可药性
胶质母细胞瘤
受体酪氨酸激酶
计算生物学
生物信息学
生物网络
酪氨酸激酶
系统生物学
激酶
U87型
药物发现
系统药理学
癌症研究
生物
药品
生物信息学
神经科学
基因
信号转导
药理学
细胞生物学
遗传学
出处
期刊:Current Drug Discovery Technologies
[Bentham Science]
日期:2013-02-01
卷期号:10 (2): 125-138
被引量:5
标识
DOI:10.2174/1570163811310020005
摘要
With increasing knowledge of cellular networks of gene and molecular interactions, and their alterations in GBM (glioblastoma multiforme), it is now possible to apply methods of Network Pharmacology (NP) to predict candidate drug targets for this malignant brain tumor. NP requires the development of mathematical methods for network stability and perturbation analysis to identify sensitive and druggable network components, as well as computational platforms to carry out in silico simulations of therapeutic interventions. This review focuses on the three most frequently deregulated GBM pathways involving membrane receptor tyrosine kinases, p53, and Rb. Structural features of these networks that may confound targeted therapies are discussed. Keywords: Network pharmacology, glioblastoma, p53, Myc, Rb, receptor tyrosine kinase
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