ArticleHeliyon2024
Bioinformatics analysis based on extracted ingredients combined with network pharmacology, molecular docking and molecular dynamics simulation to explore the mechanism of Jinbei oral liquid in the therapy of idiopathic pulmonary fibrosis.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed.
- Jinbei oral liquid for idiopathic pulmonary fibrosis: a randomized placebo-controlled trial.Scientific reports · 2025Trial
- Elucidating the Mechanism of Xiaoqinglong Decoction in Chronic Urticaria Treatment: An Integrated Approach of Network Pharmacology, Bioinformatics Analysis, Molecular Docking, and Molecular Dynamics Simulations.Current computer-aided drug design · 2026Article
- In vitro investigation of the toxicological mechanisms of Fingolimod (S)-phosphate in HEPG2 cells.Toxicology research · 2025Article
- Studying the efficacy of JBOL volatile components in idiopathic pulmonary fibrosis (IPF) using GC-MS and network pharmacology.Scientific reports · 2025Article
- Clozapine Induces Agranulocytosis via Inflammatory and Hematopoietic Cytokine Induction of the JAK-STAT Signaling Pathway: Evidence From Network Pharmacology and Molecular Docking.CNS neuroscience & therapeutics · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Jinbei oral liquid (JBOL), which is derived from a traditional hospital preparation, is frequently utilized to treat idiopathic pulmonary fibrosis (IPF) and has shown efficacy in clinical therapy. However, there are now several obstacles facing the mechanism inquiry, including target proteins, active components, and the binding affinity between crucial compounds and target proteins. To gain additional insight into the mechanisms underlying JBOL in anti-IPF, this study used bioinformation technologies, including network pharmacology, molecular docking, and molecular dynamic simulation, with a substantial amount of data based on realistic constituents. Methods: Using network pharmacology, we loaded 118 realistic compounds into the SwissTargetPrediction and SwissADME databases and screened the active compounds and target proteins. IPF-related targets were collected from the OMIM, DisGeNET, and GeneCards databases, and the network of IPF-active constituents was built with Cytoscape 3.10.1. The GO and KEGG pathway enrichment analyses were carried out using Metascape, and the protein-protein interaction (PPI) network was constructed to screen the key targets with the STRING database. Finally, the reciprocal affinity between the active molecules and the crucial targets was assessed through the use of molecular docking and molecular dynamics simulation. Results: A total of 122 targets and 34 tested active compounds were summarized in this investigation. Among these, kaempferol, apigenin, baicalein were present in high degree. PPI networks topological analysis identified eight key target proteins. AGE-RAGE, EGFR, and PI3K-Akt signaling pathways were found to be regulated during the phases of cell senescence, inflammatory response, autophagy, and immunological response in anti-IPF of JBOL. It was verified by molecular docking and molecular dynamics simulation that the combining way and binding energy between active ingredients and selected targets. Conclusions: This work forecasts the prospective core ingredients, targets, and signal pathways of JBOL in anti-IPF, which has confirmed the multiple targets and pathways of JBOL in anti-IPF and provided the first comprehensive assessment with bioinformatic approaches. With empirical backing and an innovative approach to the molecular mechanism, JBOL is being considered as a potential new medication.
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