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基于综合指数法的双活性(绿藻毒性和细菌遗传毒性)3D-QSAR 模型及其在氟喹诺酮类药物修饰中的应用。

A Double-Activity (Green Algae Toxicity and Bacterial Genotoxicity) 3D-QSAR Model Based on the Comprehensive Index Method and Its Application in Fluoroquinolones' Modification.

机构信息

Department of Chemistry, College of New Energy and Environment, Jilin University, Changchun 130012, China.

出版信息

Int J Environ Res Public Health. 2020 Feb 3;17(3):942. doi: 10.3390/ijerph17030942.

Abstract

The comparative molecular similarity index analysis (CoMSIA) model of double-activity quinolones targeting green algae toxicity and bacterial genotoxicity (8:2) was constructed in this paper on the basis of the comprehensive index method. The contour maps of the model were analyzed for molecular modifications with high toxicities. In the CoMSIA model, the optimum number of components was 7, the cross-validated value was 0.58 (>0.5), the standard deviation standard error of estimate (SEE) was 0.02 (<0.95), was 1265.33, and the non-cross-validated value was 1 (>0.9), indicating that the model had a good fit and predicting ability. The scrambling stability test parameters , cross-validated standard error of prediction (cSDEP), and d/dyy were 0.54, 0.25, and 0.8 (<1.2), respectively, indicating that the model had good stability. The external verification coefficient was 0.73 (>0.6), and standard error of prediction (SEP) was 0.17, indicating that the model had a good external prediction ability. The contribution rates of the steric fields, electrostatic fields, hydrophobic fields, hydrogen bond donor, and acceptor fields were 10.9%, 19.8%, 32.7%, 13.8%, and 22.8%, respectively. Large volume groups were selected for modification of ciprofloxacin (CIP), and the derivatives with increased double-activity characterization values were screened; the increase ratio ranged from 12.31-19.09%. The frequency of derivatives were positive and total energy, bioaccumulation, and environmental persistence was reduced, indicating that the CIP derivatives had good environmental stability and friendliness. Predicted values and CoMSIA model constructed of single activities showed that the CoMSIA model of double activities had accuracy and reliability. In addition, the total scores of the derivatives docking with the D1 protein, ferredoxin-NADP (H) reductases (FNRs), and DNA gyrase increased, indicating that derivatives can be toxic to green algae by affecting the photosynthesis of green algae. The mechanism behind the bactericidal effect was also explained from a molecular perspective.

摘要

基于综合指数法,本文构建了针对藻类毒性和细菌遗传毒性(8:2)的双效喹诺酮类化合物的分子相似性指数分析(CoMSIA)模型。对模型的轮廓图进行了分析,以寻找具有高毒性的分子修饰。在 CoMSIA 模型中,最佳成分数为 7,交叉验证值为 0.58(>0.5),估计标准误差(SEE)的标准偏差为 0.02(<0.95), 值为 1265.33,非交叉验证值为 1(>0.9),表明模型具有良好的拟合和预测能力。扰乱稳定性测试参数 、交叉验证预测标准误差(cSDEP)和 d/dyy 分别为 0.54、0.25 和 0.8(<1.2),表明模型具有良好的稳定性。外部验证系数 为 0.73(>0.6),预测标准误差(SEP)为 0.17,表明模型具有良好的外部预测能力。立体场、静电场、疏水场、氢键供体和受体场的贡献率分别为 10.9%、19.8%、32.7%、13.8%和 22.8%。选择较大体积的环丙沙星(CIP)进行修饰,并筛选出双活性特征值增加的衍生物;增加率范围为 12.31-19.09%。衍生物的频率为正,总能量、生物蓄积和环境持久性降低,表明 CIP 衍生物具有良好的环境稳定性和友好性。单活性的预测值和 CoMSIA 模型表明,双活性 CoMSIA 模型具有准确性和可靠性。此外,与 D1 蛋白、铁氧还蛋白-NADP(H)还原酶(FNRs)和 DNA 回旋酶对接的衍生物的总得分增加,表明衍生物可以通过影响藻类的光合作用对藻类产生毒性。从分子角度解释了杀菌作用的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5081/7037916/2a9a3180ab3a/ijerph-17-00942-g001.jpg

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