Computer-aided drug discovery methods play a major role in the development of therapeutically important small molecules, but their performance needs to be improved. Molecular dynamics simulations in mixed solvents are useful in understanding protein–ligand recognition and improving molecular docking predictions. In this work, we used ethanol as a cosolvent to find relevant interactions for ligands toward protein kinase G, an essential protein of Mycobacterium tuberculosis (Mtb). We validated the hot spots by screening a database of fragment-like compounds and another one of known kinase inhibitors. Next, we performed a pharmacophore-guided docking simulation and found three low micromolar inhibitors, including one with a novel chemical scaffold that we expanded to four derivative compounds. Binding affinities were characterized by intrinsic fluorescence quenching assays, isothermal titration calorimetry, and the analysis of melting curves. The predicted binding mode was confirmed by X-ray crystallography. Finally, the compounds significantly inhibited the viability of Mtb in infected THP-1 macrophages.

中文翻译：

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基于共溶剂位点的结核分枝杆菌蛋白激酶 G 抑制剂的发现

计算机辅助药物发现方法在治疗重要的小分子的开发中发挥着重要作用，但它们的性能需要改进。混合溶剂中的分子动力学模拟有助于理解蛋白质-配体识别和改进分子对接预测。在这项工作中，我们使用乙醇作为助溶剂来寻找配体与蛋白激酶 G 的相关相互作用，蛋白激酶 G 是结核分枝杆菌( Mtb ) 的必需蛋白。）。我们通过筛选片段样化合物和另一种已知激酶抑制剂的数据库来验证热点。接下来，我们进行了药效团引导的对接模拟，发现了三种低微摩尔抑制剂，包括一种具有新型化学支架的抑制剂，我们将其扩展到四种衍生化合物。通过内在荧光猝灭测定、等温滴定量热法和熔解曲线分析来表征结合亲和力。通过 X 射线晶体学证实了预测的结合模式。最后，这些化合物显着抑制了感染的 THP-1 巨噬细胞中Mtb的活力。