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合成药物再利用治疗高血压:基于关联规则和新型离散算法的数据挖掘方法。

Synthetic repurposing of drugs against hypertension: a datamining method based on association rules and a novel discrete algorithm.

机构信息

Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.

出版信息

BMC Bioinformatics. 2020 Jul 16;21(1):313. doi: 10.1186/s12859-020-03644-w.

DOI:10.1186/s12859-020-03644-w
PMID:32677879
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7469914/
Abstract

BACKGROUND

Drug repurposing aims to detect the new therapeutic benefits of the existing drugs and reduce the spent time and cost of the drug development projects. The synthetic repurposing of drugs may prove to be more useful than the single repurposing in terms of reducing toxicity and enhancing efficacy. However, the researchers have not given it serious consideration. To address the issue, a novel datamining method is introduced and applied to repositioning of drugs for hypertension (HT) which is a serious medical condition and needs some improved treatment plans to help treat it.

RESULTS

A novel two-step data mining method, which is based on the If-Then association rules as well as a novel discrete optimization algorithm, was introduced and applied to the synthetic repurposing of drugs for HT. The required data were also extracted from DrugBank, KEGG, and DrugR+ databases. The findings indicated that based on the different statistical criteria, the proposed method outperformed the other state-of-the-art approaches. In contrast to the previously proposed methods which had failed to discover a list on some datasets, our method could find a combination list for all of them.

CONCLUSION

Since the proposed synthetic method uses medications in small dosages, it might revive some failed drug development projects and put forward a suitable plan for treating different diseases such as COVID-19 and HT. It is also worth noting that applying efficient computational methods helps to produce better results.

摘要

背景

药物再利用旨在发现现有药物的新治疗功效,减少药物开发项目的时间和成本。药物的综合再利用在降低毒性和提高疗效方面可能比单一再利用更有用。然而,研究人员并没有认真考虑这一点。为了解决这个问题,引入并应用了一种新的数据挖掘方法,用于治疗高血压(HT)的药物重新定位,这是一种严重的医疗状况,需要一些改进的治疗方案来帮助治疗。

结果

引入并应用了一种新的两步数据挖掘方法,该方法基于 If-Then 关联规则和一种新的离散优化算法,用于 HT 的药物综合再利用。所需的数据也从 DrugBank、KEGG 和 DrugR+数据库中提取。研究结果表明,根据不同的统计标准,该方法优于其他最先进的方法。与之前提出的方法不同,这些方法在一些数据集上无法发现列表,我们的方法可以为所有数据集找到组合列表。

结论

由于所提出的综合方法使用小剂量的药物,它可能会恢复一些失败的药物开发项目,并为治疗 COVID-19 和 HT 等不同疾病提出合适的方案。值得注意的是,应用有效的计算方法有助于产生更好的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/86c38654d8b0/12859_2020_3644_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/88436f52a98b/12859_2020_3644_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/04fdc6a8a377/12859_2020_3644_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/03441bc49600/12859_2020_3644_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/86c38654d8b0/12859_2020_3644_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/88436f52a98b/12859_2020_3644_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/04fdc6a8a377/12859_2020_3644_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/03441bc49600/12859_2020_3644_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6676/7469914/86c38654d8b0/12859_2020_3644_Fig4_HTML.jpg

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