Abstract
This research evaluated the potential mechanisms of ASX on EIMD. The network pharmacology, machine learning, and transcription sequencing were applied to explore the targets of ASX improving EIMD, which were then validated by molecular dynamics simulation and experiments. Twenty five key targets were screened after topological network analysis and mainly enriched in the Toll-like receptor signaling pathway, NF-κB signaling pathway, and Cytokine-cytokine receptor interaction. Through machine learning algorithms, four candidate targets, including CCL2, NFE2L2, TLR4, and TGFB1, were acquired. Combined with transcriptome sequencing results, CCL2 and TLR4 were finally identified as core targets for ASX to improve EIMD. Molecular dynamics simulation confirmed the strong binding affinity of ASX-CCL2 and ASX-TLR4 complexes. Besides, RT-PCR and Western blot revealed that the mRNA and protein expression of the TLR4/MyD88/NF-κB/CCL2/CCR2 pathway in the EIMD model were significantly down-regulated after ASX intervention. ASX might effectively attenuate muscle damage during exercise through the TLR4/MyD88/NF-κB/CCL2/CCR2 pathway. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10068-026-02086-z.