannover Medical School, Braunschweig, Germany ( https://ror.org/010nsgg66)
            [6 ] Department of Pharmacology and Personalised Medicine, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands ( https://ror.org/02jz4aj89)
            [7 ] Department of Pharmacology and Personalised Medicine, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands;
            [8 ] Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany ( https://ror.org/00g30e956)
            Author notes
            Author information
            https://orcid.org/0000-0003-4851-8848
            Article
            10.14293/S2199-1006.1.SOR-.PPPY90R8.v1
            a020240c-0297-4e34-aed2-4613f54b02c4

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            RExPO22
            Maastricht, Netherlands
            2-3 September, 2022
            History
            : 12 August 2022
            Product

            ScienceOpen

            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
            Award ID: 777111
            Categories

            The datasets generated during and/or analysed during the current study are available in the repository: https://api.nedrex.net/ , https://nedrex.net , https://web.nedrex.net/
            Bioinformatics & Computational biology
            Drug repurposing,Network medicine,Disease module identification,Data integration,Heterogeneous networks,Network pharmacology,COVID-19 drug candidates

            References

            1. Sadegh Sepideh, Skelton James, Anastasi Elisa, Bernett Judith, Blumenthal David B., Galindez Gihanna, Salgado-Albarrán Marisol, Lazareva Olga, Flanagan Keith, Cockell Simon, Nogales Cristian, Casas Ana I., Schmidt Harald H. H. W., Baumbach Jan, Wipat Anil, Kacprowski Tim. Network medicine for disease module identification and drug repurposing with the NeDRex platform. Nature Communications. Vol. 12(1)2021. Springer Science and Business Media LLC. [Cross Ref]

            2. Sadegh Sepideh, Matschinske Julian, Blumenthal David B., Galindez Gihanna, Kacprowski Tim, List Markus, Nasirigerdeh Reza, Oubounyt Mhaned, Pichlmair Andreas, Rose Tim Daniel, Salgado-Albarrán Marisol, Späth Julian, Stukalov Alexey, Wenke Nina K., Yuan Kevin, Pauling Josch K., Baumbach Jan. Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing. Nature Communications. Vol. 11(1)2020. Springer Science and Business Media LLC. [Cross Ref]

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