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

被引:10
作者
Chen, Yin-ying [1 ,2 ]
Yu, Ya-nan [1 ]
Zhang, Ying-ying [1 ]
Li, Bing [1 ]
Liu, Jun [1 ]
Li, Dong-feng [3 ]
Wu, Ping [2 ]
Wang, Jie [2 ]
Wang, Zhong [1 ]
Wang, Yong-yan [1 ]
机构
[1] China Acad Chinese Med Sci, Inst Basic Res Clin Med, Beijing, Peoples R China
[2] China Acad Chinese Med Sci, Guanganmen Hosp, Beijing, Peoples R China
[3] Peking Univ, Sch Math Sci, Beijing, Peoples R China
关键词
PROTEIN-INTERACTION NETWORKS; DRUG DISCOVERY; CEREBRAL-ISCHEMIA; MOUSE HIPPOCAMPUS; PATHWAYS; ALLOSTERY; EXPRESSION; PREDICTION; COMPLEXES; OCCLUSION;
D O I
10.1371/journal.pone.0158379
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
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页数:19
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