Bekanamycin Sulfate

Acetaminophen (APAP) can induce liver injury and even acute liver failure (ALF) or death when administered in overdose. Current treatments may be associated with significant adverse effects, so it is urgent to explore other safe and effective alternative therapeutic drugs. Artemisia keiskeana Miq. (AKM), a traditional Chinese medicine, is frequently employed in clinical settings for the management of liver-related disorders. To date, no studies have been reported regarding the pharmacological effects of AKM on APAP-induced liver injury and its underlying mechanisms of action. This study is designed to investigate this unexplored area for the first time, thereby addressing the current scientific gap in this domain.

This study aims to systematically investigate the potential of AKM to alleviate APAP-induced liver injury and elucidate its underlying mechanisms.

Mice were pre-treated with AKM via intragastric administration and subsequently injected with APAP to establish a liver injury model. The liver-to-body weight ratio was measured, and biochemical markers associated with liver injury as well as pathological alterations in liver tissues were analyzed. Quantitative proteomics, Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and network pharmacology were employed to identify differentially expressed proteins, chemical constituents, and potential targets, followed by intersection analysis to determine core targets. Oxidative stress-related parameters in liver tissues were quantified using enzyme-linked immunosorbent assay (ELISA) kits. To further explore the hepatoprotective effects of AKM and its association with ferroptosis, the ferroptosis inhibitor Ferrostatin-1 (Fer-1) was utilized in conjunction with the MTT assay and C11 BODIPY 581/591 fluorescence staining to perform functional validation. Furthermore, the direct binding ability between AKM and core target proteins was verified through surface plasmon resonance (SPR) experiments. Finally, Western blot analysis was conducted to assess the effects of AKM on the ESR1/Nrf2/GPX4 signaling pathway and the expression levels of NF-κB and NLRP3 proteins.

AKM significantly alleviated liver tissue stasis and edema, reduced the liver-to-body weight ratio, markedly decreased serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (p < 0.05), and mitigated pathological alterations including inflammatory infiltration, fibrosis, and apoptosis, in mice with APAP-induced liver injury. By integrating quantitative proteomics, UPLC-MS/MS, and network pharmacology, we identified an important overlapping target, estrogen receptor alpha (ESR1). Additionally, the differentially expressed proteins were predominantly associated with oxidative stress pathways. Further investigations revealed that AKM significantly enhanced the levels of antioxidant enzymes GSH-PX and SOD in liver tissue (p < 0.001), while reducing the levels of MDA, ROS, IL-1β, IL-6 and TNF-α (p < 0.001). Co-treatment with the ferroptosis inhibitor Fer-1 and AKM was found to significantly improve the viability and lipid peroxidation status of LX-2 cells (p < 0.001). SPR experiments further confirmed a direct interaction between AKM and the ESR1 protein (KD = 3.57E-03M). Western-blot showed that AKM promoted the expression of ESR1, Nrf2, and GPX4 proteins while inhibiting the expression of Keap-1, HO-1, NLRP3, NF-κB, and 5-LOX proteins (p < 0.001).

This study provides the first evidence that AKM, as a potential natural therapeutic agent, effectively alleviates APAP-induced liver injury. Its mechanism of action is likely associated with the activation of the Nrf2/GPX4 pathway and the suppression of the NF-κB signaling pathway mediated by ESR1.

The simultaneous identification of proteins as well as their conformations in a biological system would greatly enhance our understanding of cellular mechanisms and disease. As an emerging technique, native proteomics analyzes proteins in their native states, facilitating the acquisition of protein stoichiometry, post-translational modifications (PTMs), and interactions with ligands. However, revealing protein conformations at the proteome scale remains a significant challenge. In this study, we propose an AI-assisted native proteomics method that integrates a protein structure prediction (PSP) module with top-down proteomics (TDP) and native mass spectrometry (nMS) to acquire both proteome identities and conformations. First, protein sequences are obtained using the TDP method, while the protein solvent-accessible surface area is measured by nMS. These data are integrated with the PSP module to acquire protein conformations under experimental conditions. This approach was applied to delineate the conformations of ribosomal proteins pre- and post-assembly. Results revealed that most ribosomal proteins with intrinsically disordered regions exhibit multiple conformational ensembles in the monomer state. Protein-drug interaction (PDI) experiments show that the preferred conformation during binding events may differ from its conformation within the complex, highlighting the importance of acquiring protein "dark" conformations during drug development. By enabling high-throughput proteome identification and conformational characterization, this method bridges the gap between structural biology and conventional proteomics technologies.