Network pharmacology and metabolomics reveal mathurameha, a Thai traditional Anti-Diabetic formula, enhances glucose metabolism through PI3K-AKT/AMPK/GLUT4 pathway modulation

Abstract

Traditional herbal formulations offer promising avenues for diabetes management by targeting multiple molecular pathways. Mathurameha (MT), a polyherbal preparation, has been historically used for its antidiabetic potential. However, its molecular mechanisms remain largely unexplored. FrE exhibited potent α-glucosidase inhibition (IC₅₀ 0.3 µg/mL) and significantly enhanced glucose uptake in L6 myotubes (3.67 ± 0.23-fold) and 3T3-L1 adipocytes (IC₅₀ 6.78 µg/mL). It also stimulated insulin secretion (1.42-fold), comparable to metformin (1.46-fold), and protected INS-1 pancreatic β-cells from H₂O₂-induced apoptosis (30.65 ± 3.54%) through partial caspase-3 inhibition. LC-MS-QTOF analysis identified 73 metabolites, including ellagic acid, kushenol A, gallic acid, arctiin, neoandrographolide, astilbin, paenol, muricatacin, coumarrayin, and zingerone. Network pharmacology and pathway enrichment analyses revealed key targets (GSK3β, GLUT4, PPARG, INSR, AKT2, CASP3, and MMP9) and highlighted the involvement of PI3K-AKT, AMPK, and GLUT4 signaling pathways. Gene expression analysis confirmed the upregulation of GLUT4, AMPK, IRS, PI3K, and AKT genes in L6 myotubes treated with FrE. These findings suggest that MT exerts antidiabetic effects via the PI3K-AKT/AMPK/GLUT4 signaling axis, promoting glucose uptake, insulin secretion, and β-cell protection. Future studies will focus on in vivo validation, standardization of bioactive fractions, and omics-based approaches to establish a well-defined, effective formulation for diabetes management.

Keywords: Antidiabetic activity; Glucose transport; Insulin secretion enrichment; LC-MS/MS-QTOF analysis; Mathurameha; Network pharmacology; Thai traditional medicine; Twenty-six medicinal plant mixture.

Fig. 1

Experimental Assessment of antidiabetic potential of MT. (a) The effect of MT remedy extracts and fractions on the stimulation of glucose uptake on L6 myotube cells. One-way ANOVA followed by Tukey test; ** P < 0.001 compared with control, ## P < 0.001 compared with metformin. (b) INS-1 pancreatic β-cell viability after treatment with MT remedy extracts and FrE. Apoptosis assay using flow cytometry after staining with annexin V-FITC/propidium iodide (PI). INS-1 cells were treated with 250 µM H₂O₂ for 48 h to induce hypoxic stress mediated apoptosis. The effect of MT extracts and FrE in apoptosis protection on INS-1 cells. (c) Percentage of viable, early apoptotic and late apoptotic cells. (d) Representative scatter plots of PI (y-axis) vs. annexin V(x-axis).

Fig. 2

Metabolite profiling of MT. (a) Total Ion Chromatogram (TIC) of different extracts and FrE (EtOAc fraction of EtOH). (b) Venn diagram analysis of compounds identified by LC-MS/MS different extracts and fractions. (c) Hierarchical clustering of the metabolites from different extracts based on different bioactivities.

Fig. 3

Target Space Analysis and druggability of MT metabolites and targets. (a) Venn diagram of targets with diabetes-associated target space. (b) Radial graph of ADME profile. (c) Target-PPI–disease network showing the interaction between the Target proteins to diabetes and associated targets through protein-protein interaction analysis. (d) Pathway enrichment score plot. (e) Target-pathway network showing the targets in red circles and pathways in light orange sized based on enrichment. The edges represent separate pathways.

Fig. 4

Functional Association Enrichment Analysis of MT targets. (a) Protein-Protein interaction Network of targets related to diabetes interacting with MT molecules the borders in pie format show functional annotation. (b) Network of enriched terms colored by cluster ID, where nodes that share the same cluster ID are typically close to each other (BP), molecular functions (MF), and cellular processes (CC). (c) Network of enriched terms colored by p-value, where terms containing more genes tend to have a more significant p-value. (d) Protein-protein interaction enrichment analysis of MT and MCODE components identified in the gene lists. (e) Gene-functional annotation heatmap.

Fig. 5

MT induces insulin mediated glucose transport related gene expression in L6 myotubes. (a) Gel doc representation of expression of glucose metabolism genes on L6 myotubes after treating with MT extracts, fractions, and metformin at 100 µg/mL showing GLUT4, AMPK, IRS, PI3K and AKT gene expression using GAPDH as the internal control. (b) The relative expression of insulin signalling related genes accessed by image intensity analysis expressed as fold change compared to control. FrE represents the EtOH extract partitioned with EtOAc.

Fig. 6

Pathway Analysis of MT targets associated with T2DM. (a) PI3K-AKT signalling pathway. (b) mTOR signalling pathway. (c) MAP-kinase signalling pathway. (d) Insulin resistance pathway. (e) Diabetic cardiomyopathy (f) AMPK pathway. The red nodes in the pathway represent targets which interact with MT molecules.The KEGG pathway maps were obtained from KEGG database (https://www.kegg.jp/kegg/pathway.html) rendered using Pathview.

Fig. 7

Combination Synergy Network Analysis based on neighbourhood approach. (a) Multi-molecular combination network of compound-target-disease against diabetes. (b) Multi-molecular combination network of compound-target-disease against diabetes with cardiac protection mechanism.