Evidence map›Paper›PMID 33116398›Full record

ArticleDrug design, development and therapy2020

Integrated Network Pharmacology Analysis and Experimental Validation to Reveal the Mechanism of Anti-Insulin Resistance Effects of

Qiong Huang, Rong Liu, Jing Liu, Qi Huang, Shao Liu, Yueping Jiang

Open access · goldAbstract readValidation Study
In one paragraph

Article in Drug design, development and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.9field-weighted citation impact, top 5% 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

14 citing papers in PubMed, 36 citations in OpenAlex.

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  10. Frontiers in immunology · 2022
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  11. Study on the Multitarget Mechanism and Active Compounds of Essential Oil fromEvidence-based complementary and alternative medicine : eCAM · 2022
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  12. Review
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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

6 authors at 1 institution in 1 country.

Qiong Huang *Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.
Rong Liu *Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.
Jing LiuDepartment of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.
Qi HuangDepartment of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.
Shao Liu *Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.ORCID 0000-0002-0576-8698
Yueping JiangDepartment of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeInsulin resistance (IR) is one of the factors that results in metabolic syndrome, type 2 diabetes mellitus and different aspects of cardiovascular diseases.

methodsBy incorporating compound screening and target prediction, a feasible compound-target-pathway network pharmacology model was established to systematically predict the potential active components and mechanisms of the anti-IR effects of MOS. Biological methods were then used to verify the results of the network pharmacology analysis.

resultsOur comprehensive systematic approach successfully identified 32 bioactive compounds in MOS and 44 potential targets of these compounds related to IR, as well as 37 potential pathways related to IR. Moreover, the network pharmacology analysis revealed that glycosidic isothiocyanates and glycosidic benzylamines were the major active components that improved IR by acting on key targets, such as SRC, PTPN1, and CASP3, which were involved in inflammatory responses and insulin-related pathways. Further biological research demonstrated that the anti-IR effects of MOS were mediated by increasing glucose uptake and modulating the expression of SRC and PTPN1.

conclusionOur study successfully predicts the active ingredients and potential targets of MOS for improving IR and helps to illustrate mechanism of action at a systemic level. This study not only provides new insights into the chemical basis and pharmacology of MOS but also demonstrates a feasible method for discovering potential drugs from traditional medicines.

Indexed as

Insulin ResistanceBenzylaminesCaco-2 CellsComputational BiologyDatabases, FactualDatabases, GeneticDiabetes Mellitus, Type 2HumansHypoglycemic AgentsInsulinIsothiocyanatesMolecular Docking SimulationMoringa oleiferaPredictive Value of TestsSeedsBenzylaminesHypoglycemic AgentsInsulinIsothiocyanatesaction mechanismactive componentsIRMoringa oleifera seedsnetwork pharmacology

Identifiers

PMID33116398
PMCPMC7539042
OpenAlexW3090647677

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.