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‘Load Points’ and ‘Choke Points’ as Nodes for Prioritizing Drug Targets in Pseudomonas aeruginosa (Supplementary)

机译:“负载点”和“阻塞点”作为优先处理铜绿假单胞菌中药物靶标的节点(补充)

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摘要

Biological pathways information has accumulated along with Genomic sequence data. These metabolic pathways help us in understanding network robustness and complex reaction networks. They also provide a framework for improved understanding of microbial physiology and for antimicrobial drug discovery. This article is an attempt to understand the local and global properties of metabolic networks in P. aeruginosa and to identify potential drug targets through ‘load point’ and ‘choke point’ analyses. In this study, we identify 25 choke point enzymes in pathways unique to P. aeruginosa and 202 choke point enzymes in the common pathways between the pathogen and the host human. We also list top 10 choke point enzymes based on the load point values and number of shortest paths and propose them as putative targets. These data underscore the utility of systems analyses methods for understanding human metabolic network in drug discovery process and in-depth understanding of the mechanism of diseases.
机译:生物途径信息已与基因组序列数据一起积累。这些代谢途径有助于我们理解网络的稳健性和复杂的反应网络。它们还提供了一个框架,可增进对微生物生理学的了解和抗菌药物的发现。本文旨在了解铜绿假单胞菌代谢网络的局部和全局特性,并通过“负荷点”和“ ch点”分析确定潜在的药物靶标。在这项研究中,我们确定了铜绿假单胞菌特有的途径中的25个窒息点酶和病原体与宿主人类之间的常见途径中的202种窒息点酶。我们还将根据负载点值和最短路径数列出前10个阻塞点酶,并提出它们作为推定目标。这些数据强调了系统分析方法的实用性,这些方法可用于了解药物开发过程中的人体代谢网络以及对疾病机理的深入理解。

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