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攻克癌症信号转导“迷宫”:将生化工具与数学模型相结合,可以增强对每种分子缺陷的最佳靶点的识别。

Tackling the cancer signal transduction “labyrinth”: a combinatorial use of biochemical tools with mathematical models will enhance the identification of optimal targets for each molecular defect.

出版信息

Cancer. 2014 Feb 1;120(3):316-22. doi: 10.1002/cncr.28424.

Abstract

Unraveling cancer-associated molecular defects is crucial for further pharmacological targeting. Although novel techniques are being developed to elucidate genomic, proteomic, and transcriptomic alterations, the map of protein interactions and aberrations in normal but also in malignant cells is still obscure. It has been recently shown that many of the events in signaling cascades might be revealed using mathematical models. Transcriptional regulation still represents the main obstacle for the design of truly molecularly-targeted agents, mainly due to its enormous plasticity and heterogeneity in cells and tissues. Systematic mapping of signaling networks and application of new computational algorithms will reinforce the use of novel research tools in this venue. The case of epidermal growth factor receptor family proteins and their intracellular cross-talk interactions and downstream molecules is used as a representative paradigm.

摘要

解析与癌症相关的分子缺陷对于进一步的药物靶向至关重要。虽然正在开发新的技术来阐明基因组、蛋白质组和转录组的改变,但蛋白质相互作用和正常细胞以及恶性细胞中的异常的图谱仍然不清楚。最近已经表明,许多信号级联中的事件可以使用数学模型来揭示。转录调控仍然是设计真正的分子靶向药物的主要障碍,主要是由于其在细胞和组织中的巨大可塑性和异质性。信号网络的系统映射和新的计算算法的应用将加强在这一领域使用新的研究工具。表皮生长因子受体家族蛋白及其细胞内相互作用和下游分子的情况就是一个代表性范例。

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