Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach.
Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach.
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DOI：
10.3389/fmolb.2016.00022
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发表时间：
2016
影响因子：
5
通讯作者：
Dandekar T
中科院分区：
文献类型：
--
作者：
Kaltdorf M;Srivastava M;Gupta SK;Liang C;Binder J;Dietl AM;Meir Z;Haas H;Osherov N;Krappmann S;Dandekar T
寻找新的抗霉菌药物具有挑战性，因为潜在的靶蛋白可能具有接近的人类直系同源物。我们在这里专注于确定对真菌生长至关重要的代谢靶标，并且与人类蛋白质中的靶标具有最小的相似性。我们在这里进行比较和联合收割机：（I）使用基本模式分析和使用表达数据的通量估计近似的直接代谢网络建模，（II）通过条件特异性高表达酶的转录组分析靶向代谢基因，以及（III）酶结构、酶互连性（“枢纽”）的分析，以及使用直系关系鉴定病原体特异性酶。我们已经确定了64个靶标，包括参与维生素合成、脂质和氨基酸生物合成的代谢酶，其中包括18个从文献中验证的靶标，2个经验证的靶标和5个目前在自己的遗传实验中检查的靶标，以及38个进一步有希望的新靶标蛋白，这些蛋白与人类蛋白质非正交，参与代谢，是这些管道中的高排名药物靶标。
New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness (“hubs”), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.