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Integration of Fuzzy Matter-Element Method and 3D-QSAR Model for Generation of Environmentally Friendly Quinolone Derivatives

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  • Xixi Li

    (Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Civil Engineering, Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL A1B 3X5, Canada)

  • Baiyu Zhang

    (Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Civil Engineering, Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL A1B 3X5, Canada)

  • Wendy Huang

    (Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Civil Engineering, Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL A1B 3X5, Canada)

  • Cuirin Cantwell

    (Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Civil Engineering, Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL A1B 3X5, Canada)

  • Bing Chen

    (Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Civil Engineering, Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL A1B 3X5, Canada)

Abstract

The environmental pollution of quinolone antibiotics (QAs) has caused rising public concern due to their widespread usage. In this study, Gaussian 09 software was used to obtain the infrared spectral intensity (IRI) and ultraviolet spectral intensity (UVI) of 24 QAs based on the Density Functional Theory (DFT). Rather than using two single-factor inputs, a fuzzy matter-element method was selected to calculate the combined effects of infrared and ultraviolet spectra (CI). The Comparative Molecular Field Analysis (CoMFA) was then used to construct a three-dimensional quantitative structure–activity relationship (3D-QSAR) with QAs’ molecular structure as the independent variable and CI as the dependent variable. Using marbofloxacin and levofloxacin as target molecules, the molecular design of 87 QA derivatives was carried out. The developed models were further used to determine the stability, functionality (genetic toxicity), and the environmental effects (bioaccumulation, biodegradability) of these designed QA derivatives. Results indicated that all QA derivatives are stable in the environment with their IRI, UVI, and CI enhanced. Meanwhile, the genetic toxicity of the 87 QA derivatives increased by varying degrees (0.24%–29.01%), among which the bioaccumulation and biodegradability of 43 QA derivatives were within the acceptable range. Through integration of fuzzy matter-element method and 3D-QSAR, this study advanced the QAs research with the enhanced CI and helped to generate the proposed environmentally friendly quinolone derivatives so as to aid the management of this class of antibiotics.

Suggested Citation

  • Xixi Li & Baiyu Zhang & Wendy Huang & Cuirin Cantwell & Bing Chen, 2020. "Integration of Fuzzy Matter-Element Method and 3D-QSAR Model for Generation of Environmentally Friendly Quinolone Derivatives," IJERPH, MDPI, vol. 17(9), pages 1-25, May.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3239-:d:354550
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    References listed on IDEAS

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    1. Xianxian Pan & Hong Liu & Jiajia Huan & Yu Sui & Haifeng Hong, 2020. "Allocation Model of Carbon Emission Permits for the Electric Power Industry with a Combination Subjective and Objective Weighting Approach," Energies, MDPI, vol. 13(3), pages 1-12, February.
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    Cited by:

    1. Łukasz Sikorski & Agnieszka Bęś & Kazimierz Warmiński, 2023. "The Effect of Quinolones on Common Duckweed Lemna minor L., a Hydrophyte Bioindicator of Environmental Pollution," IJERPH, MDPI, vol. 20(6), pages 1-17, March.
    2. Peixuan Sun & Wenjin Zhao, 2021. "Strategies to Control Human Health Risks Arising from Antibiotics in the Environment: Molecular Modification of QNs for Enhanced Plant–Microbial Synergistic Degradation," IJERPH, MDPI, vol. 18(20), pages 1-26, October.

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