QSAR analysis of a set of previously synthesized phosphonium ionic liquids (PILs) tested against Gram‐negative multidrug‐resistant clinical isolate Acinetobacter baumannii was done using the Online Chemical Modeling Environment (OCHEM). To overcome the problem of overfitting due to descriptor selection, fivefold cross‐validation with variable selection in each step of the model development was applied. The predictive ability of the classification models was tested by cross‐validation, giving balanced accuracies (BA) of 76%–82%. The validation of the models using an external test set proved that the models can be used to predict the activity of newly designed compounds with a reasonable accuracy within the applicability domain (BA = 83%–89%). The models were applied to screen a virtual chemical library with expected activity of compounds against MDR Acinetobacter baumannii . The eighteen most promising compounds were identified, synthesized, and tested. Biological testing of compounds was performed using the disk diffusion method in Mueller‐Hinton agar. All tested molecules demonstrated high anti‐A. baumannii activity and different toxicity levels. The developed classification SAR models are freely available online at http://ochem.eu/article/113921 and could be used by scientists for design of new more effective antibiotics.

中文翻译：

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在计算机上和体外研究了许多PIL作为针对MDR临床分离株鲍曼不动杆菌的新型抗菌剂。

一组针对革兰氏阴性多药耐药临床分离株鲍曼不动杆菌测试的先前合成的phospho离子液体（PIL）的QSAR分析使用在线化学建模环境（OCHEM）完成。为了克服由于描述符选择而导致的过拟合问题，在模型开发的每个步骤中都使用了带有变量选择的五重交叉验证。通过交叉验证测试了分类模型的预测能力，得出的平衡准确度（BA）为76％–82％。使用外部测试集对模型进行的验证证明，该模型可用于在适用范围内以合理的准确度预测新设计化合物的活性（BA = 83％–89％）。该模型被用于筛选虚拟化学文库，该文库具有预期的化合物抗MDR鲍曼不动杆菌的活性。鉴定，合成和测试了18种最有前途的化合物。使用圆盘扩散法在Mueller-Hinton琼脂中进行化合物的生物测试。所有测试的分子均显示出高的抗鲍曼不动杆菌活性和不同的毒性水平。可以在http://ochem.eu/article/113921上免费在线获得已开发的分类SAR模型，科学家可以将其用于设计更有效的新型抗生素。