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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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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. |
format | Online Article Text |
id | pubmed-4857427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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