ArticleMedicine2025
Network pharmacology and molecular docking to explore the potential mechanism of Codonopsis pilosula delaying aging.
Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundCodonopsis pilosula (CP), a traditional Chinese medicine, holds considerable potential in antioxidant and antiaging properties, however, the antiaging mechanism of its active components have been scarcely documented.
methodsNetwork pharmacology was employed to predict the active components of CP and elucidate its underlying antiaging mechanisms. Active components of CP were retrieved from traditional Chinese medicine systems pharmacology, followed by screening targets from GeneCards. Protein-protein interaction networks were constructed using String and analyzed with Cytoscape. Pathway enrichment was done using gene ontology and Kyoto encyclopedia of genes and genomes. Finally, molecular docking of active compounds with core targets was performed using Autodock and PyMOL.
resultsOur study identified 21 active components of CP targeting 433 targets, and 2906 aging-related targets. By overlapping, 232 key targets emerged, including 14 core antiaging targets. CP regulated aging through targets such as AKT1, TNF, and SRC, as well as pathways including lipid metabolism, cancer progression, and estrogen signaling, and so on. Molecular docking demonstrated that both luteolin and 7-(β-xylosyl) cephalomannine_qt exhibited strong binding affinity to these key targets.
conclusionIn short, network pharmacology analyses screened active components of CP, predicted antiaging targets and pathways, thereby establishing a basis for subsequent product development and mechanistic research.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.