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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology
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Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology

机译：用网络药理学治疗难治性癫痫的潜在药物靶标

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Epilepsy is the fourth most common neurological disease after migraine, stroke, and Alzheimer's disease. Approximately one-third of all epilepsy cases are refractory to the existing anticonvulsants. Thus, there is an unmet need for newer antiepileptic drugs (AEDs) to manage refractory epilepsy (RE). Discovery of novel AEDs for the treatment of RE further retards for want of potential pharmacological targets, unavailable due to unclear etiology of this disease. In this regard, network pharmacology as an area of bioinformatics is gaining popularity. It combines the methods of network biology and polypharmacology, which makes it a promising approach for finding new molecular targets. This work is aimed at discovering new pharmacological targets for the treatment of RE using network pharmacology methods. In the framework of our study, the genes associated with the development of RE were selected based on analysis of available data. The methods of network pharmacology were used to select 83 potential pharmacological targets linked to the selected genes. Then, 10 most promising targets were chosen based on analysis of published data. All selected target proteins participate in biological processes, which are considered to play a key role in the development of RE. For 9 of 10 selected targets, the potential associations with different kinds of epilepsy have been recently mentioned in the literature published, which gives additional evidence that the approach applied is rather promising.
机译：癫痫是偏头痛，中风和阿尔茨海默病后第四最常见的神经系统疾病。所有癫痫病例中约有三分之一的患者对现有的抗惊厥药令人难以忍受。因此，对新的抗癫痫药物（AED）有一种未满足的需求来管理难治性癫痫（RE）。在潜在的药理学靶点的潜在药理学靶点的治疗中发现新型AEDs的发现，由于该疾病的病因尚不公布。在这方面，网络药理学作为生物信息学的一个领域正在获得普及。它结合了网络生物学和多药地的方法，这使得它成为寻找新分子靶标的前景方法。这项工作旨在发现使用网络药理学方法治疗RE的新药理学靶标。在我们研究的框架中，根据可用数据的分析选择与RE发展相关的基因。网络药理学方法用于选择与所选基因连接的83个潜在的药理学靶标。然后，基于对公布数据的分析选择了10个最有前途的目标。所有选定的靶蛋白都参与生物过程，这些过程被认为在RE的发展中发挥着关键作用。对于10个选定的靶标，最近在文献中发表的潜在癫痫潜在的癫痫症，这提供了额外的证据表明所应用的方法相当承诺。

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