Designing the DNA-Intercalating Moiety to Improve the Safety and Efficacy of Novel Bacterial Topoisomerase Inhibitors
Abstract
Novel bacterial topoisomerase inhibitors (NBTIs) target bacterial topoisomerases through binding modes distinct from fluoroquinolones but are often limited by hERG channel inhibition. Our previous findings indicated that the introduction of a non-aminopiperidine linker and a halogenated phenyl enzyme-binding moiety can partially reduce cardiotoxicity. In this paper, we describe whether optimizing the DNA-intercalating 1,5-naphthyridine moiety could further improve safety while maintaining antibacterial potency. Several optimized compounds showed strong enzyme inhibition and potent antibacterial activity, particularly against Gram-positive pathogens. Compound 13 displayed broad-spectrum activity, with MICs as low as 0.008 μg/mL against Gram-positive and 0.125 μg/mL against Gram-negative bacteria. Safety profiling revealed reduced cytotoxicity and hERG binding compared to earlier series. Compounds 6, 20, 24, and 25 were nontoxic in zebrafish embryo assays. Compound 13 showed toxicity only at high doses and protected embryos in a lethalStaphylococcus aureus infection model, highlighting its potential as a preclinical lead.
Read the paper
Related studies
- Horizontal gene transfer in the human gastrointestinal tract: potential spread of antibiotic resistance genes
- Mutation supply and relative fitness shape the genotypes of ciprofloxacin-resistant Escherichia coli
- Genomic Survey of E. coli From the Bladders of Women With and Without Lower Urinary Tract Symptoms
- Characterization of cefotaxime-resistant urinary Escherichia coli from primary care in South-West England 2017–18
- Fitness cost constrains the spectrum of marR mutations in ciprofloxacin-resistant Escherichia coli
- Emerging evidence-based innovative approaches to control catheter-associated urinary tract infection: a review
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.