Evidence map›Paper›PMID 39208245›Full record

ArticlePloS one2024

Unveiling the anti-obesity potential of Kemuning (Murraya paniculata): A network pharmacology approach.

Rizka Fatriani, Firda Agustin Kartika Pratiwi, Annisa Annisa, Dewi Anggraini Septaningsih, Sandra Arifin Aziz, Isnatin Miladiyah, Siska Andrina Kusumastuti, Mochammad Arfin Fardiansyah Nasution, Donny Ramadhan, Wisnu Ananta Kusuma

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. AFoods (Basel, Switzerland) · 2026
    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

10 authors.

Rizka FatrianiTropical Biopharmaca Research Center, IPB University, Bogor, Indonesia.ORCID 0000-0002-1739-8698
Firda Agustin Kartika PratiwiDepartment of Computer Science, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia.
Annisa AnnisaDepartment of Computer Science, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia.
Dewi Anggraini SeptaningsihDepartment of Chemistry, Faculty of Military Mathematics and Natural Sciences, Republic of Indonesia Defense University, Bogor, Indonesia.
Sandra Arifin AzizDepartment of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor, Indonesia.
Isnatin MiladiyahFaculty of Medicine, Islamic University of Indonesia, Indonesia.
Siska Andrina KusumastutiResearch Center for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), Bogor, Indonesia.
Mochammad Arfin Fardiansyah NasutionDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia.ORCID 0000-0001-5243-8969
Donny RamadhanResearch Center for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), Bogor, Indonesia.
Wisnu Ananta KusumaTropical Biopharmaca Research Center, IPB University, Bogor, Indonesia.ORCID 0000-0002-3682-244X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity has become a global issue that affects the emergence of various chronic diseases such as diabetes mellitus, dysplasia, heart disorders, and cancer. In this study, an integration method was developed between the metabolite profile of the active compound of Murraya paniculata and the exploration of the targeting mechanism of adipose tissue using network pharmacology, molecular docking, molecular dynamics simulation, and in vitro tests. Network pharmacology results obtained with the skyline query technique using a block-nested loop (BNL) showed that histone acetyltransferase p300 (EP300), peroxisome proliferator-activated receptor gamma (PPARG), and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A) are potential targets for treating obesity. Enrichment analysis of these three proteins revealed their association with obesity, thermogenesis, energy metabolism, adipocytokines, fat cell differentiation, and glucose homeostasis. Metabolite profiling of M. paniculata leaves revealed sixteen active compounds, ten of which were selected for molecular docking based on drug-likeness and ADME results. Molecular docking results between PPARG and EP300 with the ten active compounds showed a binding affinity value of ≤ -5.0 kcal/mol in all dockings, indicating strong binding. The stability of the protein-ligand complex resulting from docking was examined using molecular dynamics simulations, and we observed the best average root mean square deviation (RMSD) of 0.99 Å for PPARG with trans-3-indoleacrylic acid, which was lower than with the native ligand BRL (2.02 Å). Furthermore, the RMSD was 2.70 Å for EP300 and the native ligand 99E, and the lowest RMSD with the ligand (1R,9S)-5-[(E)-2-(4-Chlorophenyl)vinyl]-11-(5-pyrimidinylcarbonyl)-7,11-diazatricyclo[7.3.1.02,7]trideca-2,4-dien-6-one was 3.33 Å. The in vitro tests to validate the potential of M. paniculata in treating obesity showed that there was a significant decrease in PPARG and EP300 gene expressions in 3T3-L1 mature adipocytes treated with M. paniculata ethanolic extract starting at concentrations 62.5 μg/ml and 15.625 μg/ml, respectively. These results indicate that M. paniculata can potentially treat obesity by disrupting adipocyte maturation and influencing intracellular lipid metabolism.

Indexed as

Molecular Docking SimulationMolecular Dynamics SimulationMurrayaPlant Extracts3T3-L1 CellsAnimalsAnti-Obesity AgentsE1A-Associated p300 ProteinHumansMiceNetwork PharmacologyObesityPPAR gammaAnti-Obesity AgentsE1A-Associated p300 ProteinPlant ExtractsPPAR gamma

Identifiers

PMID39208245
PMCPMC11361609

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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.