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一种基于最大流的方法,用于对慢性病药物重新利用的药物进行优先级排序。

A Maximum Flow-Based Approach to Prioritize Drugs for Drug Repurposing of Chronic Diseases.

作者信息

Islam Md Mohaiminul, Wang Yang, Hu Pingzhao

机构信息

Department of Computer Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.

Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.

出版信息

Life (Basel). 2021 Oct 20;11(11):1115. doi: 10.3390/life11111115.

DOI:10.3390/life11111115
PMID:34832991
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8625622/
Abstract

The discovery of new drugs is required in the time of global aging and increasing populations. Traditional drug development strategies are expensive, time-consuming, and have high risks. Thus, drug repurposing, which treats new/other diseases using existing drugs, has become a very admired tactic. It can also be referred to as the re-investigation of the existing drugs that failed to indicate the usefulness for the new diseases. Previously published literature used maximum flow approaches to identify new drug targets for drug-resistant infectious diseases but not for drug repurposing. Therefore, we are proposing a maximum flow-based protein-protein interactions (PPIs) network analysis approach to identify new drug targets (proteins) from the targets of the FDA (Food and Drug Administration) drugs and their associated drugs for chronic diseases (such as breast cancer, inflammatory bowel disease (IBD), and chronic obstructive pulmonary disease (COPD)) treatment. Experimental results showed that we have successfully turned the drug repurposing into a maximum flow problem. Our top candidates of drug repurposing, Guanidine, Dasatinib, and Phenethyl Isothiocyanate for breast cancer, IBD, and COPD were experimentally validated by other independent research as the potential candidate drugs for these diseases, respectively. This shows the usefulness of the proposed maximum flow approach for drug repurposing.

摘要

在全球老龄化和人口不断增加的时代,新药的发现至关重要。传统的药物开发策略成本高昂、耗时且风险巨大。因此,药物再利用,即使用现有药物治疗新的/其他疾病,已成为一种备受推崇的策略。它也可被称为对那些未能显示对新疾病有用性的现有药物进行重新研究。先前发表的文献使用最大流方法来识别耐药性传染病的新药物靶点,但未用于药物再利用。因此,我们提出一种基于最大流的蛋白质 - 蛋白质相互作用(PPI)网络分析方法,从美国食品药品监督管理局(FDA)批准药物的靶点及其相关慢性病(如乳腺癌、炎症性肠病(IBD)和慢性阻塞性肺疾病(COPD))治疗药物中识别新的药物靶点(蛋白质)。实验结果表明,我们已成功将药物再利用转化为一个最大流问题。我们用于乳腺癌、IBD和COPD的药物再利用顶级候选药物胍、达沙替尼和异硫氰酸苯乙酯,分别被其他独立研究实验验证为这些疾病的潜在候选药物。这表明所提出的最大流方法在药物再利用方面的有用性。

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Nat Commun. 2021 Feb 15;12(1):1033. doi: 10.1038/s41467-021-21330-0.
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SARS-CoV-2 and Coronavirus Disease 2019: What We Know So Far.严重急性呼吸综合征冠状病毒2型与2019冠状病毒病:我们目前所了解的情况。
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Bioinformatics. 2019 Oct 1;35(19):3672-3678. doi: 10.1093/bioinformatics/btz156.
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