Estimating novel potential drug targets of Plasmodium falciparum by analysing the metabolic network of knock-out strains in silico
Estimating novel potential drug targets of Plasmodium falciparum by analysing the metabolic network of knock-out strains in silico
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DOI：
10.1016/j.meegid.2008.01.007
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发表时间：
2009-05-01
影响因子：
3.2
通讯作者：
Koenig, Rainer
中科院分区：
文献类型：
--
作者：
Fatumo, Segun;Plaimas, Kitiporn;Koenig, Rainer
疟疾是世界上最常见和最严重的疾病之一，每年造成约300万人死亡。最严重的是由原生动物恶性疟原虫引起的。生物医学研究可以通过有效和特异性地靶向这种寄生虫的必需酶来治疗这种疾病。然而，这种寄生虫已经对现有药物产生了抗药性，因此必须发现新药。我们已经建立了一个简单的计算工具，分析恶性疟原虫的代谢网络的拓扑结构，以确定必要的酶作为可能的药物靶点。我们通过在计算机上删除（敲除）这样的反应来研究代谢网络中反应的重要性。该算法选择了研究反应的相邻化合物，这些化合物必须通过替代生物化学途径产生。使用广度优先搜索，我们定性地测试了这些产品是否可以由作为代谢通量的潜在偏差的反应产生。在此基础上，我们确定了70个基本反应。我们的研究结果与已批准的疟疾药物的38个目标的综合清单进行了比较。当将我们的方法与最近进行的计算机分析相结合时[Yeh，I.，Hanekamp，T.，Tsoka，S.，卡普警局阿尔特曼RB 2004.恶性疟原虫代谢的计算分析：组织基因组信息以促进药物发现。Genome Res. 14，917-924]，我们可以提高预测结果的精度。最后，我们提出了22个新的恶性疟原虫潜在候选靶点的细化列表，其中一半有合理的证据表明是有效的微生物和癌症靶点。(C)2008 Elsevier B. V.保留所有权利。
Malaria is one of the world's most common and serious diseases causing death of about 3 million people each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Biomedical research could enable treating the disease by effectively and specifically targeting essential enzymes of this parasite. However, the parasite has developed resistance to existing drugs making it indispensable to discover new drugs. We have established a simple computational tool which analyses the topology of the metabolic network of P.falciparum to identify essential enzymes as possible drug targets. We investigated the essentiality of a reaction in the metabolic network by deleting (knocking-out) such a reaction in silico. The algorithm selected neighbouring compounds of the investigated reaction that had to be produced by alternative biochemical pathways. Using breadth first searches, we tested qualitatively if these products could be generated by reactions that serve as potential deviations of the metabolic flux. With this we identified 70 essential reactions. Our results were compared with a comprehensive list of 38 targets of approved malaria drugs. When combining our approach with an in silico analysis performed recently [Yeh, I., Hanekamp, T., Tsoka, S., Karp, P.D., Altman, R.B., 2004. Computational analysis of Plasmodium falciparum metabolism: organizing genomic information to facilitate drug discovery. Genome Res. 14, 917-924] we could improve the precision of the prediction results. Finally we present a refined list of 22 new potential candidate targets for P. falciparum, half of which have reasonable evidence to be valid targets against micro-organisms and cancer. (C) 2008 Elsevier B.V. All rights reserved.