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Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks

Targeting modules or signalings may open a new path to understanding the complex pharmacological mechanisms of reversing disease processes. However, determining how to quantify the structural alteration of these signalings or modules in pharmacological networks poses a great challenge towards realiz...

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Autores principales: Chen, Yin-ying, Yu, Ya-nan, Zhang, Ying-ying, Li, Bing, Liu, Jun, Li, Dong-feng, Wu, Ping, Wang, Jie, Wang, Zhong, Wang, Yong-yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934924/
https://www.ncbi.nlm.nih.gov/pubmed/27383195
http://dx.doi.org/10.1371/journal.pone.0158379
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author Chen, Yin-ying
Yu, Ya-nan
Zhang, Ying-ying
Li, Bing
Liu, Jun
Li, Dong-feng
Wu, Ping
Wang, Jie
Wang, Zhong
Wang, Yong-yan
author_facet Chen, Yin-ying
Yu, Ya-nan
Zhang, Ying-ying
Li, Bing
Liu, Jun
Li, Dong-feng
Wu, Ping
Wang, Jie
Wang, Zhong
Wang, Yong-yan
author_sort Chen, Yin-ying
collection PubMed
description Targeting modules or signalings may open a new path to understanding the complex pharmacological mechanisms of reversing disease processes. However, determining how to quantify the structural alteration of these signalings or modules in pharmacological networks poses a great challenge towards realizing rational drug use in clinical medicine. Here, we explore a novel approach for dynamic comparative and quantitative analysis of the topological structural variation of modules in molecular networks, proposing the concept of allosteric modules (AMs). Based on the ischemic brain of mice, we optimize module distribution in different compound-dependent modular networks by using the minimum entropy criterion and then calculate the variation in similarity values of AMs under various conditions using a novel method of SimiNEF. The diverse pharmacological dynamic stereo-scrolls of AMs with functional gradient alteration, which consist of five types of AMs, may robustly deconstruct modular networks under the same ischemic conditions. The concept of AMs can not only integrate the responsive mechanisms of different compounds based on topological cascading variation but also obtain valuable structural information about disease and pharmacological networks beyond pathway analysis. We thereby provide a new systemic quantitative strategy for rationally determining pharmacological mechanisms of altered modular networks based on topological variation.
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spelling pubmed-49349242016-07-18 Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks Chen, Yin-ying Yu, Ya-nan Zhang, Ying-ying Li, Bing Liu, Jun Li, Dong-feng Wu, Ping Wang, Jie Wang, Zhong Wang, Yong-yan PLoS One Research Article Targeting modules or signalings may open a new path to understanding the complex pharmacological mechanisms of reversing disease processes. However, determining how to quantify the structural alteration of these signalings or modules in pharmacological networks poses a great challenge towards realizing rational drug use in clinical medicine. Here, we explore a novel approach for dynamic comparative and quantitative analysis of the topological structural variation of modules in molecular networks, proposing the concept of allosteric modules (AMs). Based on the ischemic brain of mice, we optimize module distribution in different compound-dependent modular networks by using the minimum entropy criterion and then calculate the variation in similarity values of AMs under various conditions using a novel method of SimiNEF. The diverse pharmacological dynamic stereo-scrolls of AMs with functional gradient alteration, which consist of five types of AMs, may robustly deconstruct modular networks under the same ischemic conditions. The concept of AMs can not only integrate the responsive mechanisms of different compounds based on topological cascading variation but also obtain valuable structural information about disease and pharmacological networks beyond pathway analysis. We thereby provide a new systemic quantitative strategy for rationally determining pharmacological mechanisms of altered modular networks based on topological variation. Public Library of Science 2016-07-06 /pmc/articles/PMC4934924/ /pubmed/27383195 http://dx.doi.org/10.1371/journal.pone.0158379 Text en © 2016 Chen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chen, Yin-ying
Yu, Ya-nan
Zhang, Ying-ying
Li, Bing
Liu, Jun
Li, Dong-feng
Wu, Ping
Wang, Jie
Wang, Zhong
Wang, Yong-yan
Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks
title Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks
title_full Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks
title_fullStr Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks
title_full_unstemmed Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks
title_short Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks
title_sort quantitative determination of flexible pharmacological mechanisms based on topological variation in mice anti-ischemic modular networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934924/
https://www.ncbi.nlm.nih.gov/pubmed/27383195
http://dx.doi.org/10.1371/journal.pone.0158379
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