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Drug Target Interplay: A Network-based Analysis of Human Diseases and the Drug Targets

机译:药物目标相互作用:基于网络的人类疾病和药物目标分析

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Screening and identifying a disease-specific novel drug target is the first step towards a rational drug designing approach. Due to the advent of high throughput data generation techniques, the protein search space has now exceeded 24,500 human protein coding genes, which encodes approximately 1804proteins. This work aims at mining out the relationship between target proteins, drugs, and diseases genes through a network-based systems biology approach. A network of all FDA approved drugs, along with their targets were utilized to construct the proposed drug target (DT) network. Further, the experimental drugs were mapped into the DT network to infer the functional relationship by utilizing the respective network attributes. Similar to the DT network, a network of disease genes was created through OMIM Gene Map and Morbid Map, to link the binary associations of disorder-disease genes. In the proposed model of Human Interactome Network, shortest path length between the target protein and disease gene was used to infer the correlation between 'Drug Targets' and 'Disease-Gene'. This network-based study will help researchers to analyze, infer and identify disease-specific novel drug targets through harnessing the graph theory based network attributes.
机译:筛选和鉴定疾病特异性新药靶标是朝着合理的药物设计方法的第一步。由于高通量数据生成技术的出现,蛋白质搜索空间现在已经超过了24,500个人蛋白质编码基因,其编码约1804颗粒。这项工作旨在通过基于网络的系统生物学方法挖掘目标蛋白质,药物和疾病基因之间的关系。所有FDA批准的药物的网络以及其目标都用于构建所提出的药物目标(DT)网络。此外,将实验药物映射到DT网络中,通过利用各自的网络属性来推断功能关系。与DT网络类似,通过OMIM基因图和病态图创建疾病基因网络,以将疾病疾病基因的二元关联联系起来。在拟议的人类互乱网络模型中,目标蛋白质和疾病基因之间的最短路径长度用于推断“药物靶标”和“疾病 - 基因”之间的相关性。该基于网络的研究将通过利用基于图论的网络属性来帮助研究人员分析,推断和识别疾病特异性新药目标。

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