Target vulnerability correlates the level of drug-target engagement required to generate a pharmacological response. High vulnerability targets are those that require only a relatively small fraction of occupancy to achieve the desired pharmacological outcome, whereas low vulnerability targets require high levels of engagement. Here, we demonstrate that the slope of the correlation between drug-target residence time and the post-antibiotic effect (PAE) can be used to define the vulnerability of bacterial targets. For macrolides, a steep slope is observed between residence time on the E. coli ribosome and the PAE, indicating that the ribosome is a highly vulnerable drug target. The analysis of the residence time-PAE data for erythromycin, azithromycin, spiramycin, and telithromycin using a mechanistic pharmacokinetic-pharmacodynamic model that integrates drug-target kinetics into predictions of drug activity lead to the successful prediction of the cellular PAE for tylosin, which has the longest residence time (7.1 h) and PAE (5.8 h). Although the macrolide data support a connection between residence time, PAE, and bactericidality, many bactericidal β-lactam antibiotics do not give a PAE, illustrating the role of factors such as protein resynthesis in the expression of target vulnerability.

中文翻译：

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关联药物目标停留时间和抗生素后作用：深入了解目标脆弱性。

目标脆弱性与产生药理反应所需的药物目标参与水平相关。高脆弱性目标是那些只需要相对较小的占用率即可达到所需药理结果的目标，而低脆弱性目标则需要较高的参与度。在这里，我们证明了药物靶标停留时间与抗生素后作用（PAE）之间的相关性斜率可用于定义细菌靶标的脆弱性。对于大环内酯类药物，在大肠杆菌核糖体和PAE上的停留时间之间观察到一个陡峭的斜率，这表明核糖体是高度脆弱的药物靶标。对红霉素，阿奇霉素，螺旋霉素的停留时间-PAE数据进行分析，和替利霉素使用机械药代动力学-药效学模型，该模型将药物靶标动力学整合到药物活性预测中，从而成功预测了泰乐菌素的细胞PAE，它具有最长的停留时间（7.1小时）和PAE（5.8小时）。尽管大环内酯类药物数据支持停留时间，PAE和杀菌性之间的联系，但许多杀菌的β-内酰胺抗生素均未提供PAE，这说明了蛋白质重新合成等因素在靶标易感性表达中的作用。