Mechanism of Slow Onset Enzyme Inhibition and Translation to Time-Dependent Drug Activity

许多候选药物在临床试验中失败，因为在人体中的体内功效差。我们推测 我们在预测体内药物疗效方面的成功率很低，这是因为我们依赖于体外 在恒定药物浓度下（平衡状态下）进行的药物活性评估 条件），而实际上药物浓度在人体内并不恒定。因此，我们建议 药物-靶点复合物形成和分解的动力学是调节 药物作用。在这项提案中，我们将阐明决定药物影响的分子因素- 靶向停留时间对体内药物活性的影响。这些研究将集中在FabI的抑制剂， 来自结核分枝杆菌的酶药物靶标，和来自结核分枝杆菌的酶药物靶标LpxC， 革兰氏阴性ESKAPE病原体。我们将定量细胞内事件，如 目标综合、目标退化和目标易损性之间存在相关性 药物-靶标停留时间和抗菌活性作为药物的函数测定 浓度.这包括去除药物后抗菌活性的延长 抗生素后效应（Post-antibiotic effect）我们将建立结构-动力学关系， 使用结构和功能的组合对FabI和LpxC的时间依赖性抑制 计算生物学结合酶动力学，合成FabI和LpxC抑制剂 延长目标攻击时间将使用一个数学模型， 动力学和药物药代动力学，预测全细胞中的抗菌活性， 感染的动物模型。提高从体外参数预测体内药物作用的能力 将对新治疗药物的发现产生巨大影响。

Many drug candidates fail in clinical trials due to poor in vivo efficacy in humans. We speculate that our poor success rate at predicting in vivo drug efficacy stems from a reliance on in vitro assessments of drug activity that are performed at constant drug concentration (under equilibrium conditions), when in fact drug concentration is not constant in the human body. We thus propose that the kinetics of drug-target complex formation and breakdown is a critical factor in modulating drug action. In this proposal we will elucidate the molecular factors that dictate the impact of drug- target residence time on in vivo drug activity. These studies will focus on inhibitors of FabI, an enzyme drug-target from Mycobacterium tuberculosis, and LpxC, an enzyme drug target from Gram negative ESKAPE pathogens. We will quantitate the role that intracellular events such as target (re)synthesis, target degradation and target vulnerability have on the correlation between drug-target residence time and antibacterial activity determined as a function of drug concentration. This includes the prolongation of antibacterial activity following removal of drug from the system (the post-antibiotic effect). We will develop structure-kinetics relationships for the time-dependent inhibition of FabI and LpxC using a combination of structural and computational biology coupled with enzyme kinetics, and synthesize inhibitors of FabI and LpxC with extended target engagement. A mathematical model will be used that links drug-target kinetics and drug pharmacokinetics with predictions of antibacterial activity in whole cells and animal models of infection. Improved ability to predict in vivo drug action from in vitro parameters will have a dramatic impact on the discovery of new therapeutic agents.