被评估在,体外和体外作为治疗肥胖的治疗工具:一个系统的审查
Ana Júlia Felipe Camelo Aguiar1, Wendjilla Fortunato de Medeiros2, Juliana Kelly da Silva-Maia2,3
1Biochemistry and Molecular Biology Postgraduate Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil.
International journal of molecular sciences
|September 14, 2024
概括
计算分析有效地选抗肥胖. 这一系统性审查证实,针对肥胖途径的酸的in silico预测与体外和体内结果一致,验证了用于药物发现的生物信息工具.
科学领域:
- 生物化学和生物信息学
- 药理学和药物发现
- 营养科学 营养科学
背景情况:
- 生物信息学和计算方法对于药物查和理解治疗效果越来越重要.
- 肥胖是一种复杂的代谢障碍,需要新的治疗策略,包括基于的干预措施.
- 在形研究提供了一个初步查方法,用于识别潜在的抗肥胖剂.
研究的目的:
- 系统地审查和评估对抗肥胖的化研究.
- 评估这些的计算预测和随后的体外/体内发现之间的一致性.
- 用计算方法识别用于治疗肥胖症的和它们的治疗标.
主要方法:
- 在PROSPERO (CRD42022355540) 中注册的,遵循PRISMA-P指南的系统文献综述.
- 在PubMed,ScienceDirect,Scopus,Web of Science,虚拟健康图书馆和EMBASE进行的搜索.
- 纳入标准侧重于反肥胖的研究,随后通过分子对接在体外和体内进行评估.
主要成果:
- 七项研究符合纳入标准,确定了来自可可,,大米,芝麻,海和阿祖基豆等不同来源的抗肥胖.
- 胰腺脂酶是主要标 (n=5),所有已识别的都显示抑制,由体外和体外数据证实.
- 其他作为PPARγ和PPARα激动剂 (n=2),表明脂质代谢和脂肪生成的各种机制;46.15%的研究具有不确定的偏差风险.
结论:
- 在研究,特别是分子对接,是有效的选抗肥胖.
- 计算预测与实验验证有很强的相关性,为进一步研究提供了指导.
- 这种方法加快了新型抗肥胖的发现,为体外和体内研究提供了关键的见解.
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