ArticleEvidence-based complementary and alternative medicine : eCAM2021
A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect.
Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed.
- Article
- Network Pharmacology and Experimental Validation to Elucidate the Pharmacological Mechanisms of Luteolin Against Chondrocyte Senescence.Combinatorial chemistry & high throughput screening · 2025Article
- Baicalein Alleviates Osteoarthritis Progression in Mice by Protecting Subchondral Bone and Suppressing Chondrocyte Apoptosis Based on Network Pharmacology.Frontiers in pharmacology · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe purpose of our research is to systematically explore the multiple mechanisms of
methodsThe components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape software was used to build a component-target network. The targets of DD were collected from DisGeNET, PharmGKB, TTD, and OMIM. Protein-protein interactions (PPIs) among the DD targets were executed to screen the key targets. Afterward, the GO and KEGG pathway enrichment analysis were performed by the KOBAS database. A compound-target-KEGG pathway network was built to analyze the key compounds and targets. Finally, the potential active substances and targets were validated by molecular docking.
resultsA total of 55 active compounds in HF, 646 compound-related targets, and 527 DD-related targets were identified from public databases. After treated with PPI, 219 key targets of DD were acquired. The gene enrichment analysis suggested that HF probably benefits DD patients by modulating pathways related to the nervous system, endocrine system, amino acid metabolism, and signal transduction. The network analysis showed the critical components and targets of HF on DD. Results of molecular docking increased the reliability of this study.
conclusionsIt predicted and verified the pharmacological and molecular mechanism of HF against DD from a holistic perspective, which will also lay a foundation for further experimental research and rational clinical application of DD.
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Registered trials
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