Evidence map›Paper›PMID 39925462›Full record

ArticleIn silico pharmacology2025

Network pharmacology and in silico approach to study the mechanism of quercetin against breast cancer.

Tejveer Singh, Mahi Rastogi, Kulbhushan Thakur

Abstract read
In one paragraph

Article in In silico pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

3 authors.

Tejveer SinghTranslational Oncology Laboratory, Department of Zoology, Hansraj College, Delhi University, New Delhi, 110007 India.
Mahi RastogiAmity Institute of Biotechnology, Amity University Madhya Pradesh, Gwalior, Madhya Pradesh 474011 India.
Kulbhushan ThakurTranslational Oncology Laboratory, Department of Zoology, Hansraj College, Delhi University, New Delhi, 110007 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is a significant health concern among females with an estimated 2.3 million cases reported worldwide in 2022. Traditional treatment methods have now developed resistance and various adverse effects, highlighting an urgent need for attention. Therefore, it is advisable to substitute these conventional therapies with innovative medications. Quercetin is a flavonoid, commonly found in various vegetables and fruits and have been shown to possess anti-cancer properties. Network pharmacology is a comprehensive approach that has significantly assisted in investigating the potential of quercetin as a therapeutic option for breast cancer. The first step includes target fishing for quercetin-targeted genes in breast cancer through various online available databases. All intersecting genes were analysed for the phenotypic- genotypic correlation via online VarElect analysis tool. Using the result from the result the GO enrichment and pathway enrichment analysis was done on 52 common genes; followed by PPI network construction and based on topological parameters top 8 genes were filtered. Based on theVenny2.1 and then GEPIA and HPA analysis the key target were identifies as ABCC1, ABCC4, AKT1, ABCB1, CYP1B1, CYP19A1, ABCB4 and ABCG2. Further, Molecular docking was done to investigate the possible interaction of the identified gene with quercetin. Our finding shows quercetin is the potential natural drug that can treat breast cancer effectively. Quercetin interacts with ABCC1, ABCC4, AKT1, ABCB1, CYP1B1, CYP19A1, ABCB4, and ABCG2 at cellular as well as molecular level. The ADMET analysis suggests the bioavaibility of quercetin is around 0.55. Suggesting that quercetin satisfies drug-likeness rules but may face challenges like low bioavailability, which can be enhanced through structural modifications or formulations (e.g., nanoparticles). The molecular docking result assures the interaction of quercetin with the ABCC1, ABCC4, AKT1, ABCB1, CYP1B1, CYP19A1, ABCB4, and ABCG2 with the binding affinity of - 7.2, - 10.1, - 10.4, - 8.0, - 8.2, - 8.2, - 9.0 and - 8.9 respectively. These results suggest quercetin has a stable interaction with the ABCC4 gene. Considering this interaction the quercetin molecules can rescue the cellular condition by inducing apoptosis, inhibiting proliferation, and suppressing metastasis. Quercetin, a natural compound found in fruits and vegetables, has been found to have significant therapeutic roles in treating breast cancer. It inhibits cell cycle arrest, promotes apoptosis, and reduces blood vessel formation. It also reverses drug resistance and has antioxidant and anti-inflammatory properties. This study concludes that the therapeutic influence of quercetin plays a significant role in treating breast cancer and aids in the advancement of the clinical application of quercetin in future studies. Graphical Abstract:

Indexed as

Breast cancerIn silico analysisMolecular dockingNetwork pharmacologyQuercetin

Identifiers

PMID39925462
PMCPMC11802979

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