Quantum chemical and molecular dynamics studies of imidazoline derivatives as corrosion inhibitor and quantitative structure–activity relationship (QSAR) analysis using the support vector machine (SVM) method
Quantum chemical and molecular dynamics studies of imidazoline derivatives as corrosion inhibitor and quantitative structure–activity relationship (QSAR) analysis using the support vector machine (SVM) method
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DOI：
10.1142/s0219633614500126
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发表时间：
2014-04
影响因子：
2.4
通讯作者：
Lei Du;Hongxia Zhao;Haixiang Hu;Xiuhui Zhang;Lin Ji;Hanlai Li;Yang Huan;Xiaochun Li;Shumin Shi;Ruijing Li;Tang Xiaoyong;Jing Yang
中科院分区：
文献类型：
--
作者：
Lei Du;Hongxia Zhao;Haixiang Hu;Xiuhui Zhang;Lin Ji;Hanlai Li;Yang Huan;Xiaochun Li;Shumin Shi;Ruijing Li;Tang Xiaoyong;Jing Yang
采用失重法和理论分析相结合的方法，研究了10种直链碳原子数为15 ~ 21的咪唑啉分子的缓蚀性能。主要目的是建立缓蚀剂结构与缓蚀效率之间的定量构效关系（QSAR），进而预测新型缓蚀剂的缓蚀效率。量子化学计算表明，咪唑啉分子的活性区域位于咪唑啉环和亲水基团上，活性中心集中在分子的氮原子和亲水基团的碳原子上。用分子动力学方法建立了符合真实的实验溶液的吸附模型，平衡构型表明咪唑啉分子以平行方式吸附在Fe（110）表面。通过主成分分析（PCA）选择描述子，采用支持向量机（SVM）方法建立QSAR模型，相关系数（R）为0.99，均方根误差（RMSE）为0.94，表现出良好的性能。此外，从理论上设计了6个新的咪唑啉分子，并通过所建立的QSAR模型预测了其中3个分子的缓蚀率均在86%以上。
The inhibition performance of 10 imidazoline molecules with number of carbon from 15 to 21 of hydrocarbon straight-chain was studied by weight-loss method and theoretical approaches. The main purpose was to build a quantitative structure–activity relationship (QSAR) between the structural properties and the inhibition efficiencies, and then to predict efficiencies of new corrosion inhibitors. The quantum chemical calculation suggested that the active region of imidazoline molecules was located on the imidazoline ring and hydrophilic group, and active sites were concentrated on the nitrogen atoms of the molecules and carbon atoms of hydrophilic group. A model in accordance with the real experimental solution was built in the molecular dynamics, and the equilibrium configuration indicated that the imidazoline molecules were adsorbed on Fe(110) surface in parallel manner. Descriptors for QSAR model building were selected by principal component analysis (PCA) and the model was built by the support vector machine (SVM) approach, which shows good performance since the value of correlation coefficient (R) was 0.99 and the root mean square error (RMSE) was 0.94. Additionally, six new imidazoline molecules were theoretically designed and the inhibition efficiencies of three molecules were predicted to be more than 86% by the established QSAR model.