Rzycki Mateusz, Kraszewski Sebastian, Gładysiewicz-Kudrawiec Marta
Department of Experimental Physics, Faculty of Fundamental Problems of Technology, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland.
Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland.
Materials (Basel). 2021 Oct 27;14(21):6455. doi: 10.3390/ma14216455.
The widespread problem of resistance development in bacteria has become a critical issue for modern medicine. To limit that phenomenon, many compounds have been extensively studied. Among them were derivatives of available drugs, but also alternative novel detergents such as Gemini surfactants. Over the last decade, they have been massively synthesized and studied to obtain the most effective antimicrobial agents, as well as the most selective aids for nanoparticles drug delivery. Various protocols and distinct bacterial strains used in Minimal Inhibitory Concentration experimental studies prevented performance benchmarking of different surfactant classes over these last years. Motivated by this limitation, we designed a theoretical methodology implemented in custom fast screening software to assess the surfactant activity on model lipid membranes. Experimentally based QSAR (quantitative structure-activity relationship) prediction delivered a set of parameters underlying the Diptool software engine for high-throughput agent-membrane interactions analysis. We validated our software by comparing score energy profiles with Gibbs free energy from the Adaptive Biasing Force approach on octenidine and chlorhexidine, popular antimicrobials. Results from Diptool can reflect the molecule behavior in the lipid membrane and correctly predict free energy of translocation much faster than classic molecular dynamics. This opens a new venue for searching novel classes of detergents with sharp biologic activity.
细菌耐药性发展这一普遍问题已成为现代医学的关键问题。为了限制这种现象，人们对许多化合物进行了广泛研究。其中包括现有药物的衍生物，还有诸如双子表面活性剂等新型替代洗涤剂。在过去十年中，人们大量合成并研究了它们，以获得最有效的抗菌剂以及用于纳米颗粒药物递送的最具选择性的辅助剂。在最小抑菌浓度实验研究中使用的各种方案和不同的细菌菌株阻碍了近年来不同表面活性剂类别的性能基准测试。受此限制的推动，我们设计了一种在定制快速筛选软件中实施的理论方法，以评估表面活性剂对模型脂质膜的活性。基于实验的定量构效关系（QSAR）预测提供了一组参数，这些参数是Diptool软件引擎用于高通量药剂 - 膜相互作用分析的基础。我们通过将得分能量分布与来自适应性偏置力方法的吉布斯自由能进行比较，对奥替尼啶和洗必泰这两种常用抗菌剂进行了软件验证。Diptool的结果可以反映脂质膜中的分子行为，并且比经典分子动力学更快地正确预测转运自由能。这为寻找具有显著生物活性的新型洗涤剂开辟了新途径。
