Validating the potential mechanism and therapeutic effect of Qinlian Jiangxia decoction (芩连姜夏汤) in the treatment of type 2 diabetes mellitus complicated with hyperlipidemia through network pharmacology, molecular docking, molecular dynamics simulation, and in vivo experiments

doi:10.19852/j.cnki.jtcm.2026.01.012

Abstract

Abstract:

OBJECTIVE: To investigate the mechanism of action of Qinlian Jiangxia decoction (芩连姜夏汤, QLJXD) in the treatment of type 2 diabetes mellitus (T2DM) complicated by hyperlipidemia using network pharmacology, molecular docking, molecular dynamics simulation and in vivo experiments.

METHODS: Drug components, targets and disease targets were identified using databases such as TCM systems pharmacology database and analysis platform and GeneCards. The intersecting targets were subjected to protein-protein interaction analysis using the search tool for the retrieval of interacting genes/proteins database. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersecting targets were conducted using the Metascape platform to identify core components and targets. The results were validated using molecular docking, molecular dynamics simulations and in vivo experiments.

RESULTS: QLJXD contains 76 active ingredients and 136 disease targets. The core ingredients are quercetin, β-sitosterol, wogonin and baicalein, while the core targets are fatty acid binding protein 4 (FABP4) and peroxisome proliferative activated receptor gamma (PPARG). Molecular docking and molecular dynamics simulations revealed that the core ingredients bound well to the core targets. Animal experiments demonstrated that QLJXD effectively inhibited the expression of FABP4 and increased the expression of PPARG, thereby enhancing disorders of glycolipid metabolism.

CONCLUSION: The putative therapeutic efficacy of QLJXD in the management of T2DM complicated with hyperlipidemia may be ascribed to the synergistic actions of multiple components, such as quercetin, β-sitosterol, wogonin, and baicalein, which collectively modulate FABP4 and PPARG molecular targets.

Key words: type 2 diabetes mellitus, hyperlipidemias, molecular docking simulation, molecular dynamics simulation, network pharmacology, Qinlian Jiangxia decoction

REN Zonghao, YUE Rensong. Validating the potential mechanism and therapeutic effect of Qinlian Jiangxia decoction (芩连姜夏汤) in the treatment of type 2 diabetes mellitus complicated with hyperlipidemia through network pharmacology, molecular docking, molecular dynamics simulation, and in vivo experiments[J]. Journal of Traditional Chinese Medicine, 2026, 46(1): 127-137.

Figures/Tables 9

Figure 1 “Traditional Chinese Medicine-Bioactive Components-Treatment Targets-Core Pathways-Disease” network

Table 1 Molecular docking results of key components with key targets

Receptor	Ligand	Binding energy in ADT (kcal/mol)	Hydrogen bond sites in ADT	Hydrogen binding sites in PyMOL	Hydrogen bond length in PyMOL (?)
PPARG	Quercetin	-3.55	THR440	THR440 ALA433 GLN430	2.1 3.0 2.3
	β-sitosterol	-4.51	-	GLU324	1.9
	Wogonin	-4.85	THR241 THR242	THR241 THR242	2.2 2.0/2.0
	Baicalein	-4.86	LYS434	GLN430 LYS434	2.4 1.9
FABP4	Quercetin	-5.86	LEU66 ASP2 ASP47	LEU66 ASP47 GLY46	2.0 1.8/3.3/3.6 2.7
	β-sitosterol	-6.69	-	GLY46	2.7
	Wogonin	-5.34	-	LEU66 ASP47	2.3 2.0/2.6
	Baicalein	-5.27	LEU66	LEU66 ASP47	1.9 2.7

Figure 2 Molecular docking results of PPARG and FABP4 A: the surface and cartoon perspectives of the docking of PPARG; A1: quercetin; A2: wogonin; A3: β-sitosterol; A4: baicalein; B: the surface and cartoon perspectives of the docking of FABP4; B1: quercetin; B2: wogonin; B3: baicalein; B4: β-sitosterol. FABP4: fatty acid-binding protein 4; PDB: Protein Data Bank; PPARG: peroxisome proliferator-activated receptor gamma.

