Network pharmacology-based analysis of the role of tacrolimus in liver transplantation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33732042", "kind": "science-record", "revision": 4, "content_hash": "sha256:ad6bc5a7cc7e8e5398949df3b42258b0b7ff2c294ea638e3fbd32abe98a21917", "created_at": "2026-11-01T15:41:29Z", "updated_at": "2026-11-01T21:24:54Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Network pharmacology-based analysis of the role of tacrolimus in liver transplantation.", "doi": "10.1016/j.sjbs.2020.12.050", "pmid": "33732042", "authors": ["Lijian Chen", "Yuming Peng", "Chunyi Ji", "Miaoxian Yuan", "Qiang Yin"], "journal": "Saudi journal of biological sciences", "year": 2021, "abstract": "BACKGROUND: Tacrolimus is a powerful immunosuppressant and has been widely used in organ transplantation. In order to further explore the role of tacrolimus in liver transplantation, we conducted network pharmacology analysis.\nMETHODS: GSE100155 was obtained from the GEO database, and the DEGs of liver transplantation were analyzed. The 2D structure of tacrolimus was obtained from the National Library of Medicine, and the pharmacophore model of tacrolimus was predicted using the online tool pharmmapper. Then a network of tacrolimus and target genes was constructed through network pharmacology, and visualization and GO enrichment analysis was performed through Cytoscape. In addition, we also analyzed the correlation between key genes and immune infiltrating cells. The data of GSE84908 was used to verify the changes of key gene expression levels after tacrolimus treatment.\nRESULTS: The results of network pharmacological analysis showed that tacrolimus had 43 target genes, and the GO enrichment results showed many potential functions. Further analysis found that there were 5 key target genes in DEGs, and these 5 genes were significantly down-regulated in liver transplant patients. Another important finding was that 5 genes were significantly related to some immune infiltrating cells. The results of the GSE84908 data analysis showed that after tacrolimus treatment, the expression of DAAM1 was significantly increased (p = 0.015).\nCONCLUSION: Tacrolimus may inhibit the human immune response by affecting the expression of DAAM1 in liver transplant patients.", "claims": [{"id": "claim-data-access", "statement": "The GSE100155 (liver transplant) and GSE84908 (comparison of gene expression of human mesangial cells after 24 h Tacrolimus vs. control) data were obtained from the GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33732042", "locator": "sections[3] \"Data collection\" paragraph 2", "quote": "The GSE100155 (liver transplant) and GSE84908 (comparison of gene expression of human mesangial cells after 24 h Tacrolimus vs. control) data were obtained from the GEO database."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33732042"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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