A fuzzy logic-based computational method for the repurposing of drugs against COVID-19.

IF 2.2 4区 工程技术 Q3 PHARMACOLOGY & PHARMACY
Bioimpacts Pub Date : 2022-01-01 DOI:10.34172/bi.2021.40
Yosef Masoudi-Sobhanzadeh, Hosein Esmaeili, Ali Masoudi-Nejad
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引用次数: 6

Abstract

Introduction: COVID-19 has spread out all around the world and seriously interrupted human activities. Being a newfound disease, not only many aspects of the disease are unknown, but also there is not an effective medication to cure the disease. Besides, designing a drug is a time-consuming process and needs large investment. Hence, drug repurposing techniques, employed to discover the hidden benefits of the existing drugs, maybe a useful option for treating COVID-19. Methods: The present study exploits the drug repositioning concepts and introduces some candidate drugs which may be effective in controlling COVID-19. The suggested method consists of three main steps. First, the required data such as the amino acid sequences of targets and drug-target interactions are extracted from the public databases. Second, the similarity score between the targets (protein/enzymes) and genome of SARS-COV-2 is computed using the proposed fuzzy logic-based method. Since the classical approaches yield outcomes which may not be useful for the real-world applications, the fuzzy technique can address the issue. Third, after ranking targets based on the obtained scores, the usefulness of drugs affecting them is examined for managing COVID-19. Results: The results indicate that antiviral medicines, designed for curing hepatitis C, may also cure COVID-19. According to the findings, ribavirin, simeprevir, danoprevir, and XTL-6865 may be helpful in controlling the disease. Conclusion: It can be concluded that the similarity-based drug repurposing techniques may be the most suitable option for managing emerging diseases such as COVID-19 and can be applied to a wide range of data. Also, fuzzy logic-based scoring methods can produce outcomes which are more consistent with the real-world biological applications than others.

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基于模糊逻辑的新冠肺炎药物再利用计算方法
导语:新冠肺炎疫情已在全球蔓延,严重干扰了人类活动。作为一种新发现的疾病,不仅疾病的许多方面是未知的,而且还没有有效的药物来治疗这种疾病。此外,设计药物是一个耗时的过程,需要大量的投资。因此,用于发现现有药物隐藏益处的药物再利用技术可能是治疗COVID-19的有用选择。方法:利用药物重新定位的概念,介绍一些可能有效控制COVID-19的候选药物。建议的方法包括三个主要步骤。首先,从公共数据库中提取所需数据,如靶点的氨基酸序列和药物-靶点相互作用等。其次,利用提出的基于模糊逻辑的方法计算SARS-COV-2靶点(蛋白质/酶)与基因组的相似度得分。由于经典方法产生的结果可能不适用于实际应用,模糊技术可以解决这个问题。第三,根据获得的分数对目标进行排序后,检查影响目标的药物对治疗COVID-19的有效性。结果:研究结果表明,用于治疗丙型肝炎的抗病毒药物也可能治疗COVID-19。根据研究结果,利巴韦林、西莫普韦、达诺韦和XTL-6865可能有助于控制疾病。结论:基于相似性的药物再利用技术可能是新冠肺炎等新发疾病管理的最合适选择,可应用于广泛的数据。此外,基于模糊逻辑的评分方法可以产生比其他方法更符合现实生物应用的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Bioimpacts
Bioimpacts Pharmacology, Toxicology and Pharmaceutics-Pharmaceutical Science
CiteScore
4.80
自引率
7.70%
发文量
36
审稿时长
5 weeks
期刊介绍: BioImpacts (BI) is a peer-reviewed multidisciplinary international journal, covering original research articles, reviews, commentaries, hypotheses, methodologies, and visions/reflections dealing with all aspects of biological and biomedical researches at molecular, cellular, functional and translational dimensions.
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