Evidence mapPaperPMID 34480296Full record

ArticleDaru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences2021

Repurposing new drug candidates and identifying crucial molecules underlying PCOS Pathogenesis Based On Bioinformatics Analysis.

Zeinab Dehghan, Samira Mohammadi-Yeganeh, Marzieh Sameni, Seyed Amir Mirmotalebisohi, Hakimeh Zali, Mohammad Salehi

Open access · bronzeAbstract read
In one paragraph

Article in Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences, 2021. 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
3.1field-weighted citation impact, top 9% 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, 22 citations in OpenAlex.

  1. Expression ofInternational journal of reproductive biomedicine · 2025
    Article
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  4. COVID-19: A novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2023
    Article
  5. Review
  6. Article
  7. Article
  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

6 authors at 1 institution in 1 country.

Zeinab DehghanStudent Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Samira Mohammadi-YeganehCellular & Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Marzieh SameniStudent Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Seyed Amir MirmotalebisohiStudent Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Hakimeh ZaliDepartment of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad SalehiCellular & Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. m.salehi@sbmu.ac.ir.
Shahid Beheshti University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundsPolycystic ovary syndrome affects 7% of women of reproductive ages. Poor-quality oocytes, along with lower cleavage and implantation rates, reduce fertilization.

objectiveThis study aimed to determine crucial molecular mechanisms behind PCOS pathogenesis and repurpose new drug candidates interacting with them. To predict a more in-depth insight, we applied a novel bioinformatics approach to analyze interactions between the drug-related and PCOS proteins in PCOS patients.

methodsThe newest proteomics data was retrieved from 16 proteomics datasets and was used to construct the PCOS PPI network using Cytoscape. The topological network analysis determined hubs and bottlenecks. The MCODE Plugin was used to identify highly connected regions, and the associations between PCOS clusters and drug-related proteins were evaluated using the Chi-squared/Fisher's exact test. The crucial PPI hub-bottlenecks and the shared molecules (between the PCOS clusters and drug-related proteins) were then investigated for their drug-protein interactions with previously US FDA-approved drugs to predict new drug candidates.

resultsThe PI3K/AKT pathway was significantly related to one PCOS subnetwork and most drugs (metformin, letrozole, pioglitazone, and spironolactone); moreover, VEGF, EGF, TGFB1, AGT, AMBP, and RBP4 were identified as the shared proteins between the PCOS subnetwork and the drugs. The shared top biochemical pathways between another PCOS subnetwork and rosiglitazone included metabolic pathways, carbon metabolism, and citrate cycle, while the shared proteins included HSPB1, HSPD1, ACO2, TALDO1, VDAC1, and MDH2. We proposed some new candidate medicines for further PCOS treatment investigations, such as copper and zinc compounds, reteplase, alteplase, gliclazide, Etc.

conclusionSome of the crucial molecules suggested by our model have already been experimentally reported as critical molecules in PCOS pathogenesis. Moreover, some repurposed medications have already shown beneficial effects on infertility treatment. These previous experimental reports confirm our suggestion for investigating our other repurposed drugs (in vitro and in vivo).

Indexed as

Computational BiologyDatabases, ProteinDrug RepositioningFemaleGene Expression RegulationHumansLetrozoleMetforminPhosphatidylinositol 3-KinasesPioglitazonePolycystic Ovary SyndromeProtein Interaction MapsProteomicsProto-Oncogene Proteins c-aktSignal TransductionSpironolactoneLetrozoleMetforminPhosphatidylinositol 3-KinasesPioglitazoneProto-Oncogene Proteins c-aktSpironolactoneDrugInfertilityPolycystic Ovary SyndromeProtein–protein interaction networkSystems biology

Identifiers

PMID34480296
PMCPMC8416576
OpenAlexW3197692203

What Socratic holds

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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 Socratic graph.