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ABSTRACT: Background
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.Methods
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. In vivo validation was conducted using a sodium iodate (SI)-induce
SUBMITTER: Zhang Y
PROVIDER: S-EPMC12350381 | biostudies-literature | 2025
REPOSITORIES: biostudies-literature