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Systematic synergy modeling: understanding drug synergy from a systems biology perspective
Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose–response data which are quite resource-demanding. In addition, t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4574089/ https://www.ncbi.nlm.nih.gov/pubmed/26377814 http://dx.doi.org/10.1186/s12918-015-0202-y |
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author | Chen, Di Liu, Xi Yang, Yiping Yang, Hongjun Lu, Peng |
author_facet | Chen, Di Liu, Xi Yang, Yiping Yang, Hongjun Lu, Peng |
author_sort | Chen, Di |
collection | PubMed |
description | Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose–response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and “omic”-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations. |
format | Online Article Text |
id | pubmed-4574089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45740892015-09-19 Systematic synergy modeling: understanding drug synergy from a systems biology perspective Chen, Di Liu, Xi Yang, Yiping Yang, Hongjun Lu, Peng BMC Syst Biol Review Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose–response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and “omic”-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations. BioMed Central 2015-09-16 /pmc/articles/PMC4574089/ /pubmed/26377814 http://dx.doi.org/10.1186/s12918-015-0202-y Text en © Chen et al. 2015 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 | Review Chen, Di Liu, Xi Yang, Yiping Yang, Hongjun Lu, Peng Systematic synergy modeling: understanding drug synergy from a systems biology perspective |
title | Systematic synergy modeling: understanding drug synergy from a systems biology perspective |
title_full | Systematic synergy modeling: understanding drug synergy from a systems biology perspective |
title_fullStr | Systematic synergy modeling: understanding drug synergy from a systems biology perspective |
title_full_unstemmed | Systematic synergy modeling: understanding drug synergy from a systems biology perspective |
title_short | Systematic synergy modeling: understanding drug synergy from a systems biology perspective |
title_sort | systematic synergy modeling: understanding drug synergy from a systems biology perspective |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4574089/ https://www.ncbi.nlm.nih.gov/pubmed/26377814 http://dx.doi.org/10.1186/s12918-015-0202-y |
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