Evidence map›Paper›PMID 38077799›Full record

ArticleWorld journal of diabetes2023

Exploring the targets and molecular mechanism of glycyrrhetinic acid against diabetic nephropathy based on network pharmacology and molecular docking.

Fan-Di Meng, Ling Yuan, Duo-Jie Xu, Meng-Ying Che, Shao-Zhang Hou, Dou-Dou Lu, Wen-Jing Liu, Yi Nan

Open access · diamondAbstract read
In one paragraph

Article in World journal of diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 8 citations in OpenAlex.

  1. Comparative Study ofPharmaceuticals (Basel, Switzerland) · 2026
    Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Exploring the toxicological network in diabetic microvascular disease.International journal of surgery (London, England) · 2025
    Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Fan-Di MengTraditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Ling YuanCollege of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Duo-Jie XuTraditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Meng-Ying CheTraditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Shao-Zhang HouNingxia Key Laboratory of Craniocerebral Diseases, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Dou-Dou LuTraditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Wen-Jing LiuKey Laboratory of Ningxia Ethnomedicine Modernization, Ministry of Education, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Yi NanTraditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Ningxia Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic nephropathy (DN) stands as the most prevalent chronic microvascular complication of diabetes mellitus. Approximately 50% of DN patients progress to end-stage renal disease, posing a substantial health burden.

aimTo employ network pharmacology and molecular docking methods to predict the mechanism by which glycyrrhetinic acid (GA) treats DN, subsequently validating these predictions through experimental means.

methodsThe study initially identified GA targets using Pharm Mapper and the TCMSP database. Targets relevant to DN were obtained from the Genecards, OMIM, and TTD databases. The Venny database facilitated the acquisition of intersecting targets between GA and DN. The String database was used to construct a protein interaction network, while DAVID database was used to conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) analysis. Molecular docking experiments were performed using Autodock software with selected proteins. Experimental validation was conducted using renal proximal tubular cells (HK-2) as the study subjects. A hyperglycemic environment was simulated using glucose solution, and the effect of GA on cell viability was assessed through the cell counting kit-8 method. Flow cytometry was employed to detect cell cycle and apoptosis, and protein immunoblot (western blot) was used to measure the expression of proteins of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway and insulin resistance pathway, including insulin receptor (INSR), PI3K, p-PI3K, AKT, p-AKT, and glycogen synthase kinase-3 (GSK3).

resultsA total of 186 intersecting targets between GA and DN were identified, which were associated with 144 KEGG-related enrichment pathways, 375 GO biological process entries, 45 GO cellular component entries, and 112 GO cellular function entries. Molecular docking demonstrated strong binding of GA to mitogen-activated protein kinase (MAPK)-1, SRC, PIK3R1, HSP90AA1, CASPASE9, HARS, KRAS, and MAPK14.

conclusionGA may protect renal intrinsic cells by modulating the PI3K/AKT signaling pathway, thereby inhibiting HK-2 cell viability, reducing HK-2 cell apoptosis, and inducing cell cycle arrest at the G0/G1 phase.

Indexed as

Diabetic nephropathyGlycyrrhetinic acidMechanism of actionMolecular dockingNetwork pharmacology

Identifiers

PMID38077799
PMCPMC10704203
OpenAlexW4388649059

What OpenQuestion holds

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Registered trials

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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.