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DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing

BACKGROUND: The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based...

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Autores principales: Issa, Naiem T., Kruger, Jordan, Wathieu, Henri, Raja, Rajarajan, Byers, Stephen W., Dakshanamurthy, Sivanesan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4857427/
https://www.ncbi.nlm.nih.gov/pubmed/27151405
http://dx.doi.org/10.1186/s12859-016-1065-y
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author Issa, Naiem T.
Kruger, Jordan
Wathieu, Henri
Raja, Rajarajan
Byers, Stephen W.
Dakshanamurthy, Sivanesan
author_facet Issa, Naiem T.
Kruger, Jordan
Wathieu, Henri
Raja, Rajarajan
Byers, Stephen W.
Dakshanamurthy, Sivanesan
author_sort Issa, Naiem T.
collection PubMed
description BACKGROUND: The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation. RESULTS: We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, −signaling pathway, −molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity. When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer’s and Parkinson’s diseases. CONCLUSIONS: DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1065-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-48574272016-05-20 DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing Issa, Naiem T. Kruger, Jordan Wathieu, Henri Raja, Rajarajan Byers, Stephen W. Dakshanamurthy, Sivanesan BMC Bioinformatics Research Article BACKGROUND: The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation. RESULTS: We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, −signaling pathway, −molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity. When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer’s and Parkinson’s diseases. CONCLUSIONS: DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1065-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-05-05 /pmc/articles/PMC4857427/ /pubmed/27151405 http://dx.doi.org/10.1186/s12859-016-1065-y Text en © Issa et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Issa, Naiem T.
Kruger, Jordan
Wathieu, Henri
Raja, Rajarajan
Byers, Stephen W.
Dakshanamurthy, Sivanesan
DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
title DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
title_full DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
title_fullStr DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
title_full_unstemmed DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
title_short DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
title_sort druggenex-net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4857427/
https://www.ncbi.nlm.nih.gov/pubmed/27151405
http://dx.doi.org/10.1186/s12859-016-1065-y
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