Antibacterial Activity of Imidazolium-Based Ionic Liquids Investigated by QSAR Modeling and Experimental Studies

作者：Hodyna Diana; Kovalishyn Vasyl; Rogalsky Sergiy; Blagodatnyi Volodymyr; Petko Kirill; Metelytsia Larisa

来源：Chemical Biology & Drug Design, 2016, 88(3): 422-433.

DOI：10.1111/cbdd.12770

<jats:p>Predictive <jats:styled-content style="fixed-case">QSAR</jats:styled-content> models for the inhibitors of <jats:italic><jats:styled-content style="fixed-case">B</jats:styled-content>. subtilis</jats:italic> and <jats:italic><jats:styled-content style="fixed-case">P</jats:styled-content>s. aeruginosa</jats:italic> among imidazolium‐based ionic liquids were developed using literary data. The regression <jats:styled-content style="fixed-case">QSAR</jats:styled-content> models were created through <jats:styled-content style="fixed-case">A</jats:styled-content>rtificial <jats:styled-content style="fixed-case">N</jats:styled-content>eural <jats:styled-content style="fixed-case">N</jats:styled-content>etwork and <jats:italic>k</jats:italic>‐nearest neighbor procedures. The classification <jats:styled-content style="fixed-case">QSAR</jats:styled-content> models were constructed using <jats:styled-content style="fixed-case">WEKA</jats:styled-content>‐<jats:styled-content style="fixed-case">RF</jats:styled-content> (random forest) method. The predictive ability of the models was tested by fivefold cross‐validation; giving <jats:italic>q</jats:italic><jats:sup>2</jats:sup> = 0.77–0.92 for regression models and accuracy 83–88% for classification models. 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 to have opposite relationship with the length of aliphatic radical being maximum for compounds based on 1,3‐dioctylimidazolium cation. The obtained experimental results suggested that the application of classification <jats:styled-content style="fixed-case">QSAR</jats:styled-content> models is more accurate for the prediction of activity of new imidazolium‐based <jats:styled-content style="fixed-case">IL</jats:styled-content>s as potential antibacterials.</jats:p>

• 出版日期2016-9