Gentiopicroside targeting AKT1 activates HIF-1α/VEGF axis promoting diabetic ulcer wound healing.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40078292", "kind": "science-record", "revision": 4, "content_hash": "sha256:b3b4a106768fb96f30b00e34262e16f4e84b0b98940634712ff1a7ed7fd937a6", "created_at": "2026-11-01T20:30:17Z", "updated_at": "2026-11-01T22:56:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Gentiopicroside targeting AKT1 activates HIF-1α/VEGF axis promoting diabetic ulcer wound healing.", "doi": "10.3389/fphar.2025.1506499", "pmid": "40078292", "authors": ["Xinxia Wang", "Mingyan Liu", "Yao Wu", "Jianguo Sun", "Li Liu", "Zheng Pan"], "journal": "Frontiers in pharmacology", "year": 2025, "abstract": "Backgound: Gentiopicroside (GSP) have been proven to accelerate the healing of diabetic ulcers (DU), but the underlying molecular mechanisms remain unclear. This study aims to explore the mechanism by which GSP accelerates the healing of DU.\nMethod: The targets of GSP were firstly predicted using the SuperPred, SwissTargetPrediction, and Pharmmapper databases; DU-related transcriptome data were obtained from the GEO database, including GSE147890, GSE68183, and GSE199939; differential expression analysis was conducted using the Limma package, and DU-related targets were identified after summarization and de-duplication. Then, Potential targets for GSP treatment of DU were screened by Venn analysis; core targets for GSP treatment of DU were selected by constructing a protein-protein interaction (PPI) network; the mechanism of GSP treatment of DU was predicted by GO and KEGG enrichment analysis. Finally, the target binding of GSP to core targets was evaluated by molecular docking and CETSA assay, and in vitro experiments were conducted using L929 cells to validate the findings.\nResult: A total of 538 targets of GSP and 10795 DU-related targets were predicted; Venn analysis identified 215 potential targets for GSP to accelerate DU wound healing; PPI network analysis suggested that AKT1 may be core targets for GSP treatment of DU; GO and KEGG enrichment analysis showed that pathways such as HIF-1 and VEGF are closely related to the treatment of DU with GSP, and it also participates in the regulation of various biological processes such as small molecule catabolism and leukocyte migration to exert its therapeutic effect on DU. Molecular docking and CETSA detection indicated that GSP can target bind to AKT1. The experimental results confirmed that GSP can significantly promote the proliferation and migration of L929 cells. Westen Blot results showed that GSP can accelerate DU wound healing via AKT1/HIF-1α/VEGF axis.\nConclusion: GSP target binding to AKT1 accelerates DU wound healing via the regulation of HIF-1α/VEGF axis.", "claims": [{"id": "claim-method", "statement": "differential expression analysis was conducted using the Limma package, and DU-related targets were identified after summarization and de-duplication.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40078292", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "differential expression analysis was conducted using the Limma package, and DU-related targets were identified after summarization and de-duplication."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40078292", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Differential-expression analysis using the Limma package on three GEO diabetic-ulcer transcriptomic datasets identified 10,795 DU-associated targets, and intersection with predicted GSP targets yielded 215 potential targets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40078292", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The targets of GSP were firstly predicted using the SuperPred, SwissTargetPrediction, and Pharmmapper databases; DU-related transcriptome data were obtained from the GEO database, including GSE147890, GSE68183, and GSE199939; differential expression analysis was conducted using the Limma package, and DU-related targets were identified after summarization and de-duplication."}, {"asset": "source:pmid:40078292", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 538 targets of GSP and 10795 DU-related targets were predicted; Venn analysis identified 215 potential targets for GSP to accelerate DU wound healing; PPI network analysis suggested that AKT1 may be core targets for GSP treatment of DU; GO and KEGG enrichment analysis showed that pathways such as HIF-1 and VEGF are closely related to the treatment of DU with GSP, and it also participates in the regulation of various biological processes such as small molecule catabolism and leukocyte migration to exert its therapeutic effect on DU."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Differential-expression analysis using the Limma package on three GEO diabetic-ulcer transcriptomic datasets identified 10,795 DU-associated targets, and intersection with predicted GSP targets yielded 215 potential targets.", "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:40078292"], "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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