Screening and preliminary validation of anti-gout drugs based on transcriptomics

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Author: ZOU Qian ^1, ² ZHANG Peng ³ CHEN Qiuling ^1, ² LIN Siqi ^1, ² YAN Xue ^1, ²  CHEN Penglong ^1, ²

Affiliation: 1. Department of Pharmacy, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510422, China 2. Guangdong Clinical Resarch Academy of Chinese Medicine, Guangzhou 510422, China 3 .Clinical Medical College/Pharmacy Department of Jiujiang University Affiliated Hospital, Jiujiang 332000, Jiangxi Province, China

Keywords: Gout Connectivity map Transcriptome Uric acid Mitogen-activated protein kinase

DOI: 10.12173/j.issn.2097-4922.202501056

Reference: ZHOU Qian, ZHANG Peng, CHEN Qiuling, LIN Siqi, YAN Xue, CHEN Penglong. Screening and preliminary validation of anti-gout drugs based on transcriptomics[J]. Yaoxue QianYan Zazhi, 2025, 29(7): 1081-1089. DOI: 10.12173/j.issn.2097-4922.202501056.[Article in Chinese]  Copied

Abstract
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Abstract

Objective To explore new anti-gout drugs based on transcriptomics and conduct preliminary validation.

Methods Gout transcriptome data were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were screened using thresholds of |logFC|>1 and P<0.05. KEGG pathway enrichment analysis and protein-protein interaction (PPI) network analysis were performed on the DEGs. Candidate gout drugs were predicted via connectivity map (CMap), with molecular docking assessing binding affinity, and the compounds’ absorption, distribution, metabolism, excretion, and toxicity properties were evaluated. An in vitro model of uric acid-induced injury in human renal proximal tubular epithelial (HK-2) cells was established to examine the effects of PD-98059 on interleukin (IL)-6 and tumor necrosis factor-alpha (TNF-α) expression in HK-2 cells.

Results A total of 373 DEGs were identified in the GSE214587 gout dataset, including 228 upregulated and 145 downregulated genes, primarily enriched in signaling pathways such as TNF signaling pathway, NF-κB signaling pathway, C-type lectin receptor signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway. PPI network analysis revealed C-C motif chemokine ligand 2 (CCL2), colony stimulating factor 2 (CSF2), TNF, mitogen-activated protein kinase kinase 1 (MAP2K1), prostaglandin-endoperoxide synthase 2 (PTGS2), suppressor of cytokine signaling 3 (SOCS3), cluster of differentiation (CD) 86, CD40, C-X-C motif chemokine ligand (CXCL) 1, vascular endothelial growth factor A (VEGFA), CD14, CD274, B-cell lymphoma-2 gene (Bcl-2), CXCL2, steroid receptor coactivator (SRC), and IL-1 receptor antagonist as core genes involved in gout pathogenesis. CMap platform predictions identified mitogen-activated protein kinase kinase (MEK) inhibitors as potential gout treatments, with six predicted MEK inhibitors demonstrating good druggability and safety, as well as strong binding affinity to MEK proteins. Cell validation experiments indicated that PD-98059 can reverse uric acid-induced upregulation of TNF-α and IL-6 expression.

Conclusion The integration of transcriptomics and CMap drug discovery provides a novel approach for the development of anti-gout medications.

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