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Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology

BACKGROUND: S. miltiorrhiza-C. aromatica (Danshen-Yujin; red sage and turmeric) is a frequently used Chinese herbal medicine pair in treating polycystic ovary syndrome (PCOS). This study aimed to classify the molecular targets and mechanisms participating in treating PCOS through network pharmacolog...

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Autores principales: Yu, Hong, Zhang, Lan, Yin, Fei, Zhan, Chaowu, Chen, Jie, Chu, Jijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9951011/
https://www.ncbi.nlm.nih.gov/pubmed/36846000
http://dx.doi.org/10.21037/atm-23-29
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author Yu, Hong
Zhang, Lan
Yin, Fei
Zhan, Chaowu
Chen, Jie
Chu, Jijun
author_facet Yu, Hong
Zhang, Lan
Yin, Fei
Zhan, Chaowu
Chen, Jie
Chu, Jijun
author_sort Yu, Hong
collection PubMed
description BACKGROUND: S. miltiorrhiza-C. aromatica (Danshen-Yujin; red sage and turmeric) is a frequently used Chinese herbal medicine pair in treating polycystic ovary syndrome (PCOS). This study aimed to classify the molecular targets and mechanisms participating in treating PCOS through network pharmacology. METHODS: The Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform was employed for screening the active ingredients of S. miltiorrhiza-C. aromatica. The molecular targets from the UniProt database were identified and compared to the differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) dataset GSE34526; the intersecting genes were obtained by constructing a Venn diagram. Protein-protein interaction (PPI) network construction and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were made on the crossover genes. A key protein 3-dimensional (3D) structure was created using the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCDB PDB) database. Finally, the clinical data of 104 hospital-admitted PCOS patients from January 2018 to December 2020 were retrospectively analyzed to explore and analyze the clinical value of S. miltiorrhiza-C. aromatica in treating PCOS. RESULTS: In the TCMSP database, we found a total of 80 active ingredients in S. miltiorrhiza-C. A high clustering and three key proteins were obtained A high-scoring cluster and 3 key proteins, AOAH, HCK, and C1orf162, were obtained through the construction of protein mutual aid network and module analysis of differential genes. KEGG and GO enrichment analyses indicated that the S. miltiorrhiza-C. aromatica treatment mechanism in PCOS was mainly involved with inflammation-related pathways. The clinical data of PCOS patients were retrospectively analyzed. In the end, The long diameter of the ovary, the thickness of the endometrium, and the antral follicle count in the combined treatment group of S. miltiorrhiza-C. aromatica combined with clomiphene were higher after treatment than before treatment, and the clinical symptoms and hormone levels were also improved. CONCLUSIONS: This study expounds the research value of S. miltiorrhiza-C. aromatica in treating PCOS from the perspectives of active ingredients, targets, signaling pathways, and clinical research. These findings also provide an important reference for treating PCOS with traditional Chinese medicine (TCM).
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spelling pubmed-99510112023-02-25 Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology Yu, Hong Zhang, Lan Yin, Fei Zhan, Chaowu Chen, Jie Chu, Jijun Ann Transl Med Original Article BACKGROUND: S. miltiorrhiza-C. aromatica (Danshen-Yujin; red sage and turmeric) is a frequently used Chinese herbal medicine pair in treating polycystic ovary syndrome (PCOS). This study aimed to classify the molecular targets and mechanisms participating in treating PCOS through network pharmacology. METHODS: The Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform was employed for screening the active ingredients of S. miltiorrhiza-C. aromatica. The molecular targets from the UniProt database were identified and compared to the differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) dataset GSE34526; the intersecting genes were obtained by constructing a Venn diagram. Protein-protein interaction (PPI) network construction and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were made on the crossover genes. A key protein 3-dimensional (3D) structure was created using the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCDB PDB) database. Finally, the clinical data of 104 hospital-admitted PCOS patients from January 2018 to December 2020 were retrospectively analyzed to explore and analyze the clinical value of S. miltiorrhiza-C. aromatica in treating PCOS. RESULTS: In the TCMSP database, we found a total of 80 active ingredients in S. miltiorrhiza-C. A high clustering and three key proteins were obtained A high-scoring cluster and 3 key proteins, AOAH, HCK, and C1orf162, were obtained through the construction of protein mutual aid network and module analysis of differential genes. KEGG and GO enrichment analyses indicated that the S. miltiorrhiza-C. aromatica treatment mechanism in PCOS was mainly involved with inflammation-related pathways. The clinical data of PCOS patients were retrospectively analyzed. In the end, The long diameter of the ovary, the thickness of the endometrium, and the antral follicle count in the combined treatment group of S. miltiorrhiza-C. aromatica combined with clomiphene were higher after treatment than before treatment, and the clinical symptoms and hormone levels were also improved. CONCLUSIONS: This study expounds the research value of S. miltiorrhiza-C. aromatica in treating PCOS from the perspectives of active ingredients, targets, signaling pathways, and clinical research. These findings also provide an important reference for treating PCOS with traditional Chinese medicine (TCM). AME Publishing Company 2023-02-15 2023-02-15 /pmc/articles/PMC9951011/ /pubmed/36846000 http://dx.doi.org/10.21037/atm-23-29 Text en 2023 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Yu, Hong
Zhang, Lan
Yin, Fei
Zhan, Chaowu
Chen, Jie
Chu, Jijun
Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology
title Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology
title_full Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology
title_fullStr Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology
title_full_unstemmed Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology
title_short Exploring the molecular targets and mechanism of S. miltiorrhiza-C. aromatica in treating polycystic ovary syndrome based on network pharmacology
title_sort exploring the molecular targets and mechanism of s. miltiorrhiza-c. aromatica in treating polycystic ovary syndrome based on network pharmacology
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9951011/
https://www.ncbi.nlm.nih.gov/pubmed/36846000
http://dx.doi.org/10.21037/atm-23-29
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