ArticleHeliyon2024
Combining bioinformatics, network pharmacology, and artificial intelligence to predict the mechanism of resveratrol in the treatment of rheumatoid arthritis.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Identifying coagulation-related biomarkers in steroid-induced osteonecrosis of the femoral head: implications for early diagnosis and treatment.Clinical and experimental medicine · 2026Article
- Integrative Network Toxicology, Machine Learning, Single-Cell Analysis, scTenifoldKnk-Based Virtual Knockout, and Molecular Docking Suggest a Potential Molecular Link Between Aspartame and Rheumatoid Arthritis InvolvingInternational journal of molecular sciences · 2026Article
- Resveratrol and Redox Regulation in Cardiovascular Disease Across the Life Course: Mechanistic and Translational Perspectives.Antioxidants (Basel, Switzerland) · 2026Review
- UPLC-Q-TOF/MS, network pharmacology, molecular docking, and experimental validation to explore the mechanisms of toad clothing on rheumatoid arthritis.Scientific reports · 2025Article
- Network Pharmacology-Driven Sustainability: AI and Multi-Omics Synergy for Drug Discovery in Traditional Chinese Medicine.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Harnessing network pharmacology in drug discovery: an integrated approach.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Rheumatoid arthritis (RA) is a chronic autoimmune disorder that causes joint inflammation and destruction, resulting in significant physical and economic burdens. Finding effective and targeted therapy for RA remains a top priority. Resveratrol is a potential candidate with anti-inflammatory and immunomodulatory properties for RA treatment. This study aims to determine the therapeutic targets and signaling pathways of resveratrol in the treatment of RA. Methods: The GSE205962 dataset downloaded from The Gene Expression Omnibus (GEO) database was used to obtain the differentially expressed genes (DEGs) in blood samples from the patients and the healthy. PharmMapper database and Cytoscape (v3.9.1) were applied to construct the resveratrol pharmacophore target network. Gene functional enrichment analysis, including the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, was based on the BiNGo plug-in of Cytoscape and David's online tool. The intersection of the target genes of resveratrol and the DEGs were considered potential therapeutic genes (PT-genes). The Protein-Protein Interaction (PPI) network of PT-genes was constructed using the STRING tool, and the key therapeutic genes (KT-genes) were determined using the cytoHubba plug-in based on the Maximal Clique Centrality (MCC) algorithms. Molecular docking validation of resveratrol and therapeutic targets was performed based on the protein structure of KT-genes predicted by AlphaFold. Results: A total of 2202 DEGs and 47PT-genes were identified. GO analysis showed that the three groups of genes, the DEGs, the resveratrol target genes, and the PT-genes, have similar results for the top-five gene functional enrichment. PT-genes were closely related to the pathways of metabolic pathways, pathways in cancer, proteoglycans in cancer, insulin signaling pathway, and chemokine signaling pathway. The common pathway enriched by KEGG for the DEGs, and the resveratrol target genes was up to 36 %. The nine KT-genes were ABL1, ANXA5, CASP3, HSP90AA1, LCK, MAP2K1, MAPK1, PIK3R1, and RAC1, and the lowest free energy indicating the resveratrol/protein affinity were -8.4, -7.4, -6.4, -6.7, -8.0, -7.9, -7.4, -6.7, and -7.9, respectively. Conclusion: Nine KT-genes were identified and validated as the most potential therapeutic targets in the treatment of RA with resveratrol, which provide new insights into therapeutic mechanisms and may improve the efficiency of drug development.
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