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Network-based assessment of the selectivity of metabolic drug targets in Plasmodium falciparum with respect to human liver metabolism

机译:基于网络的恶性疟原虫中代谢药物靶标相对于人类肝脏代谢的选择性评估

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Background The search for new drug targets for antibiotics against Plasmodium falciparum, a major cause of human deaths, is a pressing scientific issue, as multiple resistance strains spread rapidly. Metabolic network-based analyses may help to identify those parasite’s essential enzymes whose homologous counterparts in the human host cells are either absent, non-essential or relatively less essential. Results Using the well-curated metabolic networks PlasmoNet of the parasite Plasmodium falciparum and HepatoNet1 of the human hepatocyte, the selectivity of 48 experimental antimalarial drug targets was analyzed. Applying in silico gene deletions, 24 of these drug targets were found to be perfectly selective, in that they were essential for the parasite but non-essential for the human cell. The selectivity of a subset of enzymes, that were essential in both models, was evaluated with the reduced fitness concept. It was, then, possible to quantify the reduction in functional fitness of the two networks under the progressive inhibition of the same enzymatic activity. Overall, this in silico analysis provided a selectivity ranking that was in line with numerous in vivo and in vitro observations. Conclusions Genome-scale models can be useful to depict and quantify the effects of enzymatic inhibitions on the impaired production of biomass components. From the perspective of a host-pathogen metabolic interaction, an estimation of the drug targets-induced consequences can be beneficial for the development of a selective anti-parasitic drug.
机译:背景技术由于多种耐药菌株迅速传播,寻找抗恶性疟原虫(人类死亡的主要原因)的抗生素的新药物靶标是紧迫的科学问题。基于代谢网络的分析可能有助于鉴定那些寄生虫的必需酶,这些寄生虫在人类宿主细胞中的同源对应物不存在,不重要或相对不重要。结果利用精心设计的寄生虫恶性疟原虫的PlasmoNet和人类肝细胞的HepatoNet1的代谢网络,分析了48种实验性抗疟药靶标的选择性。应用计算机模拟基因删除,发现这些药物靶标中的24个具有完美的选择性,因为它们对寄生虫必不可少,但对人体细胞却不是必需的。使用降低的适应性概念评估了两个模型中必不可少的一部分酶的选择性。然后,有可能量化在逐渐抑制相同酶活性的情况下两个网络功能适应性的降低。总的来说,这种计算机模拟分析提供的选择性等级与众多的体内和体外观察结果一致。结论基因组规模模型可用于描述和量化酶促抑制作用对生物质组分生产受损的影响。从宿主-病原体代谢相互作用的角度来看,对药物靶标诱导的后果的评估可能对开发选择性抗寄生虫药物有益。

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