Exploring the Antidepressant Mechanism of Codonopsis pilosula through Network Pharmacology and Molecular Docking Analysis

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The study investigated the antidepressant properties and potential mechanisms of Codonopsis pilosula using network pharmacology and molecular docking. Using TCMSP for plant constituents and GeneCards/OMIM for depression-associated genes, the authors built component–target and protein–protein interaction networks in Cytoscape/STRING, then performed GO and KEGG pathway enrichment with DAVID and validated interactions via Autodock. They identified 18 primary components predicted to affect many targets and 57 signaling pathways, and reported that the key constituent lobetyolin has binding affinity with the pivotal target TP53, based on integrated prior research and docking results. The paper is a Research Square preprint and does not provide explicit experimental caveats beyond its computational/target-prediction framework, limiting confirmation in biological systems. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract Objective To investigate the antidepressant properties and underlying mechanisms of Codonopsis pilosula using network pharmacology and molecular docking analysis. Methods The principal constituents of Codonopsis pilosula were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Genecards and the Online Mendelian Human Inheritance Database (OMIM) were utilized to gather genes associated with depression. Subsequently, Cytoscape software and the STRING database were employed to construct a components-targets network and protein interaction network models for Codonopsis pilosula. The DAVID database was applied for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the targets, while Autodock software was utilized for molecular docking of the primary active compounds of Codonopsis pilosula with its key targets. Results This investigation identified 18 primary components in Codonopsis pilosula, which have the potential to modulate numerous targets and impact 57 signaling pathways. Through integration of prior research findings and molecular docking validation, it was observed that Lobetyolin, the key constituent of Codonopsis pilosula, exhibits binding affinity with the pivotal target Tumor Protein P53 (TP53). Conclusion The findings suggest that Codonopsis pilosula may elicit antidepressant effects through a multi-component, multi-target, and multi-pathway approach, laying a foundation for further exploration and clinical utilization of Codonopsis pilosula in the prevention and management of depression.
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Exploring the Antidepressant Mechanism of Codonopsis pilosula through Network Pharmacology and Molecular Docking Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring the Antidepressant Mechanism of Codonopsis pilosula through Network Pharmacology and Molecular Docking Analysis Mu Lin, Jiangrong Liao, Yadong Gong, Ran Xiao, Mubo Liu, Huihong Ding, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4706131/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To investigate the antidepressant properties and underlying mechanisms of Codonopsis pilosula using network pharmacology and molecular docking analysis. Methods The principal constituents of Codonopsis pilosula were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Genecards and the Online Mendelian Human Inheritance Database (OMIM) were utilized to gather genes associated with depression. Subsequently, Cytoscape software and the STRING database were employed to construct a components-targets network and protein interaction network models for Codonopsis pilosula. The DAVID database was applied for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the targets, while Autodock software was utilized for molecular docking of the primary active compounds of Codonopsis pilosula with its key targets. Results This investigation identified 18 primary components in Codonopsis pilosula, which have the potential to modulate numerous targets and impact 57 signaling pathways. Through integration of prior research findings and molecular docking validation, it was observed that Lobetyolin, the key constituent of Codonopsis pilosula, exhibits binding affinity with the pivotal target Tumor Protein P53 (TP53). Conclusion The findings suggest that Codonopsis pilosula may elicit antidepressant effects through a multi-component, multi-target, and multi-pathway approach, laying a foundation for further exploration and clinical utilization of Codonopsis pilosula in the prevention and management of depression. Depression Codonopsis pilosula Network pharmacology Apoptosis TP53/PI3K-AKT signaling pathway Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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