Quantitative Structure−Activity Relationship Model for Prediction of Genotoxic Potential for Quinolone Antibacterials
2007; American Chemical Society; Volume: 41; Issue: 13 Linguagem: Inglês
10.1021/es070031v
ISSN1520-5851
AutoresJianying Hu, Wanfeng Wang, Lezhu Zhou, Hong Chang, Feng Pan, Bin‐Le Lin,
Tópico(s)Antibiotic Resistance in Bacteria
ResumoAntibiotics are of concern because of their widespread usage, their potential role in the spread and maintenance of bacterial resistance, and because of the selection pressure on microbes. In this study, the genotoxic potential of 20 quinolone antibacterials, including 5 first-generation, 8 second-generation, and 7 third-generation quinolones, was determined. While all of the antibacterials studied showed genotoxic potential, the molar concentration for each antibacterial that produces 10% (EC10) of the maximum response of corresponding antibacterial ranged from 0.61 to 2917.0 nM, and was greatly dependent on chemical structures. A quantitative structure−activity relationship (QSAR) was established by applying a quantum chemical modeling method to determine the factors required for the genotoxic potential of quinolone antibacterials. The octanol−water coefficient (logPow) adjusted by the pH and energies of the highest occupied molecular orbital (εHOMO) and lowest unoccupied molecular orbital (εLUMO) were selected as hydrophobic and electronic chemical descriptors, respectively. The genotoxic potentials of quinolone antibacterials were found to be dependent on their logPow and εHOMO, while the effects of εLUMO on the genotoxic potentials could not be identified. The QSAR model was also used to predict the genotoxic potentials for 14 quinolone antibacterials, including 1 second-generation, 2 third-generation, and 11 fourth-generation quinolone antibacterials. A correlation between the genotoxic potentials and their minimal inhibition concentrations (MIC50) against Streptococcus pneumoniae from the literature for 18 quinolone antibacterials was observed, providing a potential method to estimate MIC50.
Referência(s)