Antibacterial Activity of Imidazolium-Based Ionic Liquids Investigated by QSAR Modeling and Experimental Studies
作者:Diana Hodyna、Vasyl Kovalishyn、Sergiy Rogalsky、Volodymyr Blagodatnyi、Kirill Petko、Larisa Metelytsia
DOI:10.1111/cbdd.12770
日期:2016.9
Twenty synthesized samples of 1,3‐dialkylimidazolium ionic liquids with predictive value of activity level of antimicrobial potential were evaluated. For all asymmetric 1,3‐dialkylimidazolium ionic liquids, only compounds containing at least one radical with alkyl chain length of 12 carbon atoms showed high antibacterial activity. However, the activity of symmetric 1,3‐dialkylimidazolium salts was found
枯草芽孢杆菌和Ps抑制剂的预测QSAR模型。咪唑鎓离子液体中的铜绿是利用文学数据开发的。回归QSAR模型是通过人工神经网络和k最近邻程序创建的。使用WEKA‐RF(随机森林)方法构建了QSAR分类模型。通过五重交叉验证测试了模型的预测能力;给q 2对于回归模型= 0.77–0.92,对于分类模型,准确度为83–88%。评价了20个合成的1,3-二烷基咪唑鎓离子液体的样品,这些样品对抗菌潜能的活性水平具有预测价值。对于所有不对称的1,3-二烷基咪唑鎓离子液体,只有含有至少一个烷基链长为12个碳原子的基团的化合物才具有较高的抗菌活性。但是,发现对称的1,3-二烷基咪唑鎓盐的活性与基于1,3-二辛基咪唑鎓阳离子的化合物的脂族基团的长度最大相反。获得的实验结果表明,分类QSAR模型的应用对于预测新型咪唑类ILs作为潜在抗菌药的活性更为准确。