Drug repurposing for rheumatoid arthritis: Identification of new drug candidates via bioinformatics and text mining analysis
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Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Rheumatoid arthritis (RA) is an autoimmune disease that results in the destruction of tissue by attacks on the patient by his or her own immune system. Current treatment strategies are not sufficient to overcome RA. In the present study, various transcriptomic data from synovial fluids, synovial fluid-derived macrophages, and blood samples from patients with RA were analysed using bioinformatics approaches to identify tissue-specific repurposing drug candidates for RA. Differentially expressed genes (DEGs) were identified by integrating datasets for each tissue and comparing diseased to healthy samples. Tissue-specific protein-protein interaction (PPI) networks were generated and topologically prominent proteins were selected. Transcription-regulating biomolecules for each tissue type were determined from protein-DNA interaction data. Common DEGs and reporter biomolecules were used to identify drug candidates for repurposing using the hypergeometric test. As a result of bioinformatic analyses, 19 drugs were identified as repurposing candidates for RA, and text mining analyses supported our findings. We hypothesize that the FDA-approved drugs momelotinib, ibrutinib, and sodium butyrate may be promising candidates for RA. In addition, CHEMBL306380, Compound 19a (CHEMBL3116050), ME-344, XL-019, TG100801, JNJ-26483327, and NV-128 were identified as novel repurposing candidates for the treatment of RA. Preclinical and further validation of these drugs may provide new treatment options for RA.
Açıklama
Anahtar Kelimeler
Autoimmune, rheumatoid arthritis, drug repurposing, text mining, bioinformatics
Kaynak
Autoimmunity
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
55
Sayı
3
