Integrated analysis of the circRNA–miRNA–mRNA regulatory network underlying the therapeutic effects of Jinkui Shenqi Wan, a traditional Chinese medicine formula, in diabetic kidney disease: A network pharmacology and bioinformatics study

Jinkui Shenqi Wan (JKSQW) is a classical traditional Chinese medicine (TCM) formula used for diabetic kidney disease (DKD), but its molecular mechanisms remain incompletely defined. While non-coding RNAs (ncRNAs) are increasingly recognized as key regulators in DKD, their role in the therapeutic action of JKSQW has not been systematically explored. Accordingly, we aimed to elucidate the potential mechanisms of JKSQW in DKD by integrating a circRNA-miRNA-mRNA regulatory network into a network pharmacology framework. Bioactive constituents and putative targets of JKSQW were retrieved from TCMSP and STITCH and mapped to UniProt. DKD-related differentially expressed mRNAs (DEmRNAs) were obtained from GEO (GSE1009; GPL16791) and analyzed using DESeq2 (Benjamini-Hochberg adjusted P < .05; |log2FC| > 2). circRNA-miRNA interactions were predicted using miRcode and cross-checked with starBase when available; miRNA-mRNA interactions were integrated from miRDB, miRTarBase, and TargetScan, retaining pairs supported by ≥ 2 resources or validated entries. Overlapping drug-disease targets underwent STRING-based protein-protein interaction (PPI) analysis, GO/KEGG enrichment with clusterProfiler, and molecular docking (AutoDock Vina). Docked complexes were visualized in PyMOL and annotated with PLIP. Fifty constituents mapped to 218 targets; 543 DEmRNAs were identified in DKD, with 20 overlapping genes considered potential therapeutic targets. PPI analysis highlighted hubs HTR2A, EGFR, TOP2A, CDK1, and MYC. Integration of ncRNA predictions yielded a circRNA-miRNA-mRNA network comprising 50 circRNAs, 32 miRNAs, and 20 mRNAs, revealing axes such as circ_0000962-miR‑15a‑5p-CDK1. Enrichment implicated p53 and AGE-RAGE signaling in apoptosis, fibrosis, and oxidative stress. Docking showed stigmasterol exhibited favorable affinities with HTR2A (-8.3 kcal/mol), EGFR (-7.6), TOP2A (-7.8), and CDK1 (-8.7). JKSQW may exert multi-component, multi-target protection against DKD by engaging ncRNA-mediated regulation and protein hubs within p53 and AGE-RAGE pathways. These findings provide a modern pharmacological rationale for this TCM formula and a transferable framework for ceRNA-integrated network analyses.

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Journal
Medicine
Published
2026-04-17
DOI
https://doi.org/10.1097/md.0000000000048377
Primary Topic
Circular RNAs in diseases
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article
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article

Integrated analysis of the circRNA–miRNA–mRNA regulatory network underlying the therapeutic effects of Jinkui Shenqi Wan, a traditional Chinese medicine formula, in diabetic kidney disease: A network pharmacology and bioinformatics study

Peiwu Jiang, Qingying Tan, Tianxiao Hu, Jiaqi Yao et al.
Medicine
Circular RNAs in diseases
article

Integrated analysis of the circRNA–miRNA–mRNA regulatory network underlying the therapeutic effects of Jinkui Shenqi Wan, a traditional Chinese medicine formula, in diabetic kidney disease: A network pharmacology and bioinformatics study

Peiwu Jiang, Qingying Tan, Tianxiao Hu, Jiaqi Yao, Yanxia Ren, Yao Xu, Xiujing Wang
article en

Abstract

Jinkui Shenqi Wan (JKSQW) is a classical traditional Chinese medicine (TCM) formula used for diabetic kidney disease (DKD), but its molecular mechanisms remain incompletely defined. While non-coding RNAs (ncRNAs) are increasingly recognized as key regulators in DKD, their role in the therapeutic action of JKSQW has not been systematically explored. Accordingly, we aimed to elucidate the potential mechanisms of JKSQW in DKD by integrating a circRNA-miRNA-mRNA regulatory network into a network pharmacology framework. Bioactive constituents and putative targets of JKSQW were retrieved from TCMSP and STITCH and mapped to UniProt. DKD-related differentially expressed mRNAs (DEmRNAs) were obtained from GEO (GSE1009; GPL16791) and analyzed using DESeq2 (Benjamini-Hochberg adjusted P < .05; |log2FC| > 2). circRNA-miRNA interactions were predicted using miRcode and cross-checked with starBase when available; miRNA-mRNA interactions were integrated from miRDB, miRTarBase, and TargetScan, retaining pairs supported by ≥ 2 resources or validated entries. Overlapping drug-disease targets underwent STRING-based protein-protein interaction (PPI) analysis, GO/KEGG enrichment with clusterProfiler, and molecular docking (AutoDock Vina). Docked complexes were visualized in PyMOL and annotated with PLIP. Fifty constituents mapped to 218 targets; 543 DEmRNAs were identified in DKD, with 20 overlapping genes considered potential therapeutic targets. PPI analysis highlighted hubs HTR2A, EGFR, TOP2A, CDK1, and MYC. Integration of ncRNA predictions yielded a circRNA-miRNA-mRNA network comprising 50 circRNAs, 32 miRNAs, and 20 mRNAs, revealing axes such as circ_0000962-miR‑15a‑5p-CDK1. Enrichment implicated p53 and AGE-RAGE signaling in apoptosis, fibrosis, and oxidative stress. Docking showed stigmasterol exhibited favorable affinities with HTR2A (-8.3 kcal/mol), EGFR (-7.6), TOP2A (-7.8), and CDK1 (-8.7). JKSQW may exert multi-component, multi-target protection against DKD by engaging ncRNA-mediated regulation and protein hubs within p53 and AGE-RAGE pathways. These findings provide a modern pharmacological rationale for this TCM formula and a transferable framework for ceRNA-integrated network analyses.

MedicineVol. 105(16)
Zhejiang Chinese Medical University (CN), 117th Hospital of People's Liberation Army (CN)
Good health and well-being
Openalex Percentile: Top 19%
Circular RNAs in diseases
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