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基于网络的新型药物靶点鉴定工具。

Network-based tools for the identification of novel drug targets.

机构信息

Statistical and Biological Physics Group of the Hungarian Academy of Sciences, Pázmány P. s. 1A, H-1117 Budapest, Hungary.

出版信息

Sci Signal. 2011 May 17;4(173):pt3. doi: 10.1126/scisignal.2001950.

DOI:10.1126/scisignal.2001950
PMID:21586727
Abstract

In the past few years, network-based tools have become increasingly important in the identification of novel molecular targets for drug development. Systems-based approaches to predict signal transduction-related drug targets have developed into an especially promising field. Here, we summarize our studies, which indicate that modular bridges and overlaps of protein-protein interaction and signaling networks may be of key importance in future drug design. Intermodular nodes are very efficient in mediating the transmission of perturbations between signaling modules and are important in network cooperation. The analysis of stress-induced rearrangements of the yeast interactome by the ModuLand modularization algorithm indicated that components of modular overlap are key players in cellular adaptation to stress. Signaling crosstalk was much more pronounced in humans than in Caenorhabditis elegans or Drosophila melanogaster in the SignaLink (http://www.SignaLink.org) database, a uniformly curated database of eight major signaling pathways. We also showed that signaling proteins that participate in multiple pathways included multiple established drug targets and drug target candidates. Lastly, we caution that the pervasive overlap of cellular network modules implies that wider use of multitarget drugs to partially inhibit multiple individual proteins will be necessary to modify specific cellular functions, because targeting single proteins for complete disruption usually affects multiple cellular functions with little specificity for a particular process. Tools for analyzing network topology and especially network dynamics have great potential to identify alternative sets of targets for developing multitarget drugs.

摘要

在过去的几年中,基于网络的工具在发现新药开发的新分子靶标方面变得越来越重要。基于系统的方法来预测信号转导相关的药物靶标已经发展成为一个特别有前途的领域。在这里,我们总结了我们的研究结果,表明蛋白质-蛋白质相互作用和信号网络的模块化桥梁和重叠可能是未来药物设计的关键。 互模块节点在介导信号模块之间的扰动传递方面非常有效,并且在网络合作中很重要。通过 ModuLand 模块化算法对酵母相互作用组的应激诱导重排进行分析表明,模块化重叠的成分是细胞适应应激的关键因素。在 SignaLink(http://www.SignaLink.org)数据库中,信号转导串扰在人类中比在秀丽隐杆线虫或黑腹果蝇中更为明显,这是一个经过统一整理的 8 个主要信号通路的数据库。我们还表明,参与多个途径的信号蛋白包括多个已建立的药物靶标和药物靶标候选物。最后,我们警告说,细胞网络模块的普遍重叠意味着需要更广泛地使用多靶标药物来部分抑制多个单个蛋白,以改变特定的细胞功能,因为针对单个蛋白进行完全破坏通常会影响多个细胞功能,而对特定过程的特异性很小。用于分析网络拓扑结构,特别是网络动态的工具具有很大的潜力,可以确定开发多靶标药物的替代靶标集。

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