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DenguePredict: An Integrated Drug Repositioning Approach towards Drug Discovery for Dengue

机译:登革热预测:一种用于登革热药物发现的综合药物重新定位方法

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摘要

Dengue is a viral disease of expanding global incidence without cures. Here we present a drug repositioning system (DenguePredict) leveraging upon a unique drug treatment database and vast amounts of disease- and drug-related data. We first constructed a large-scale genetic disease network with enriched dengue genetics data curated from biomedical literature. We applied a network-based ranking algorithm to find dengue-related diseases from the disease network. We then developed a novel algorithm to prioritize FDA-approved drugs from dengue-related diseases to treat dengue. When tested in a de-novo validation setting, DenguePredict found the only two drugs tested in clinical trials for treating dengue and ranked them highly: chloroquine ranked at top 0.96% and ivermectin at top 22.75%. We showed that drugs targeting immune systems and arachidonic acid metabolism-related apoptotic pathways might represent innovative drugs to treat dengue. In summary, DenguePredict, by combining comprehensive disease- and drug-related data and novel algorithms, may greatly facilitate drug discovery for dengue.
机译:登革热是一种病毒性疾病,无法治愈就扩大了全球发病率。在这里,我们将利用独特的药物治疗数据库以及大量疾病和药物相关数据,提供一种药物重新定位系统(DenguePredict)。我们首先利用从生物医学文献中收集的丰富登革热遗传数据,构建了一个大规模的遗传疾病网络。我们应用了基于网络的排名算法,从疾病网络中查找与登革热相关的疾病。然后,我们开发了一种新颖的算法,优先考虑FDA批准的与登革热相关疾病的药物来治疗登革热。在新型验证环境中进行测试时,DenguePredict发现只有两种在临床试验中测试过的用于治疗登革热的药物,并获得了很高的评价:氯喹排在前0.96%,伊维菌素排在前22.75%。我们发现靶向免疫系统和花生四烯酸代谢相关的凋亡途径的药物可能代表了治疗登革热的创新药物。总之,通过结合全面的疾病和药物相关数据以及新颖的算法,登革热预测可以极大地促进登革热的药物发现。

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