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首页> 外文期刊>Nucleic acids research >SynSysNet: integration of experimental data on synaptic protein–protein interactions with drug-target relations
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SynSysNet: integration of experimental data on synaptic protein–protein interactions with drug-target relations

机译:SynSysNet:整合突触蛋白-蛋白相互作用与药物-靶标关系的实验数据

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摘要

We created SynSysNet, available online at http://bioinformatics.charite.de/synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal communication and information processing. These processes are dynamically regulated by a network of proteins. New developments in interaction proteomics and yeast two-hybrid methods allow unbiased detection of interactors. The consolidation of data from different resources and methods is important to understand the relation to human behaviour and disease and to identify new therapeutic approaches. To this end, we established SynSysNet from a set of ~1000 synapse specific proteins, their structures and small-molecule interactions. For two-thirds of these, 3D structures are provided (from Protein Data Bank and homology modelling). Drug-target interactions for 750 approved drugs and 50 000 compounds, as well as 5000 experimentally validated protein–protein interactions, are included. The resulting interaction network and user-selected parts can be viewed interactively and exported in XGMML. Approximately 200 involved pathways can be explored regarding drug-target interactions. Homology-modelled structures are downloadable in Protein Data Bank format, and drugs are available as MOL-files. Protein–protein interactions and drug-target interactions can be viewed as networks; corresponding PubMed IDs or sources are given.
机译:我们创建了SynSysNet,可从http://bioinformatics.charite.de/synsysnet在线获取,以提供一个平台,该平台可创建一个全面的突触相互作用的4D网络。神经元突触是连接大脑中神经细胞的基本结构,它们负责神经元的交流和信息处理。这些过程由蛋白质网络动态调节。相互作用蛋白质组学和酵母双杂交方法的新发展允许对相互作用物的无偏检测。整合来自不同资源和方法的数据对于理解与人类行为和疾病的关系并确定新的治疗方法非常重要。为此,我们从一组约1000个突触特异性蛋白,它们的结构和小分子相互作用中建立了SynSysNet。对于其中的三分之二,提供了3D结构(来自蛋白质数据库和同源性建模)。包括750种已批准药物和5万种化合物的药物-靶标相互作用以及5000种经过实验验证的蛋白质-蛋白质相互作用。可以交互查看生成的交互网络和用户选择的零件,并在XGMML中将其导出。关于药物-靶标相互作用,可以探索大约200个参与途径。同源性建模的结构可以以Protein Data Bank格式下载,药物可以MOL文件的形式获得。蛋白质-蛋白质相互作用和药物-靶标相互作用可以看作是网络;给出了相应的PubMed ID或来源。

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