| 摘要: |
| 随着人民生活水平的提高，肥胖已日益成为成年人及儿童面临的主要健康问题。药物是肥胖的主要治疗手段，但现有药物数量有限且在治疗效果上也不能满足所有患者的需求。在减肥新药陷入研发困境的同时，采用药物重定位（DR）策略挖掘现有药物的新适应症可为发现新的减肥药物提供思路和方向。近年来稳步增加的生物医学数据及持续发展的高通量筛选技术在减肥药物的DR领域显示出巨大的潜力，以计算机为主的计算方法和以高通量筛选为主的实验方法以更加系统合理的方式实现DR。计算方法由数据驱动，结合了数据库、网络药理学和人工智能的应用。实验方法从低通量基于动物模型的技术过渡到高通量的筛选，为发现肥胖疾病的潜在治疗药物提供机遇。本综述回顾了DR系统的研究方法以及其在发现潜在减肥药物中的应用进展。 |
| 关键词: 肥胖 减肥药物 药物重定位 计算方法 实验方法 数据库 网络药理学 人工智能 |
| DOI：10.16781/j.CN31-2187/R.20220392 |
| 投稿时间：2022-05-09修订日期：2022-10-31 |
| 基金项目: |
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| Drug repositioning and its application in the discovery of potential anti-obesity drugs: recent progress |
| CHEN Feng,ZHANG Zhen,CHEN Fei,LIU Xia* |
(Department of Clinical Pharmacy, School of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China
*Corresponding author) |
| Abstract: |
| With the improvement of people's living standards, obesity has increasingly become a major health problem for adults and children. Drugs are still the main treatment for obesity, but the number of existing drugs is limited and the effect can hardly meet the needs of all patients. While new anti-obesity drugs are in a difficult development situation, the use of drug repositioning (DR) strategy to explore new indications of existing drugs can provide ideas and directions for the discovery of new anti-obesity drugs. In recent years, the steady increase of biomedical data and the continuous development of high-throughput screening technology have shown great potential anti-obesity DR, which is achieved in a more systematic and rational way by computer-based computational approaches and experimental approaches based on high-throughput screening. The computational approaches are driven by data, combining the application of databases, network pharmacology and artificial intelligence. The experimental approaches have transited from low-throughput animal model-based techniques to high-throughput screening, providing opportunities to discover potential therapeutic drugs for obesity. Here, we review the research methods of DR and its application in the discovery of potential anti-obesity drugs. |
| Key words: obesity anti-obesity drugs drug repositioning computational approaches experimental approaches database network pharmacology artificial intelligence |
