This protocol aims to explore the mechanism by which QUF3 improves endometrial receptivity in PCOS using network pharmacology, docking, and MD simulation.
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Research Article
* These authors contributed equally
This protocol aims to explore the mechanism by which QUF3 improves endometrial receptivity in PCOS using network pharmacology, docking, and MD simulation.
Impaired endometrial receptivity is a major cause of infertility in polycystic ovary syndrome (PCOS). Qu's Formula 3 (QUF3) is a Chinese herbal medicine formula clinically used to improve endometrial receptivity in patients with PCOS. This study employed network pharmacology, molecular docking, and molecular dynamics (MD) simulations to investigate the underlying mechanisms. Active constituents of QUF3 were identified using the TCMSP database, and potential targets related to endometrial receptivity and PCOS were retrieved from DrugBank and other resources. A compound-target interaction network and a protein-protein interaction (PPI) network were constructed via Cytoscape to identify key targets. Core targets were subjected to GO and KEGG enrichment analyses. Molecular docking, MD simulations, principal component analysis (PCA), free energy landscape (FEL), and dynamic cross-correlation matrix (DCCM) were used to evaluate binding interactions. From 91 active ingredients and 294 potential drug targets, 60 disease-related targets were identified. Luteolin and sesamin were among the key pharmacodynamic components. Ten core targets were identified: AKT1, EGFR, TNF, TP53, IL6, BCL2, ESR1, IL1B, STAT3, and MMP9. KEGG enrichment revealed 132 signaling pathways, and GO analysis identified 678 entries. MD simulations indicated that the binding between the top five active constituents and their respective targets was stable. PCA, FEL, and DCCM further demonstrated high thermodynamic stability and structural rigidity of these complexes. In conclusion, QUF3 improves endometrial receptivity in PCOS through multicomponent, multitarget, and multipathway interactions. This study provides a theoretical basis, from a computational simulation perspective, for the development of targeted Chinese herbal medicine therapies for PCOS-related infertility, and may have positive implications for improving pregnancy outcomes in women with PCOS in the future.
Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women1. Its main characteristics include chronic persistent ovulatory dysfunction, clinical or biochemical hyperandrogenemia, and polycystic ovarian morphology, with clinical manifestations such as amenorrhea, infertility, hirsutism, acne, and obesity. In recent years, advances in ovulation induction and assisted reproductive technology (ART) have significantly improved pregnancy rates in PCOS patients; however, pregnancy outcomes remain poorer than those in healthy women2,3. Endometrial receptivity is a k....
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Screening of active constituents and potential targets of QUF3
The active chemical components of Baishao, Shudihuang, Tusizi, Nvzhenzi, Sangjisheng, Danshen, and Shanzhuyu in the medication QUF3 were identified using the TCMSP on April 1, 202510. The active ingredients were preliminarily screened based on the conditions of oral bioavailability (OB) ≥30% and drug-likeness (DL) ≥ 0.1811. These thresholds were chosen as standard empirical criteria to ensure sufficient absorption and drug-like properties. The canonical SMILES sequence of each compound was searched in the PubChem database, and the resulti....
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Screening of active constituents and potential targets of QUF3
Using OB ≥ 30% and DL ≥ 0.18 as screening criteria, after searching the TCMSP database, QUF3 identified 126 chemical components. Among these, Paeoniae Radix Alba (Baishao) contained 13 active constituents, Rehmanniae Radix Praeparata (Shudihuang) contained 2, Cuscutae Semen (Tusizi) contained 13, Fructus Ligustri Lucidi (Nvzhenzi) contained 13, Herba Taxilli (Sangjisheng) contained 2, Radix Salviae (Danshen) contained 65, Cornus Officinal.......
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There is growing evidence that the endometrium of patients with PCOS exhibits impaired function, which may correlate with higher rates of implantation failure and adverse pregnancy outcomes40. Endometrial differences in women with PCOS are mainly characterized by decreased expression of pinopodes, nucleolar channel systems, estrogen receptors, and progesterone receptors during the window of implantation (WOI)41. Moreover, the expressions of homeobox A10 (HOXA-10), homeobox .......
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No conflict of interest exists in the submission of this manuscript, and the manuscript is approved by all authors for publication.
The authors declare that there are no additional acknowledgments to report for this study.
FUNDING: Zhejiang Provincial Natural Science Foundation of China (No. LZ26H270001 to F.Q.); National Natural Science Foundation of China (No.82575119 to F.Q.); the Health High-Level Talent Training Project, the Health Commission of Zhejiang Province, China (Grant no. [2021] 40 to F.Q.).
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| Name | Company | Catalog Number | Comments |
|---|---|---|---|
| Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (Version 2.3) | Lab of Systems Pharmacology | https://www.tcmsp-e.com/load_intro.php?id=43 | Database for screening of active components |
| Swiss Target Prediction online database (2019 version) | Molecular Modelling Group, University of Lausanne & SIB Swiss Institute of Bioinformatics | http://www.swisstargetprediction.ch/ | Online target prediction database |
| PubChem database | National Library of Medicine, NIH | https://pubchem.ncbi.nlm.nih.gov/ | Chemical database for compound SMILES/SDF retrieval |
| UniProt database | NIH | https://www.uniprot.org/uniprotkb | Protein database for UniProt IDs and gene names |
| Online Mendelian Inheritance in Man (OMIM) | Johns Hopkins University | https://www.omim.org/ | Disease target database |
| DrugBank | University of Alberta | https://www.drugbank.ca/ | Disease target database |
| Therapeutic Target Database (TTD) | Zhejiang University | https://ttd.idrblab.cn/ | Disease target database |
| GeneCards (Version 5.26) | Weizmann Institute of Science, LifeMap Sciences | https://www.genecards.org/ | Disease target database (relevance score >5) |
| Venny visualization platform (Version 2.1.0) | Centro Nacional de Biotecnología (CNB-CSIC) | https://bioinfogp.cnb.csic.es/tools/venny/ | Online Venn diagram tool for intersection target visualization |
| Cytoscape (Version 3.10.3) | National Resource for Network Biology, NHGRI | https://cytoscape.org/ | Network analysis and visualization software for H-C-T, PPI, and pathway networks |
| STRING database (Version 12.0) | STRING Consortium | https://string-db.org/ | Protein-protein interaction database for PPI network construction |
| DAVID database (Version v2025-2) | U.S. Department of Health & Human Services, NIH | https://davidbioinformatics.nih.gov/ | Gene enrichment analysis database for GO and KEGG |
| AutoDockTools (Version 1.5.7) | The Scripps Research Institute | https://autodock.scripps.edu/ | Molecular docking software for preprocessing and calculation |
| PyMOL software (Version 3.0.3) | Schrödinger | https://pymol.org/ | Molecular visualization software for docking visualization |
| Protein Data Bank (PDB) | RCSB | https://www.rcsb.org/ | Protein structure database for downloading target PDB files |
| GROMACS (Version 2023.2) | GROMACS development team | https://www.gromacs.org/ | Molecular dynamics simulation software |
| VMD (Version 1.9.3) | University of Illinois | https://www.ks.uiuc.edu/Research/vmd/ | Molecular visualization and trajectory analysis software |
| gmx_MMPBSA | Open-source (GitHub) | https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA | Binding free energy calculation tool from MD trajectories |
| Science Data Bank | Chinese Academy of Sciences, Computer Network Information Center | https://www.scidb.cn/ | Scientific data repository for data availability and deposition |