Zhang Yaqiong, Chen Yuanyuan, Sun Chenglin, Li Fang, Shen Yin
Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, Hubei, China.
Front Pharmacol. 2025 Jul 31;16:1626907. doi: 10.3389/fphar.2025.1626907. eCollection 2025.
Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss among the elderly. α-Lipoic acid (ALA), a naturally occurring antioxidant and iron-chelator, has shown potential in modulating ferroptosis, but its mechanism in AMD remains unclear.
Network pharmacology, transcriptomic profiling, and machine learning were used to identify potential molecular targets of ALA in AMD. Core genes were identified through interaction network construction, functional enrichment analysis, and machine learning-based screening. Molecular docking and molecular dynamics simulations were performed to assess the binding affinity and stability between ALA and its predicted targets. validation was conducted using a sodium iodate (SI)-induced AMD mouse model, with retinal structure, function, oxidative stress, and gene expression evaluated through behavioral tests, histological staining, and qRT-PCR.
We identified six ferroptosis-related core targets ( and ) of ALA implicated in AMD. Molecular docking revealed strong binding affinities between ALA and these six targets, with dynamic simulations confirming stable interactions, particularly with and . In the SI-induced AMD mouse model, ALA significantly preserved retinal structure, maintained visual function, and reduced oxidative stress and iron accumulation. qRT-PCR confirmed that ALA exerted differential effects on the expression of the six genes, demonstrating a context-dependent regulatory mechanism.
This study provides multi-level evidence that ALA protects against AMD by modulating ferroptosis-related pathways and restoring retinal structural integrity and functions. These findings warrant further investigation into the therapeutic potential of ALA in AMD.
年龄相关性黄斑变性(AMD)是老年人不可逆视力丧失的主要原因。α-硫辛酸(ALA)是一种天然存在的抗氧化剂和铁螯合剂,已显示出在调节铁死亡方面的潜力,但其在AMD中的作用机制仍不清楚。
运用网络药理学、转录组分析和机器学习来确定ALA在AMD中的潜在分子靶点。通过构建相互作用网络、功能富集分析和基于机器学习的筛选来确定核心基因。进行分子对接和分子动力学模拟以评估ALA与其预测靶点之间的结合亲和力和稳定性。使用碘酸钠(SI)诱导的AMD小鼠模型进行验证,通过行为测试、组织学染色和qRT-PCR评估视网膜结构、功能、氧化应激和基因表达。
我们确定了ALA在AMD中涉及的六个与铁死亡相关的核心靶点(和)。分子对接显示ALA与这六个靶点之间具有很强的结合亲和力,动态模拟证实了稳定的相互作用,特别是与和。在SI诱导的AMD小鼠模型中,ALA显著保留了视网膜结构,维持了视觉功能,并减少了氧化应激和铁积累。qRT-PCR证实ALA对这六个基因的表达产生了不同的影响,表明存在上下文依赖性调节机制。
本研究提供了多层面证据,表明ALA通过调节铁死亡相关途径以及恢复视网膜结构完整性和功能来预防AMD。这些发现值得进一步研究ALA在AMD中的治疗潜力。