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Investigation of molecular mechanism of Ulmus davidiana against gastric cancer: A network pharmacology study incorporating gene expression data and molecular docking analysis

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dc.contributor.authorBhola, Shivam-
dc.contributor.authorJaiswal, Varun-
dc.contributor.authorLee, Hae-Jeung-
dc.date.accessioned2023-07-24T08:40:59Z-
dc.date.available2023-07-24T08:40:59Z-
dc.date.created2023-07-21-
dc.date.issued2023-08-
dc.identifier.issn0254-6299-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/88630-
dc.description.abstractUlmus davidiana (UD), has long been utilized in traditional medicine to treat various diseases, particularly gastric cancer (GC). However, the molecular mechanism behind its health-protective effect has yet to be clarified. An extensive literature search was conducted to collect all reported phytochemicals of the plant, which were then filtered for druglike properties. SwissTargetPrediction was utilized to predict targets for phytochemicals and functional enrichment of targets was performed for GO, pathways, and diseases. A network pharmacology approach was used to investigate all possible targets and targets specifically associated with GC. The expression of target genes was also studied for their expression in the TCGA patient GC dataset from TCGA through GEPIA 2.0. Cytoscape and STRING were used for network construction and analysis, while core targets and filtered phytochemicals were employed for molecular docking. In total, 396 targets for screened compounds, of which 242 targets were associated with GC. Among these, 87 targets were differentially expressed in GC. Several highly differentially expressed genes (MMP7, TOP2A, CCNB2, MMP12, and CCNB2) were found to be strongly associated with gastric cancer. Target enrichment categories were correlated with the known bioactivities of UD such as antioxidant, anti-inflammatory, and anticancer properties. Cancer and neurological complications-related diseases were prevalent in the associated disease network. The interferon-gamma signaling pathway was identified as the most enriched pathway for gastric cancer targets (GT). CCKR signaling was found to be the most connected pathway in the GC network. Core targets (HSP90AA1, STAT3, SRC, ESR1, and EGFR) were determined through protein-protein-interaction network analysis. Molecular docking revealed phytochemicals (torilin, 1-hydroxytorilin, and butyl alpha-Dfructofuranoside) with high docking scores and strong interactions with core targets. The key findings of the study, including phytochemicals, targets, and pathways, are suggested for further validation.& COPY; 2023 Published by Elsevier B.V. on behalf of SAAB.-
dc.language영어-
dc.language.isoen-
dc.publisherELSEVIER-
dc.relation.isPartOfSOUTH AFRICAN JOURNAL OF BOTANY-
dc.titleInvestigation of molecular mechanism of Ulmus davidiana against gastric cancer: A network pharmacology study incorporating gene expression data and molecular docking analysis-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid001016734200001-
dc.identifier.doi10.1016/j.sajb.2023.06.004-
dc.identifier.bibliographicCitationSOUTH AFRICAN JOURNAL OF BOTANY, v.159, pp.51 - 60-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85161310541-
dc.citation.endPage60-
dc.citation.startPage51-
dc.citation.titleSOUTH AFRICAN JOURNAL OF BOTANY-
dc.citation.volume159-
dc.contributor.affiliatedAuthorBhola, Shivam-
dc.contributor.affiliatedAuthorJaiswal, Varun-
dc.contributor.affiliatedAuthorLee, Hae-Jeung-
dc.type.docTypeArticle-
dc.subject.keywordAuthorGastric cancer-
dc.subject.keywordAuthorNetwork pharmacology-
dc.subject.keywordAuthorPhytochemicals-
dc.subject.keywordAuthorUlmus davidiana-
dc.subject.keywordPlusVAR. JAPONICA-
dc.subject.keywordPlusACTIVATION-
dc.subject.keywordPlusRECEPTOR-
dc.subject.keywordPlusCELLS-
dc.subject.keywordPlusAPOPTOSIS-
dc.subject.keywordPlusEXTRACT-
dc.subject.keywordPlusTARGET-
dc.subject.keywordPlusSRC-
dc.relation.journalResearchAreaPlant Sciences-
dc.relation.journalWebOfScienceCategoryPlant Sciences-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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