Jang Giup, Lee Taekeon, Lee Byung Mun, Yoon Youngmi
Dept. of IT Convergence Engineering, Gachon University, Korea.
Mol Biosyst. 2017 Jun 27;13(7):1399-1405. doi: 10.1039/c7mb00020k.
There have been many attempts to identify and develop new uses for existing drugs, which is known as drug repositioning. Among these efforts, text mining is an effective means of discovering novel knowledge from a large amount of literature data. We identify a gene regulation by a drug and a phenotype based on the biomedical literature. Drugs or phenotypes can activate or inhibit gene regulation. We calculate the therapeutic possibility that a drug acts on a phenotype by means of these two types of regulation. We assume that a drug treats a phenotype if the genes regulated by the phenotype are inversely correlated with the genes regulated by the drug. Based on this hypothesis, we identify drug-phenotype associations with therapeutic possibility. To validate the drug-phenotype associations predicted by our method, we make an enrichment comparison with known drug-phenotype associations. We also identify candidate drugs for drug repositioning from novel associations and thus reveal that our method is a novel approach to drug repositioning.
人们已经进行了许多尝试来识别和开发现有药物的新用途，这被称为药物重新定位。在这些努力中，文本挖掘是从大量文献数据中发现新知识的有效手段。我们基于生物医学文献确定药物对基因的调控以及一种表型。药物或表型可以激活或抑制基因调控。我们通过这两种调控方式计算药物作用于一种表型的治疗可能性。我们假设，如果由该表型调控的基因与由药物调控的基因呈负相关，那么该药物可治疗此表型。基于这一假设，我们确定具有治疗可能性的药物 - 表型关联。为了验证我们的方法预测的药物 - 表型关联，我们与已知的药物 - 表型关联进行富集比较。我们还从新关联中识别出用于药物重新定位的候选药物，从而表明我们的方法是一种药物重新定位的新方法。
