Evidence map›Paper›PMID 39623711›Full record

ArticleCurrent computer-aided drug design2026

Mechanisms Underlying the Attenuating Effects of Bugantang on Liver Fibrosis Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

Taojing Zhang, Jia Chang, Zengle Zheng, Guobi Chen, Yiping Wu, Jinxiang Xiang, Jing Chen

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Article in Current computer-aided drug design, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Taojing ZhangSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Jia ChangSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Zengle ZhengSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Guobi ChenSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Yiping WuSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Jinxiang XiangSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Jing ChenSchool of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.

Funding

National Undergraduate Innovation and Entrepreneurship Training Program 202310344021
6 · The paper itself

Abstract

backgroundLiver fibrosis, a chronic liver disease, threatens people's health, increases the burden of healthcare, and currently lacks effective treatment measures. Bugantang (BGT) is a traditional Chinese herbal prescription from Jin Kui Yi with promising potential for treating liver fibrosis. Despite this potential, the efficacy and mechanism for treating liver fibrosis remain unclear.

objectiveTo primarily prove the efficacy, predict the active components of BGT, and explore the mechanism of BGT on liver fibrosis.

methodsThe liver condition of CCL4-induced mice was examined using hematoxylin and eosin staining. The targets and active compounds of BGT were sourced from HERB and TCMSP databases, while the targets related to liver fibrosis were acquired from DisGeNET, Gene Expression Omnibus, and GeneCards databases. The core targets were identified, and the network of protein-protein interactions was established. KEGG and GO analyses were performed on DAVID. Molecular docking and molecular dynamics simulations assessed the active components' interactions with potential targets. RESULTS AND DISCUSSION: A total of 215 targets and 152 active compounds were identified for BGT. The network analysis identified kaempferol, quercetin, 2-(2,4-dihydroxyphenyl)-7-hydroxy- 4H-chromen-4-one, sitosterol, naringenin, adenosine, plo, and beta-sitosterol as potential key compounds, and AKT1, MMP9, SRC, TNF, ESR1, NF-κB, and PPARG as potential key targets. KEGG and GO analyses revealed that the therapeutic effect of BGT on liver fibrosis may be associated with the PI3K-AKT and MAPK signaling pathways, as well as cell apoptosis, protein phosphorylation, and inflammation. Molecular docking demonstrated high-affinity binding of the identified targets to the active compounds. Additionally, molecular dynamics simulation further confirmed that the bindings of AKT1-beta-sitosterol and MMP9-quercetin exhibited good stability.

conclusionsThe potential of BGT in alleviating liver fibrosis may be attributed to a combination of various active compounds, targets, and pathways. These results could support the use of BGT in treating liver fibrosis and facilitate the development of new drug candidates for this condition.

Indexed as

Drugs, Chinese HerbalLiver CirrhosisAnimalsCarbon TetrachlorideHumansMaleMiceMolecular Docking SimulationMolecular Dynamics SimulationNetwork PharmacologySignal TransductionCarbon TetrachlorideDrugs, Chinese HerbalBugantanggene expression omnibusliver fibrosismolecular dockingmolecular dynamics simulationnetwork pharmacology

Identifiers

PMID39623711

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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 OpenQuestion graph.