Prediction of drug-metabolite interactions with bioinformatics approaches: Potential applications for toxicological profile and drug development

Ciprofloxacin is a commonly prescribed fluoroquinolone group antibiotic due to its broad-spectrum antibacterial effects, easy accessibility and economic advantages. Adverse effects include systemic tendinosis, peripheral neuropathy, central nervous system stimulation, depression, memory disorders and suicidal thoughts. Although its neurotoxic effects have been demonstrated by various studies, the underlying mechanisms are not fully understood. In the body, it is converted into metabolites defined as desethyleneciprofloxacin, sulphocyprofloxacin, oxocyprofloxacin and N-formylcyprofloxacin. There are no adequate studies on the metabolites in relation to their toxicity. Bioinformatics contributes to the analysis and interpretation of biological data and is less costly than laboratory studies and is a tool that can be used in the collection, analysis and interpretation of biological data such as genomes, proteins, metabolic pathways. In this thesis, toxicogenomic analyses, protein-protein interactions, gene-gene interactions and molecular docking methods were used to comprehensively evaluate the neurotoxic potential of ciprofloxacin and its metabolites. According to the findings, both ciprofloxacin and its metabolites were shown to induce inflammatory factor-mediated neurotoxicity such as interleukin-1 beta (IL1B) and tumour necrosis factor-alpha (TNF-α). At this point, the relationship between oxidative stress and inflammatory processes resulting from the production ofreactive oxygen species (ROS) associated with ciprofloxacin is important.