Unveiling the common mechanisms and therapeutic targets of medicinal herbs in acute pancreatitis: a network pharmacology and experimental validation approach

Abstract

Background: Acute pancreatitis (AP) is an acute abdominalgia with complicated pathogenesis and high mortality, which is lacking in specific means for clinical diagnosis and treatment. Currently, numerous traditional Chinese medicines have demonstrated remarkable efficacy in AP. Given their multi-target and multi-compound actions, we hypothesize that an underlying common mechanism may contribute to their therapeutic effects. This study aimed to identify key therapeutic targets and potential strategies for AP by investigating the shared pharmacological effects of medicinal plants through network pharmacology analysis and experimental validation.

Methods: We systematically searched the literature for medicinal herbs that have been reported in AP treatment. Next, we utilized the TCMSP database to identify active compounds that were present in at least two medicinal herbs. Key active compounds and targets were determined through Cytoscape analysis and a PPI network, followed by KEGG pathway enrichment analysis. Combined the core targets identified by Cytoscape and the targets enriched in the PI3K/AKT signaling pathway, molecular docking was performed to assess the binding affinity between the intersecting targets and active compounds. Finally, high-affinity compounds were screened, and linarin’s optimal binding profile led to its selection for further in vivo and in vitro experimental validation.

Results: A total of 37 medicinal herbs were retrieved from the literature search. We identified 62 common compounds and 968 targets from medicinal herbs, further taking intersection to 319 targets for anti-AP. Based on this, “compound-target” and “target” networks were constructed, and the top 12 key active compounds and 11 targets were selected. KEGG analysis indicated that the PI3K/AKT pathway might be closely related to pancreatic protection. Molecular docking results showed that linarin exhibited good binding affinity with all core intersecting targets, particularly with AKT1. Subsequently, both in vivo and in vitro experiments demonstrated that linarin could alleviate AP-induced pancreatic damage and systemic inflammation. To further validate the mechanistic involvement of PI3K/AKT signaling pathway, we employed the PI3K/AKT activator 740 Y-P, which was found to effectively reverse linarin-mediated downregulation of PI3K/AKT activation, thereby confirming the crucial role of this pathway in linarin’s protective effects.

Conclusion: Exploring therapeutic strategies based on common mechanisms and targets may be an effective approach. This study revealed that linarin and AKT1 were potential therapeutic compounds and targets for AP in the preclinical stage, which could provide theoretical support and new insights for the drug discovery of AP.

Graphical Abstract:

Supplementary Information: The online version contains supplementary material available at 10.1186/s40643-025-00925-1.

Fig. 1

Targets of medicinal herbs in the treatment of AP. (A) Venn diagram of AP-related targets. (B) Venn diagram of the overlapping targets of medicinal herbs and AP. (C) Screening of core targets through the “target” network

Fig. 2

KEGG enrichment analysis and molecular docking results. (A) KEGG enrichment analysis. (B) Heatmap illustrating the binding affinity between core compounds and key targets as determined by molecular docking. (C) Molecular docking of linarin and 5 core targets

Fig. 3

Effects of linarin on caerulein-induced AP mice and drug safety evaluation. (A) HE staining of pancreatic tissues. (B) Pancreatic tissue pathology score. (C) Serum amylase levels. (D) Serum lipase levels. (E-I) The dosage of 50 mg/kg linarin has no effect on mouse body weight, ALT, AST, BUN, and CREA levels. n = 5. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. AP group

Fig. 4

Effects of linarin on inflammation and apoptosis of caerulein-induced AP mice. (A) Bar graph of the levels of serum IL-1β. (B) Bar graph of the levels of serum IL-6. (C) Bar graph of the levels of serum TNF-α. (D) Immunohistochemical images of MPO and CD68 in the pancreatic tissues. (E) Statistical analysis of MPO expression. (F) Statistical analysis of CD68 expression. (G) TUNEL staining. (H) Statistical analysis of TUNEL-positive cells. n = 5. *P < 0.05, **P < 0.01, ***P < 0.001 vs. AP group

Fig. 5

Linarin attenuated caerulein-induced AP mice via pathways involving PI3K/AKT signaling. (A) Western blots of PI3K/AKT signaling pathway. (B) Relative protein expression of P-PI3K. (C) Relative protein expression of P-AKT. n = 3. *P < 0.05, **P < 0.01, ***P < 0.001 vs. AP group

Fig. 6

Effects of linarin on caerulein-induced AR42J cell. (A) CCK-8 assay of linarin on normal AR42J cells viability. (B) LDH release of linarin on caerulein-induced AR42J cells. (C) Calcein-AM/PI staining images. (D) Bar graph of PI-positive cells. (E-F) The ROS level in the AR42J cells. (G-H) The apoptosis level of the AR42J cells detected by flow cytometry. n = 5. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. AP group or DMSO group

Fig. 7

Effect of linarin on PI3K/AKT signaling in caerulein-induced AR42J cells. (A) Western blots of PI3K/AKT signaling pathway. (B) Relative protein expression of P-PI3K. (C) Relative protein expression of P-AKT. n = 3. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. AP group. ^#P < 0.05, ^##P < 0.01 vs. AP + Linarin group