Evidence map›Paper›PMID 41622156›Full record

ArticleBMC complementary medicine and therapies2026

Integrated network pharmacology and bioinformatics analysis reveals MME as key target of Notoginsenoside R1 in diabetic nephropathy.

Xinyu Gan, Mingzhu Liang, Halinuer Shadekejiang, Huan Hong, Jinyu Lu, Xu Li, Xueqin Zhang, Chen Lu

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Article in BMC complementary medicine and therapies, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Xinyu Gan *School of Life Science and Technology, Xinjiang University, Urumqi, Xinjiang, 830046, China.
Mingzhu Liang *Department of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
Halinuer ShadekejiangDepartment of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
Huan HongDepartment of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
Jinyu LuDepartment of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
Xu LiDepartment of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
Xueqin ZhangDepartment of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
Chen LuDepartment of Nephrology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China. luchenxj@163.com.

Funding

Leading Talents in Science and Technology Innovation Project 2022TSYCLJ0022Major Scientific Research Project Cultivation Program of Xinjiang Medical University XYD2024ZX05Xinjiang Uygur Autonomous Region Regional Collaborative Innovation Special Project 2023E01020
6 · The paper itself

Abstract

backgroundDiabetic nephropathy (DN) is a major diabetes complication and a primary cause of end-stage renal failure. Notoginsenoside R1 (NGR1) is known to reduce proteinuria, exert hypoglycemic effects, and enhance renal function in DN patients. However, the exact mechanisms by which NGR1 affects DN are not well understood.

methodsAn integrative approach combining multi-omics bioinformatics and experimental validation was employed. We analyzed GEO datasets (GSE30122, GSE96804) to identify differentially expressed genes and performed WGCNA to define key modules. Network pharmacology predicted NGR1 targets, which were refined via machine learning (LASSO and Random Forest). Immune infiltration was assessed by CIBERSORT. Molecular docking and dynamics simulations evaluated binding interactions. In vitro functional validation used high glucose (HG)-injured MPC5 podocytes, with MME-specific inhibitor (Thiorphan), confirming target necessity.

resultsBioinformatic analysis identified three core targets, MME, PTGS2, and S100A9, within the DN pathological network. Functional enrichment revealed their involvement in oxidative stress detoxification, TGF-β-mediated fibrosis, and AGE-RAGE signaling pathways. Immune infiltration analysis indicated an aberrant increase in M0/M2 macrophages and activated mast cells, alongside a reduction in protective γδ T cells, with core targets showing strong correlations with specific immune subsets. Subsequent molecular docking and dynamics simulations indicated that NGR1 exhibited the strongest binding affinity for MME, among the three targets. Corroborating these findings, in vitro experiments confirmed that NGR1 specifically upregulates MME expression transcriptionally and translationally. Crucially, NGR1 counteracted HG-induced oxidative stress, fibrosis, and inflammation. These protective effects were largely abolished upon MME inhibition, demonstrating MME's essential role in this process.

conclusionThis study suggests that NGR1 may exert renoprotective effects in DN potentially through MME modulation, which appears to mitigate oxidative stress, inflammation, and fibrosis. The findings indicate MME could serve as a promising therapeutic target, providing preliminary mechanistic insights for developing targeted DN therapies.

Indexed as

Diabetic NeuropathiesGinsenosidesNeprilysinPodocytesAnimalsCell LineFibrosisGlucoseInflammationMachine LearningMiceMolecular Docking SimulationMolecular Dynamics SimulationMultiomicsNetwork PharmacologyOxidative StressGinsenosidesGlucoseNeprilysinnotoginsenoside R1ThiorphanBioinformaticsDiabetic nephropathyMMENetwork pharmacologyNotoginsenoside R1

Identifiers

PMID41622156
PMCPMC12955068

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.