Academic Journal
Elucidating the therapeutic targets and multi-target mechanisms of salvianolic acid A for diabetic nephropathy.
| Τίτλος: | Elucidating the therapeutic targets and multi-target mechanisms of salvianolic acid A for diabetic nephropathy. |
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| Συγγραφείς: | Fu T; Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixian'ge Street, Xicheng District, Beijing, 100053, People's Republic of China., Xiong Z; Hubei Provincial Hospital of Traditional Chinese Medicine, No. 4, Huaishu Gang Road, Wuchang District, Wuhan, 430065, Hubei Province, People's Republic of China., Tao H; The Second Affiliated Hospital of Liaoning, University of Traditional Chinese Medicine, No. 33, Beiling Street, Huanggu District, Shenyang, 110034, Liaoning Province, People's Republic of China. taohw@126.com., Zhan Y; Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No. 5, Beixian'ge Street, Xicheng District, Beijing, 100053, People's Republic of China. 18812519897@163.com. |
| Πηγή: | Mammalian genome : official journal of the International Mammalian Genome Society [Mamm Genome] 2026 Jun 24; Vol. 37 (1). Date of Electronic Publication: 2026 Jun 24. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Springer-Verlag Country of Publication: United States NLM ID: 9100916 Publication Model: Electronic Cited Medium: Internet ISSN: 1432-1777 (Electronic) Linking ISSN: 09388990 NLM ISO Abbreviation: Mamm Genome Subsets: MEDLINE |
| Imprint Name(s): | Publication: New York, NY : Springer-Verlag Original Publication: New York, NY, USA : Springer International, c1991- |
| Ιατρικοί όροι (MeSH): | Diabetic Nephropathies*/drug therapy , Diabetic Nephropathies*/genetics , Diabetic Nephropathies*/metabolism , Diabetic Nephropathies*/pathology , Lactates*/pharmacology , Lactates*/therapeutic use , Lactates*/chemistry , Caffeic Acids*/pharmacology , Caffeic Acids*/chemistry , Caffeic Acids*/therapeutic use, Podocytes/drug effects ; Podocytes/metabolism ; Podocytes/pathology ; Humans ; Molecular Docking Simulation ; Animals |
| Περίληψη: | Diabetic nephropathy (DN) is a leading cause of chronic kidney disease. Salvianolic acid A (SAA) has shown promising therapeutic potential against DN, yet its underlying mechanisms and precise molecular targets remain incompletely elucidated. Potential targets of SAA were predicted using SwissTargetPrediction and SuperPred, with its drug-like properties evaluated by ADMET analysis. Diabetic nephropathy (DN)-related targets were collected from GEO, CTD, and GeneCards databases. Shared targets underwent GO and KEGG enrichment analyses. Core targets were identified through topological analysis in Cytoscape, machine learning, and Mendelian randomization validation. Molecular docking and dynamics simulations assessed the binding affinity and stability between SAA and core targets. Single-cell RNA sequencing data revealed their cell type-specific expression in kidney tissues. Experimental validation was performed using an in vitro high glucose-induced podocyte injury model analyzed by RT-qPCR. The intersection of 212 drug targets with 5,097 disease targets yielded 134 potential therapeutic targets for salvianolic acid A in DN. Machine learning and Mendelian randomization further identified eight targets with causal relationships to DN. Molecular docking demonstrated strong binding affinities of salvianolic acid A to the domains of FYN, AKR1B1, TNF, GALK1, HMGCR, MAP2K2, SCN4A, and ITGA5. Single-cell analysis revealed distinct expression patterns across different renal cell types. In vitro experiments demonstrated that SAA effectively protected podocytes from HG-induced injury. SAA alleviates diabetic nephropathy through multi-target mechanisms, influencing key genes involved in disease progression. This study provides a systematic elucidation of the therapeutic basis for SAA and supports its further clinical development. (© 2026. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.) |
| Competing Interests: | Declarations. Competing interests: The authors declare no competing interests. Ethical approval: Not applicable. Consent for publication: Not applicable. Disclosure statement: No potential conflict of interest was reported by the authors. |
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| Contributed Indexing: | Keywords: Diabetic Nephropathy; Experimental validation; Machine learning; Network pharmacology; Salvianolic acid A; Single-cell analysis |
| Substance Nomenclature: | 51622542XO (salvianolic acid A) 0 (Lactates) 0 (Caffeic Acids) |
| Entry Date(s): | Date Created: 20260624 Date Completed: 20260624 Latest Revision: 20261010 |
| Update Code: | 20261010 |
| DOI: | 10.1007/s00335-026-10246-z |
| PMID: | 42342966 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1432-1777 |
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| DOI: | 10.1007/s00335-026-10246-z |