{"title":"Potential therapeutic role of sex steroids in treating sarcopenia: a network pharmacology and molecular dynamics study.","authors":"Xiangyu Cui, Xiaodong Li, Xin Qi, Dawang Wang, Boyuan Kang, FengJiu Li, Xilin Xu","doi":"10.1186/s40360-025-00978-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Sarcopenia, characterized by progressive muscle loss and functional decline in aging, poses significant health challenges. Sex steroids, such as estradiol and testosterone, have potential therapeutic roles in mitigating muscle degeneration. This study explores the molecular mechanisms and targets of sex steroids in the treatment of sarcopenia using network pharmacology, enrichment analysis, machine learning, molecular docking, and molecular dynamics simulations.</p><p><strong>Methods: </strong>We identified potential anti-sarcopenia targets by analyzing the interaction network between sex steroids and their targets, intersecting these with differentially expressed genes (DEGs) from the GSE1428. Enrichment analysis was conducted to determine the functional relevance of these targets. Gene set variation analysis (GSVA) was employed to explore pathway-level differences between age groups. Machine learning algorithms (RF, SVM, XGBoost) identified crucial biomarker genes. A nomogram for predicting sarcopenia was constructed and validated. Molecular docking and molecular dynamics (MD) simulations evaluated the binding interactions and stability of steroid-target complexes.</p><p><strong>Results: </strong>Intersection analysis revealed 69 potential anti-sarcopenia targets. Enrichment analysis highlighted pathways related to muscle function, such as calcium signaling and synaptic transmission. GSVA indicated significant upregulation of DNA damage response and immune response pathways in the older group. Machine learning algorithms pinpointed CFTR, FYN, and PRKCA as top biomarkers. The nomogram demonstrated high predictive accuracy with an AUC of 0.925. Molecular docking showed significant binding affinities of sex steroids with target proteins, further supported by stable RMSD values in MD simulations.</p><p><strong>Conclusion: </strong>Sex steroids, specifically estradiol and testosterone, demonstrate promising interactions with key targets implicated in sarcopenia in silico. These computational findings offer preliminary mechanistic insights into the potential therapeutic role of sex steroids in modulating muscle-related pathways. Further experimental and clinical validation is warranted to assess their translational applicability for sarcopenia treatment.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9023,"journal":{"name":"BMC Pharmacology & Toxicology","volume":"26 1","pages":"155"},"PeriodicalIF":2.7000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12403257/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Pharmacology & Toxicology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40360-025-00978-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Sarcopenia, characterized by progressive muscle loss and functional decline in aging, poses significant health challenges. Sex steroids, such as estradiol and testosterone, have potential therapeutic roles in mitigating muscle degeneration. This study explores the molecular mechanisms and targets of sex steroids in the treatment of sarcopenia using network pharmacology, enrichment analysis, machine learning, molecular docking, and molecular dynamics simulations.
Methods: We identified potential anti-sarcopenia targets by analyzing the interaction network between sex steroids and their targets, intersecting these with differentially expressed genes (DEGs) from the GSE1428. Enrichment analysis was conducted to determine the functional relevance of these targets. Gene set variation analysis (GSVA) was employed to explore pathway-level differences between age groups. Machine learning algorithms (RF, SVM, XGBoost) identified crucial biomarker genes. A nomogram for predicting sarcopenia was constructed and validated. Molecular docking and molecular dynamics (MD) simulations evaluated the binding interactions and stability of steroid-target complexes.
Results: Intersection analysis revealed 69 potential anti-sarcopenia targets. Enrichment analysis highlighted pathways related to muscle function, such as calcium signaling and synaptic transmission. GSVA indicated significant upregulation of DNA damage response and immune response pathways in the older group. Machine learning algorithms pinpointed CFTR, FYN, and PRKCA as top biomarkers. The nomogram demonstrated high predictive accuracy with an AUC of 0.925. Molecular docking showed significant binding affinities of sex steroids with target proteins, further supported by stable RMSD values in MD simulations.
Conclusion: Sex steroids, specifically estradiol and testosterone, demonstrate promising interactions with key targets implicated in sarcopenia in silico. These computational findings offer preliminary mechanistic insights into the potential therapeutic role of sex steroids in modulating muscle-related pathways. Further experimental and clinical validation is warranted to assess their translational applicability for sarcopenia treatment.
期刊介绍:
BMC Pharmacology and Toxicology is an open access, peer-reviewed journal that considers articles on all aspects of chemically defined therapeutic and toxic agents. The journal welcomes submissions from all fields of experimental and clinical pharmacology including clinical trials and toxicology.