Active Constituent of HQS in T2DM Intervention: Efficacy and Mechanistic Insights

Abstract

Traditional Chinese Medicine (TCM) is recognized for its complex composition and multiple therapeutic targets. Current pharmacological research often concentrates on extracts or individual components. The former approach faces numerous challenges, whereas the latter oversimplifies and disregards the synergistic effects of TCM components. This study aimed to address this limitation by evaluating the therapeutic efficacy and mechanisms of Huang-Qi San (HQS) active constituent (AC) against type 2 diabetes (T2DM). Active components of HQS were identified using network pharmacology and spectrum-effect correlation analysis. The reconstituted AC group was assessed both in vitro (for glucose consumption and glycogen synthesis) and in vivo (in T2DM mice), with metabolomics and molecular docking techniques used to elucidate the underlying mechanisms. Eight components exhibiting a correlation degree greater than 0.85 were identified as the representative components of HQS intervention for T2DM. These eight components were then mixed in equal proportions to produce AC. The AC group demonstrated increased glucose uptake and glycogen synthesis in vitro, surpassing both the HQS extract and individual components. In diabetic mice, AC significantly increased the insulin sensitivity, outperforming the HQS extract and matching the efficacy of metformin. Metabolomics analysis identified pentose and glucuronic acid interconversion as a critical metabolic pathway, with strong binding affinity (less than -15 kJ/mol) between AC and key enzymes. This research further substantiates the scientific validity and feasibility of emphasizing active constituents in the evaluation of TCM efficacy. Additionally, it provides a scientific foundation for the clinical application of HQS. Most importantly, this study serves as a demonstration of the development of new TCM drugs characterized by clear ingredients, safety, and effectiveness.

Keywords: Huang-Qi San; active constituent; potential pharmacodynamic ingredients; type 2 diabetes.

Figure 1

(A) The common targets of HQS together with the differentially expressed genes related to T2DM; (B) the network of compounds and targets; (C) the PPI network encompassing genes associated with the treatment of T2DM using HQS.

Figure 2

Outcomes of spectrum–effect correlation analysis. (A) A total ion chromatogram showcasing blood components extracted from HQS in rat models; (B) a heat map illustrating correlations between HQS blood components and serum biomarkers; (C) the relationship between HQS components and the overall evaluation metric, with the red line representing a relevancy value of 0.85.

Figure 3

(A) Chromatogram of HQS extract. (B) Chromatogram of the standard substance; 1–8 are, respectively, Puerarin, Scopoletin, Moracin A, Tiliroside, Kaempferol, Formononetin, Astragaloside IV, and Astragaloside III.

Figure 4

Cell viability of IR-HepG2 cells induced by INS. Astragaloside IV (A), Astragaloside III (B), Kaempferol (C), Tiliroside (D), Formononetin (E), Scopoletin (F), Moracin A (G), Puerarin (H), HQS extract (I), and AC (J).

Figure 5

Beneficial effect curve in IR-HepG2 cells. Astragaloside IV (A), Astragaloside III (B), Kaempferol (C), Tiliroside (D), Formononetin (E), Scopoletin (F), Moracin A (G), Puerarin (H), HQS extract (I), and AC (J); effect of HQS on glucose consumption (K) and glycogen levels (L). In comparison to the control group, ^## p < 0.01; when compared to the model group, * p < 0.05, ** p < 0.01.

Figure 6

The hypoglycemic effects of the HQS extract and AC were evaluated in mice induced with T2DM using STZ. Over a duration of 8 weeks, the researchers monitored several parameters related to the mice’s health. Food intake (A), water intake (B), FBG levels (C), and the results of OGTT (D,E). In comparison to the control group, ^## p < 0.01; when contrasted with the model group, * p < 0.05, ** p < 0.01.

Figure 7

The effect of HQS on insulin sensitivity in T2DM mice. (A) Serum INS levels; (B) HOMA-IR; (C) HOMA-β; (D) curve of ITT; (E) AUC of ITT. In comparison to the control group, ^## p < 0.01; when contrasted with the model group, ** p < 0.01.

Figure 8

Enhancement of HQS extract and the AC on biochemical markers in mice T2DM. The levels of serum T-CHO (A), TG (B), LDL-C (C), HDL-C (D) GHb (E) and KB (F) in mice. Relative to the control group, ^## p < 0.01; when compared to the model group, * p < 0.05, ** p < 0.01.

Figure 9

Histological evaluation of the effects of HQS extract and active constituent on liver and pancreas tissues in STZ-induced T2DM mice. In the results of H&E staining (A) and PAS staining (B) of the liver (magnification, ×400), as well as H&E staining of the pancreas (C) (magnification, ×100), a–g represent the control group, model group, Metformin (Met) group, HQS group, and AC groups (50, 100, 200 mg/kg).

Figure 10

Analysis using multivariate statistics. (A) PCA score plots; (B) PLS-DA score plots. Distribution of samples across various groups in OPLS-DA mode: (C) Control vs. Model in negative ion mode; (D) Model vs. HQS in negative ion mode. Variation demonstrated in volcano plots: (E) Control vs. Model; (F) Model vs. HQS. Note: The horizontal axis represents change multiples, while the vertical axis indicates p-values from t-tests.

Figure 11

(A) Venn diagram showing the overlapping metabolites; (B) the heatmap displaying the clustering of differential metabolite levels. Red denotes an increase in metabolite levels, while blue signifies a decrease in metabolite levels.

Figure 12

Bubble diagram illustrating the analysis of differential metabolite pathways in rat serum: (A) Control vs. Model; (B) Model vs. HQS; (C) comparison between (A) and (B). Each point denotes a specific metabolic pathway; the size of the dot and its color intensity are positively associated with the significance of the metabolic pathway. (D) Analysis of metabolic pathways. The metabolites highlighted in yellow are the potential biomarkers identified in this study.

Figure 13

Molecular docking of 8 representative compounds of HQS with UGT1A1 (A), UGT1A9 (B), UGT2B10 (C), and UGT2B15 (D). (a) Puerarin, (b) Scopoletin, (c) Tiliroside, (d) Formononetin, (e) Kaempferol, (f) Moracin A, (g) Astragaloside IV, and (h) Astragaloside III. The compounds under investigation are represented in cyan, while the adjacent residues within the binding pockets are shown in green. Additionally, the receptor’s backbone is illustrated as a slate-colored cartoon.