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巫晓丹1,马清萍1,宋春磊2,林志芬2,#,印春生1,*. 磺胺类化合物对大肠杆菌突变QSAR预测模型初探[J]. 生态毒理学报, 2018, 13(5): 118-127
磺胺类化合物对大肠杆菌突变QSAR预测模型初探
QSAR Prediction Model Based on the Mutation Effect of Sulfonamides on Escherichia coli
投稿时间:2017-08-26  修订日期:2017-11-08
DOI:10.7524/AJE.1673-5897.20170826001
中文关键词:  磺胺类抗生素  大肠杆菌  突变效应  QSAR模型
英文关键词:sulfonamides  Escherichia coli  mutation  QSAR model
基金项目:同济大学污染控制与资源化研究国家重点实验室自主研究(重点)项目(PCRRK16007);国家自然科学面上基金(21577105, 21777123);国家水体污染控制与治理重大专项(2018ZX07109-1);上海市科学技术委员会科研计划课题(14DZ2261100, 17DZ1200103);环境化学与生态毒理学国家重点实验室开放基金课题(KF2016-11)
作者单位
巫晓丹1,马清萍1,宋春磊2,林志芬2,#,印春生1,* 1. 上海海洋大学海洋生态与环境学院上海 201306 2. 同济大学环境科学与工程学院污染控制与资源化研究国家重点实验室上海污染控制与生态安全研究院上海 200092 
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中文摘要:
      抗生素被广泛应用于医疗、农业和畜牧业等领域,但是长期滥用会促进细菌的突变作用。本文以大肠杆菌(E. coli)为受试生物,测定了10种磺胺类抗生素(SAs)单一暴露时对E. coli的突变效应,采用物化参数Ebinding(抗生素与其靶蛋白的相互作用能力)与突变效应参数lgRC0-2(最高可观测突变促进效应浓度)或lgRCmax(突变促进率最大值对应的浓度),建立了突变效应的QSAR模型,并采用雷达图进行验证。结果表明,lgRC0-2Ebinding模型和lgRCmaxEbinding、DMG(偶极矩)模型的拟合系数R2分别是0.888、0.873,即lgRC0-2或lgRCmaxEbinding相关性均较好,可能由于磺胺类化合物(SAs)会作用于叶酸合成通路,影响嘌呤、嘧啶碱基的合成,从而对E. coli的突变具有促进效应,且雷达图验证表明,上述2个模型均具有良好的内部预测能力。本研究有望为抗生素使用带来的生态风险评价以及药物设计提供相关指导。
  
AuthorAffiliation
Wu Xiaodan1, Ma Qingping1, Song Chunlei2, Lin Zhifen2,#, Yin Chunsheng1,*1. College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai 201306, China 2. College of Environmental Science and Engineering, Tongji University, State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
英文摘要:
      Antibiotics have been used in many fields, such as medical treatment, agriculture, livestock husbandry. However, the abuse of antibiotics has aroused many environmental problems, among which the antibiotics resistance genes are most concerned. In this study, 10 sulfanilamides (SAs) were determined for their effects on resistance mutations of Escherichia coli (E. coli). QSAR models of mutation effects have been constructed by using physicochemical parameter Ebinding (the ability of antibiotics to interact with their target proteins) and mutation effect parameters lgRC0-2 (the highest observable concentration of mutation promoting effect) and lgRCmax (the concentration corresponding to the maximum mutation promotion rate). Moreover, the QSAR models established in this study are verified by radar charts. The results suggest that the R2 values are 0.888, 0.873 in the models of lgRC0-2 and Ebinding, lgRCmax and Ebinding, DMG (Dipole moment), respectively, which shows that either lgRCmax or lgRC0-2 is well correlated with Ebinding. It can be speculated that SAs are involved in the synthesis pathway of folate, affecting the synthesis of purines and pyrimidines, which has a promoting effect on the mutations of E. coli. Moreover, the results of radar charts indicate that both models have benign internal predictive ability. This work can provide guidance for the ecological risk assessment of the use of antibiotics in the environment as well as the design of antibacterial drugs.
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