ArticleIranian journal of pharmaceutical research : IJPR
Elucidating the Molecular Mechanisms of
Article in Iranian journal of pharmaceutical research : IJPR. 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hepatocellular carcinoma (HCC) is a lethal liver malignancy associated with substantial morbidity and mortality and remains a major socioeconomic burden worldwide. Given the high risk associated with HCC, novel therapeutic approaches are urgently needed. Objectives: This study integrated computational network pharmacology, molecular docking, and in vitro cellular assays to elucidate the mechanisms by which Methods: Phytochemicals were identified using the Traditional Chinese Medicine Systems Pharmacology database and filtered according to drug-likeness and oral bioavailability criteria. Key compounds (β-sitosterol, alpha-cephalin, sitogluside, and stigmasterol) were further analyzed using the SuperPred Target Prediction tool to predict potential targets. HCC-related targets were curated from GeneCards and refined using the GeneCards Inferred Functionality Score. The overlap between compound-related and disease-specific targets was used to construct a protein-protein interaction network using STRING, which was subsequently visualized in Cytoscape to identify hub genes. Molecular docking between stigmasterol and the top 3 hub genes was evaluated using the CB-Dock2 online server, and all preparations were performed in BIOVIA Discovery Studio. In vitro, Hep-G2 cells were treated with varying concentrations (0, 25, 50, 100, and 200 µg/mL) of Results: In silico analysis identified an initial pool of 126 phytochemicals, which was refined to 4 key compounds yielding 139 unique targets. Intersection with HCC-related targets produced 123 common targets, generating a network comprising 119 nodes and 520 edges. STAT3, NFKB1, and TLR4 were identified as pivotal hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of the hub genes demonstrated significant enrichment in HCC-related pathways and biological processes. Molecular docking indicated a strong binding affinity of stigmasterol to STAT3, NFKB1, and TLR4, with binding energies of -7.8, -6.9, and -6.9 kcal/mol, respectively. In vitro assays showed a dose-dependent reduction in Hep-G2 cell viability and colony formation, significant induction of apoptosis, and marked inhibition of migration. Western blotting confirmed significant downregulation of STAT3, NFKB1, and TLR4 expression at higher extract concentrations. Conclusions: This study concluded that
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.