{"title":"Repurposing thioridazine as a potential CD2068 inhibitor to mitigate antibiotic resistance in Clostridioides difficile infection","authors":"Methinee Pipatthana , Matthew Phanchana , Apiwat Sangphukieo , Sitthivut Charoensutthivarakul , Phurt Harnvoravongchai , Surang Chankhamhaengdecha , Pattaneeya Prangthip , Pattanai Konpetch , Chanakarn Sripong , Sarawut Wongphayak , Tavan Janvilisri","doi":"10.1016/j.csbj.2025.02.036","DOIUrl":null,"url":null,"abstract":"<div><div><em>Clostridioides difficile</em> infection (CDI) is a major public health issue, driven by antibiotic resistance and frequent recurrence. CD2068, an ABC protein in <em>C. difficile</em>, is associated with drug resistance, making it a potential target for novel therapies. This study explored FDA-approved non-antibiotic drugs for their ability to inhibit CD2068 through drug screening and experimental validation. Thioridazine exhibited moderate binding affinity to CD2068 and inhibited its ATP hydrolysis activity. It also suppressed the growth of multiple <em>C. difficile</em> ribotypes at 64–128 µg/mL, with rapid-killing effects. When combined with sub-MIC levels of standard antibiotics, thioridazine significantly reduced bacterial growth. In a mouse CDI model, thioridazine demonstrated potential in restoring gut microbial balance and improving survival, although it did not show superiority to vancomycin. These findings suggest that thioridazine has potential as a novel therapeutic for CDI, either as an adjunct to existing antibiotics or as part of a combination therapy to combat antibiotic resistance. Further research, including replication studies and dose optimization, is needed to fully evaluate thioridazine’s therapeutic potential.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 887-895"},"PeriodicalIF":4.4000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and structural biotechnology journal","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2001037025000649","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Clostridioides difficile infection (CDI) is a major public health issue, driven by antibiotic resistance and frequent recurrence. CD2068, an ABC protein in C. difficile, is associated with drug resistance, making it a potential target for novel therapies. This study explored FDA-approved non-antibiotic drugs for their ability to inhibit CD2068 through drug screening and experimental validation. Thioridazine exhibited moderate binding affinity to CD2068 and inhibited its ATP hydrolysis activity. It also suppressed the growth of multiple C. difficile ribotypes at 64–128 µg/mL, with rapid-killing effects. When combined with sub-MIC levels of standard antibiotics, thioridazine significantly reduced bacterial growth. In a mouse CDI model, thioridazine demonstrated potential in restoring gut microbial balance and improving survival, although it did not show superiority to vancomycin. These findings suggest that thioridazine has potential as a novel therapeutic for CDI, either as an adjunct to existing antibiotics or as part of a combination therapy to combat antibiotic resistance. Further research, including replication studies and dose optimization, is needed to fully evaluate thioridazine’s therapeutic potential.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology