Mechanism of Slow Onset Enzyme Inhibition and Drug Target Residence Time

描述(申请人提供)：许多候选药物由于在第二阶段临床试验中缺乏疗效而失败。这种失败发生在所有治疗领域，主要原因是粪便在体内的疗效以及缺乏安全性(毒性)。我们假设，使用药物靶标停留时间(Tr)测量，以及其他化合物效力的热力学估计，将提高预测体内药物疗效的能力。由于我们对tr的重要性的认识大多是基于观察到的许多药物缓慢地从靶点解离这一事实，在特定的化合物系列中，tr和体内药物活性之间的相关性的证明，与药物药代动力学的知识相结合，将允许建立预测药物药效学的数学模型。这一目标是创新的，并将创造一种范式转变，即关于先导化合物(抑制剂、激动剂、拮抗剂)与其目标相互作用的信息既 收集并使用。为了实现这一目标，我们将结合使用X射线结晶学、定点诱变、化学合成和计算方法。特别是，与时间无关的分子动力学(MD)模拟将有助于揭示结合动力学测量所探测的特定原子水平的相互作用，并将提供动态信息来填补晶体结构中观察到的稳定状态之间的时间间隙。这将使用来自结核分枝杆菌(MtFabi)和金黄色葡萄球菌(SaFabi)的Fabi酶来实现，这两种酶都是临床相关的药物靶点。此外，虽然这两种酶都被二苯醚类化合物和第二个基于吡啶酮的相关系列所抑制，但通过相同的两步慢起诱导-匹配动力学机制，伴随着酶抑制的结构变化是不同的。因此，我们的目标是确定我们是否能够首先了解并合理地调节两种不同酶的停留时间，同时保持化合物类的恒定。这将提供一个将我们的知识转换到其他系统的平台。在目标1中，我们将阐明mtFabI的时间依赖性抑制的机制。时间相关的分子动力学模拟和X射线结晶学将用于确定导致最终酶-抑制剂复合体(E-I*)的过渡态的结构，并确定对时间相关抑制至关重要的关键相互作用。将设计出TR值增加的抑制剂。这将提供对诱导适配结合机制的详细理解。在目标2中，我们将确定saFabI的时间依赖性抑制的结构基础。这将使用动力和结构方法来实现。将合成更多的类似物来询问我们对缓慢起效的saFabI抑制的理解。在目标3中，我们将描述受体、抗生素后效应(PAE)和体内活性之间的关系。PAE是药物暴露和移除后对微生物生长的持续抑制，是微生物学中一种众所周知的、经常观察到的现象，对抗菌药的药代动力学和改进给药方案的发展具有广泛的意义。Tr对PAE的贡献以及最终在体内的抗菌活性将在金黄色葡萄球菌中进行评估。对活细胞的PAE测量将在体外和体内药物活性估计之间提供一座桥梁。这些研究将为在药物发现中利用滞留时间奠定基础。在更广泛的水平上，我们的研究将提供对蛋白质构象变化的时间依赖性的洞察以及这些变化如何与蛋白质功能直接相关，并将为探索其他系统中依赖于时间的酶抑制的结构基础提供平台。证明tr的重要性将导致铅化合物优化的范式转变。 公共卫生相关性：我们假设，除了测量药物发现管道中推进化合物的热力学亲和力外，还应使用药物靶标停留时间(Tr)。这是因为药物浓度在体内并不是恒定的。在目前的提案中，我们将阐明影响细菌靶标药物靶标寿命的分子因素。这些研究将为在药物发现中利用滞留时间奠定基础。在更广泛的水平上，我们的研究将提供对蛋白质构象变化的时间依赖性的洞察以及这些变化如何与蛋白质功能直接相关，并将为探索其他系统中依赖于时间的酶抑制的结构基础提供平台。证明药物靶向停留时间的重要性将导致先导化合物优化的范式转变。

DESCRIPTION (provided by applicant): Many drug candidates fail due to lack of efficacy in Phase II clinical trials. This failure occurs in all therapeutic areas and primarily stems from poo in vivo efficacy as well as lack of safety (toxicity). We hypothesize that the use of drug-target residence time (tR) measurements, together with other thermodynamic estimates of compound potency, would improve the ability to predict drug efficacy in vivo. Since much of our appreciation for the importance of tR is anecdotally based on the observation that many drugs dissociate slowly from their targets, demonstration of correlations between tR and in vivo drug activity within specific compound series would, when coupled with knowledge of drug pharmacokinetics, allow mathematical models to be created that predict drug pharmacodynamics. This goal is innovative and will create a paradigm shift in how information on the interaction of lead compounds (inhibitors, agonists, antagonists) with their targets is both gathered and used. To meet this goal, we will use a combination of X-ray crystallography, site-directed mutagenesis, chemical synthesis, and computational methods. In particular, time-independent molecular dynamics (MD) simulations will help unravel the specific atomic-level interactions that are probed by the binding kinetics measurements, and will provide dynamic information to fill in the gaps in time between the stable states observed in the crystal structure. This will be accomplished using the FabI enzymes from Mycobacterium tuberculosis (mtFabI) and Staphylococcus aureus (saFabI), both of which are clinically relevant drug targets. In addition, while both enzymes are inhibited by the diphenyl ether compound class, and a second related series based on pyridones, through the same two-step slow-onset induced-fit kinetic mechanism, the structural changes that accompany enzyme inhibition differ. Thus our goal is to determine whether we can first understand and then rationally modulate residence time in two distinct enzymes whilst keeping the compound class constant. This will provide a platform for translating our knowledge to other systems. In Aim 1 we will elucidate the mechanism for the time-dependent inhibition of mtFabI. Time-indendent MD simulations and X-ray crystallography will be used to determine the structure of the transition state leading to the final enzyme-inhibitr complex (E-I*) and to identify key interactions critical for time-dependent inhibition. Inhibitors with increased tR values will be designed. This will provide a detailed understanding of an induced-fit binding mechanism. In Aim 2 we will determine the structural basis for the time-dependent inhibition of saFabI. This will be accomplished using kinetic and structural approaches. Additional analogues will be synthesized to interrogate our understanding of slow-onset saFabI inhibition. In Aim 3 we will delineate the relationship between tR, post-antibiotic effect (PAE) and in vivo activity. The PAE is the persistent suppression of microbial growth following drug exposure and removal, and is a well-known and frequently observed phenomenon in microbiology with widely stated implications for antimicrobial pharmacokinetics and the development of improved dosing regimens. The contribution of tR to PAE and, ultimately, in vivo antibacterial activity will be evaluated in S. aureus. The PAE measurements on live cells will provide a bridge between in vitro and in vivo estimates of drug activity. These studies will provide a foundation for using residence time in drug discovery. At a broader level, our studies will provide insight into the time dependence of conformational changes in proteins and how these relate directly to protein function, and will provide a platform for exploring the structural basis for time-dependent enzyme inhibition in other systems. Demonstrating the importance of tR will lead to a paradigm shift in lead compound optimization. PUBLIC HEALTH RELEVANCE: We hypothesize that drug-target residence time (tR) should be used in addition to measurements of thermodynamic affinity for advancing compounds along the drug discovery pipeline. This is because drug concentration is not constant in vivo. In the current proposal we will elucidate the molecular factors that modulate drug-target lifetime for a bacterial target. These studies will provide a foundation for using residence time in drug discovery. At a broader level, our studies will provide insight into the time dependence of conformational changes in proteins and how these relate directly to protein function, and will provide a platform for exploring the structural basis for time-dependent enzyme inhibition in other systems. Demonstrating the importance of drug-target residence time will lead to a paradigm shift in lead compound optimization.