KG-DTI: a knowledge graph based deep learning method for drug-target interaction predictions and Alzheimer's disease drug repositions
KG-DTI: a knowledge graph based deep learning method for drug-target interaction predictions and Alzheimer's disease drug repositions
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KG-DTI：基于知识图谱的深度学习方法，用于药物-靶标相互作用预测和阿尔茨海默病药物重新定位
DOI：
10.1007/s10489-021-02454-8
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发表时间：
2021-05-12
影响因子：
5.3
通讯作者：
Song, Tao
中科院分区：
文献类型：
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作者：
Wang, Shudong;Du, Zhenzhen;Song, Tao
药物重新定位通过预测药物 - 靶点相互作用（DTI），将已获批药物推荐给潜在靶点，能够节省药物研发成本并缩短研发周期。在这项研究中，我们提出了一种名为KG - DTI的基于知识图谱的新型深度学习方法，用于DTI预测。具体而言，利用DistMult嵌入策略构建了一个包含29,607个阳性药物 - 靶点对的知识图谱。提出了一个Conv - Conv模块来提取药物 - 靶点对（DTP）的特征，随后使用全连接神经网络进行DTI计算。在随机选择的11,840个正负样本上进行了数据实验。结果表明，KG - DTI在五折交叉验证中平均准确率达到88.0%，F1分数为87.7%，受试者工作特征曲线下面积（AUROC）为94.3%，平均精度均值（AUPR）为95%。在实际应用中，KG - DTI通过载脂蛋白E靶点将药物重新定位用于阿尔茨海默病（AD）的治疗。结果发现，排名前十的推荐药物中有七种已在临床实践中使用，或有文献支持其对AD有效。配体 - 靶点对接结果显示，排名第一的推荐药物能够与载脂蛋白E显著对接，这为重新定位潜在药物用于AD治疗提供了重要线索。
Drug repositioning, which recommends approved drugs to potential targets by predicting drug-target interactions (DTIs), can save the cost and shorten the period of drug development. In this work, we propose a novel knowledge graph based deep learning method, named KG-DTI, for DTIs predictions. Specifically, a knowledge graph of 29,607 positive drug-target pairs is constructed by DistMult embedding strategy. A Conv-Conv module is proposed to extract features of drug-target pairs (DTPs), which is followed by a fully connected neural network for DTIs calculation. Data experiments are conducted on randomly chosen 11,840 positive and negative samples. It is obtained that KG-DTI achieves average ACC by 88.0%, F1-Score by 87.7%, AUROC by 94.3% and AUPR by 95% in five-fold cross-validation. In practice, KG-DTI is applied to reposition drugs to Alzheimer's disease (AD) by Apolipoprotein E target. As results, it is found that seven of the top ten recommended drugs have been used in clinic practice or with literature supported useful to AD. Ligand-target docking results show that the top one recommended drug can dock with Apolipoprotein E significantly, which gives vital hints in repositioning potential drug to AD treatment.