Figure 3 Molecular dynamics simulation results of FABP4 and β-sitosterol A: RMSD results during the docking of FABP4 and β-sitosterol; B: RMSF results during the docking of FABP4 and β-sitosterol. RMSD: root mean square deviation; RMSF: root mean square fluctuation; FABP4: fatty acid-binding protein 4; ns: nanosecond.

Table 2 OGTT blood glucose of rats in each group (mmol/L)

Group	n	0 min	30 min	60 min	90 min	120 min	180 min
NG	6	4.5±0.6	5.9±0.6	6.8±0.6	5.9±0.7	5.1±0.7	4.5±0.6
MG	6	27.6±2.1^a	32.2±1.0^a	32.0±1.8^a	32.0±1.5^a	32.8±1.3^a	31.1±1.9^a
QG	6	13.2±1.4^b	15.2±2.1^b	20.5±2.4^b	19.2±2.0^b	16.8±2.6^b	13.9±1.7^b
PG	6	17.6±2.2^b	14.0±2.0^b	18.7±3.5^b	17.3±2.4^b	16.2±4.2^b	12.3±2.1^b

Table 3 Serum insulin and lipid measurements of the experimental rats

Group	n	INS (ng/mL)	TC (mmol/L)	TG (mmol/L)	LDL-C (mmol/L)	HDL-C (mmol/L)
NG	6	15.70±0.99	0.41±0.09	0.21±0.03	0.28±0.06	0.81±0.07
MG	6	86.34±5.67^a	1.83±0.08^a	1.92±0.13^a	1.66±0.17^a	0.35±0.10^a
QG	6	54.02±4.98^b	1.01±0.17^b	0.66±0.09^b	0.46±0.09^b	0.59±0.08^b
PG	6	25.25±1.98^b	1.14±0.11^b	0.92±0.06^b	0.65±0.09^b	0.49±0.07^c

Figure 4 Oil Red O staining results of perirenal adipose tissue in rats A1: results of perirenal fat oil red o staining in NG rats; A2: results of perirenal fat oil red o staining in MG rats; A3: results of perirenal fat oil red o staining in QG rats; A4: results of perirenal fat oil red o staining in PG rats; B: quantitative analysis of lipid accumulation. NG and MG received normal saline for eight weeks according to body weight. QG received QLJXD for eight weeks according to body weight. PG received metformin for eight weeks according to body weight. NG: normal control group; MG: model group; QG: QLJXD group; PG: positive control group. One-way analysis of variance was used for data statistics in this figure. The data are shown as the mean ± standard deviation (n = 6). aP < 0.01, compared to NG; bP < 0.01, compared to MG.

Table 4 mRNA expression of FABP4 and PPARG in perirenal adipose tissue of rats in each group

Item	NG (n = 6)	MG (n = 6)	QG (n = 6)	PG (n = 6)
FABP4 mRNA	1.00±0.07	8.79±0.32^a	1.75±0.14^b	4.46±0.41^b
PPARG mRNA	1.00±0.10	0.12±0.01^a	0.44±0.03^b	0.21±0.03^b

Table 5 Primer sequences

Gene	Primer	Sequence (5′-3′)
Rat GAPDH	Forward	ACAGCAACAGGGTGGTGGAC
	Reverse	TTTGAGGGTGCAGCGAACTT
Rat FABP4	Forward	TGGCTTTGTCTGTTTCTCCTCTCC
	Reverse	TTCCGCTCCTCCTTCCTCTGG
Rat PPARG	Forward	CCAAGAATACCAAAGTGCGATC
	Reverse	TCACAAGCATGAACTCCATAGT

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