Literature DB >> 32142973

Predicting mixture toxicity and antibiotic resistance of fluoroquinolones and their photodegradation products in Escherichia coli.

Dali Wang1, Qing Ning1, Jiayu Dong1, Bryan W Brooks2, Jing You3.   

Abstract

Antibiotics in the environment usually co-exist with their transformation products with retained toxicity, raising concerns about environmental risks of their combined exposure. Herein, we reported a novel predictive approach for evaluating the individual and combined toxicity for photodegradation products of fluoroquinolone antibiotics (FQs). Quantitative structure-activity relationship (QSAR) models with promising predictive performance were constructed and validated using experimental data obtained with 13 FQs and 78 mixtures towards E. coli. A structural descriptor reflecting the interaction among FQ molecules and the target protein was employed in the QSAR models, which was obtained through molecular docking and thus provided a rational mechanistic explanation for these models. The predicted results indicated that the degradation products displayed varying degrees of changes compared to the parent FQs, while the combined toxicity of FQs and their degradation products was mostly additive. Furthermore, following UV irradiation the degradation products displayed elevated capacity of inducing resistance mutations in E. coli, though their overall toxicity was reduced. This result highlights the implications of antibiotic degradation products on resistance development in bacteria and stresses the importance of considering such impacts during environmental risk assessments of antibiotics.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Combined toxicity; Fluoroquinolones; Photodegradation; QSAR; Resistance mutation

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Year:  2020        PMID: 32142973     DOI: 10.1016/j.envpol.2020.114275

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  2 in total

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Authors:  Izabella Kośka; Krystian Purgat; Paweł Kubalczyk
Journal:  Sci Rep       Date:  2022-05-11       Impact factor: 4.996

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Journal:  RSC Adv       Date:  2020-10-01       Impact factor: 4.036

  2 in total

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